text:
## Background

Although it is very simple, Sewall Wright’s infinite island model of migration is a useful way to explore how drift, migration, and mutation interact to influence the genetic structure of populations that are divided into subpopulations. In this model we assume that

1. Every allele introduced into a population differs from any of the resident alleles.

2. Every population receives the same fraction, $$m$$, of migrants.1

Given those assumptions and assuming an infinite alleles model of mutation, we showed that2

$F_{ST} = \frac{1}{4N_e(m + \mu) + 1} \quad .$

A more realistic model of migration is the finite island model of migration.3 It’s still very simple, but it adds one thing that makes it a bit more realistic:

It assumes that there are a finite number of populations exchanging migrants with one another. Every population still receives the same fraction of migrants, $$m$$, but we now also specify that the fraction of migrants coming from any one population into this one is $$m/(k - 1)$$, where $$k$$ is the number of popuations.

The formula for $$F_{ST}$$ under the finite island model is a lot more complicated than the one above. If you’re interested, you can look in the R code below.4 Let’s compare the predictions for a few values of $$m$$ and $$k$$ with $$N_e = 100$$ and $$\mu = 10^{-3}$$.

### Comparing the predictions

rm(list = ls())

infinite_island <- function(n_e, m, mu) {
return(1/(4*n_e*(m + mu) + 1))
}

lambda <- function(mu, m, k) {
m_prime <- m*k/(k - 1)
l <- (1/2)*((1 - mu)^(-2)*(1- m_prime)^(-2) - 1)
return(l)
}

gamma <- function(mu, m, k) {
m_prime <- m*k/(k - 1)
g <- (1 + m_prime*(2 - m_prime)/(k*mu*(2 - mu)*(1 - m_prime)^2))^(-1)
return(g)
}

finite_island <- function(n_e, m, mu, n_islands) {
l <- lambda(mu, m, n_islands)
g <- gamma(mu, m, n_islands)
h_s <- 4*n_e*l*g/(4*n_e*l*g + 1)
h_b <- h_s*(1 + 4*n_e*l)/(4*n_e*l)
h_t <- ((n_islands - 1)/n_islands)*h_b + (1/n_islands)*h_s
f_st <- (h_t - h_s)/h_t
return(f_st)
}

n_e <- 100
mu <- 10^(-4)
k_vals <- rep(c(5, 25, 250, 2500), 2)
m_vals <- c(rep(0.01, 4), rep(0.05, 4))
dat <- data.frame(k = k_vals,
m = m_vals,
Infinite = rep(NA, length(k_vals)),
Finite = rep(NA, length(m_vals)),
Ratio = rep(NA, length(k_vals)))
for (i in 1:nrow(dat)) {
dat$Infinite[i] <- infinite_island(n_e, dat$m[i], mu)
dat$Finite[i] <- finite_island(n_e, dat$m[i], mu, dat$k[i]) dat$Ratio[i] <- dat$Infinite[i]/dat$Finite[i]
}
round(dat, 3)

### Comparing predictions to simulations

From the table above, it’s apparent that predictions of the infinite island and finite island models are rather different when the number of islands is small. Let’s run a simulation of the finite island model and see how well the simulation results match up to each prediction.

library(tidyverse)
Registered S3 methods overwritten by 'dbplyr':
method         from
print.tbl_lazy
print.tbl_sql
── Attaching packages ───────────────────────────── tidyverse 1.3.1 ──
✓ ggplot2 3.3.5     ✓ purrr   0.3.4
✓ tibble  3.1.4     ✓ dplyr   1.0.7
✓ tidyr   1.1.3     ✓ stringr 1.4.0
✓ readr   2.0.1     ✓ forcats 0.5.1
── Conflicts ──────────────────────────────── tidyverse_conflicts() ──
x dplyr::lag()    masks stats::lag()
library(hierfstat)

initialize <- function(k, n_loci) {
p <- array(dim = c(n_loci, k, 2))
for (j in 1:n_loci) {
for (i in 1:k) {
p[j, i, 1] <- runif(n = 1, min = 0, max = 1)
p[j, i, 2] <- 1 - p[j, i, 1]
}
}
return(p)
}

make_symmetric_matrix <- function(m, k) {
M <- diag(x = 1 - m, nrow = k)
for (i in 1:(k - 1)) {
for (j in (i+1):k) {
M[i, j] <- m/(k-1)
M[j, i] <- M[i, j]
}
}
return(M)
}

sample_two_alleles <- function(p) {
allele_1 <- ((runif(1) < p) + 1)*10
allele_2 <- (runif(1) < p) + 1
return(allele_1 + allele_2)
}

make_sample <- function(p, n_sample) {
n_pops <- dim(p)[2]
n_loci <- dim(p)[1]
names <- paste("Locus", seq(1:n_loci), sep = "")
pops <- numeric(n_pops*n_sample)
ct <- 1
for (k in 1:n_pops) {
population <- paste("Population", k, sep = "")
for (i in 1:n_sample) {
pops[ct] <- population
ct <- ct + 1
}
}
locus_data <- matrix(nrow = n_pops*n_sample, ncol = n_loci)
for (i in 1:n_loci) {
ct <- 1
for (k in 1:n_pops) {
for (n in 1:n_sample) {
locus_data[ct, i] <- sample_two_alleles(p[i, k, 1])
ct <- ct + 1
}
}
}
df <- data.frame(locus_data)
colnames(df) <- paste("Locus", seq(1:n_loci), sep = "")
df$Population <- pops df <- relocate(df, Population) return(df) } simulate <- function(n_e, m, mu, n_islands, n_loci, n_gen, n_sample) { p <- initialize(n_islands, n_loci) M <- make_symmetric_matrix(m, n_islands) V <- make_symmetric_matrix(mu, 2) g_st <- numeric(n_loci) p_star <- array(dim = c(n_loci, n_islands, 2)) for (i in 1:n_gen) { for (k in 1:n_loci) { p_star[k, , ] <- M %*% p[k, , ] %*% V for (j in 1:n_islands) { p[k, j, ] <- rmultinom(1, 2*n_e, p_star[k, j, ])/(2*n_e) } mu_p <- mean(p[k, , 1]) g_st[k] <- ((n_islands - 1)/n_islands)*var(p[k, , 1])/(mu_p*(1 - mu_p)) } } df <- make_sample(p, n_sample) return(wc(df)$FST)
}

run_simulation <- function(n_e, m, mu, n_islands, n_loci, n_gen,
n_sample, n_repetitions)
{
f_st <- numeric(n_repetitions)
for (i in 1:n_repetitions) {
if (n_repetitions > 50) {
cat(".", sep="")
if ((i %% 50) == 0) {
cat(i, "\n", sep ="")
}
}
f_st[i] <-simulate(n_e, m, mu, n_islands, n_loci, n_gen, n_sample)
}
return(f_st)
}

plot_simulation <- function(f_st, n_e, m, mu, n_islands) {
df <- data.frame(F_st = f_st)
p <- ggplot(df, aes(x = F_st)) +
geom_histogram(bins = 20, alpha = 0.4) +
geom_vline(xintercept = infinite_island(n_e, m, mu),
linetype = "dashed",
color = "red") +
geom_vline(xintercept = finite_island(n_e, m, mu, n_islands),
linetype = "dashed",
color = "blue") +
ggtitle(paste("N_e = ", n_e, ", m = ", m, ", mu = ", mu,
", n_islands = ", n_islands, sep = "")) +
theme_bw()
return(p)
}

f_st <- run_simulation(100, 0.05, 1e-4, 5, 10, 1000, 25, 100)
..................................................50
..................................................100
plot_simulation(f_st, 100, 0.05, 1e-4, 5)

The dashed red line is the prediction from the infinite island model. The dashed blue line is the prediction from the finite island model.

## Exercise 6

The last plot shows that neither the infinite island nor the finite island prediction captures the results of this particular simulation very well, it only does so on average and there’s a lot of variation from one replicate to the next. This outcome reflects the “evolutionary” or “genetic” sampling we discussed when comparing Nei’s $$G_{ST}$$ with Weir and Cockerham’s $$\theta$$. This weeks lab exercise will explore that variability a bit further and explore condidtions that affect the amount of variability and how useful the infinite island approximation is. To do so, you’ll want to use the following code.5 You’ll be changing some or all of

• n_loci - The number of loci included in the genetic sample,
• n_sample - The number of (diploid) individuals sampled in each population,
• n_gen - The number of generations for which to run the simulation, and
• n_repetitions - The number of times to repeat the simulation for any set of the first three choices. This item corresponds to the number of evolutionary or genetic sampling events included in your simulation.

For each choice of these four parameters, the simulation will run through all combinations of N_e = (25, 200, 250, 500), m = (0.05, 0.01, 0.005, 0.001), mu = (0.001, 0.0001), and n_islands = (10, 25, 50).

n_loci <- 10
n_sample <- 25
n_gen <- 1000
n_repetitions <- 10

df <- data.frame(N_e = NA, m = NA, mu = NA, n_islands = NA, Observed = NA,
Infinite = NA, Finite = NA)
for (n_e in c(25, 100, 250, 500)) {
for (m in c(0.05, 0.01, 0.005, 0.001)) {
for (mu in c(0.001, 1e-4)) {
for (n_islands in c(10, 25, 50)) {
cat("N_e = ", n_e, ", m = ", m, ", mu = ", mu,
"n_islands = ", n_islands, "\n" )
f_st <- run_simulation(n_e, m, mu, n_islands, n_loci, n_gen,
n_sample, n_repetitions)
N_e = rep(n_e, n_repetitions),
m = rep(m, n_repetitions),
mu = rep(mu, n_repetitions),
n_islands = rep(n_islands, n_repetitions),
Observed = f_st,
Infinite = infinite_island(n_e, m, mu),
Finite = finite_island(n_e, m, mu, n_islands))
}
}
}
}
df <- filter(df, !is.na(N_e))

Running one set of simulations for a particular choice of n_loci, n_sample, n_gen, and n_repetitions takes close to half an hour on my MacBook. You’ll get a printout periodically that lets you know what the current set of parameters being simulated is, and you’ll see the set or parameters that’s already been completed. Because running the simulation for one set of parameters takes so long, you can’t possibly explore all of the combinations of those parameters you might be interested in, but I’d like you to explore at least five and address the following questions:6

1. Are there conditions under which the predictions of the infinite island and finite island model are similar enough that we don’t need to worry about the added mathematical complexity of the finite island model?

2. How close is the relationship between observed estimates of $$F_{ST}$$ from the simulations and those predicted from the infinite island model? from the finite island model?

3. Under what conditions is the observed variation in $$F_{ST}$$ relatively small?

### A few hints

The easiest way to run different combinations of parameters is to copy the code block above and replace n_loci, n_sample, n_gen, and n_repetitions with new choices. To keep track of what you’re doing, I recommend doing that for one combination of parameters, examining the results as described below, and moving on to a new set of parameter (with a new code block) after that.

You can plot the observed $$F_{ST}$$ versus the $$F_{ST}$$ predicted from either model using the code below.7 In addition to showing how well the simulations match the predictions, you can get a feel for how much variabiity there is among the simulations by seeing how scatterd the points are.

## for the infinite island model
##
p <- ggplot(df, aes(x = Infinite, y = Observed)) +
geom_point() +
geom_abline(intercept = 0, slope = 1, linetype = "dashed",
color = "red") + theme_bw()
p
## for the finite island model
##
p <- ggplot(df, aes(x = Finite, y = Observed)) +
geom_point() +
geom_abline(intercept = 0, slope = 1, linetype = "dashed",
color = "red") + theme_bw()
p

If you’d like a more quantitative way to compare the models,8 a simple way is to run linear regressions of Observed on Infinite and Expected like this:

summary(lm(Observed ~ Infinite, data = df))
summary(lm(Observed ~ Finite, data = df))

If predictions were perfect the (Intercept) term in the regression would be 0, and the other term (Infinite in the first regression and Finite in the second) would be 1. Given the variability of the simulations, you won’t see numbers that are exactly 0 or 1. You can judge whether they are “close” by noticing whether the number in the Estimate column is more than two standard errors away from what you predict.

The residual standard error below the table measures how much error there is around the regression, i.e., it gives you a way to compare quantitatively how much variation there is in $$F_{ST}$$.

1. Notice that $$m$$ is the backwards migration rate, i.e., the fraction of a population composed of migrants that come from another population, not the fraction of residents that migrate to another population.↩

2. Actually, we didn’t show what happens with both migration and mutation, but from what we saw you can probably guess where this came from.↩

3. Latter, B.D.H. 1973. The island model of population differentiation: a general solution. Genetics 73:147-157 doi: 10.1093/genetics/73.1.147↩

4. You won’t find the formula for $$F_{ST}$$ in Latter, but the formulas in the R code follow from the results there.↩

5. Notice that in order to run this code, you’ll also need to run the code above so that the relevant functions are loaded in R’s memory.↩

6. Keep in mind that you’ll only be able to answer these questions for the set of simulations that you complete. I’ll be grading your responses on the simulation results that you show, not on what an exhaustive examination of all possibilities might be.↩

7. The diagonal red dashed line is the 1:1 line. Every point should fall on this line if observed exactly matches the prediction.↩

8. And I’d encourage you to take a more quantitative approach↩


text:
How to change the way LibGDX scales images?

I'm using FillViewport and OrthographicCamera. LibGDX is scaling my images rather badly - jagged edges, visible pixels. How can I change the scaling method?

by the way, I'm pretty sure the issue isn't my images. I've scaled them using imaging software and they look a lot better than when LibGDX scales them.

You can set filters for Libgdx textures using setFilter() method. For eg., try setting the filter to:
yourTexture.setFilter(TextureFilter.MipMapLinearNearest,TextureFilter.Nearest);

format: plain


text:
# Journey of the Heavenly Storm Dragon

(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Journey of the Heavenly Storm Dragon
Spell information
Nickname jhsd
Guild Wizards
Type Offensive
Description Summons an elemental serpent from the sky to strike targets.
GP cost 100
Mind space 75
Thaums 15
Components lightable torch (consumed), staff
Tome Heavenly Arts

Journey of the Heavenly Storm Dragon (abbreviated as JHSD) is a offensive spell that summons a serpent to attack one or more targets. It can only be cast outside.

## Casting

This spell costs 100 GP to cast and takes up 75 units of mind space.

If cast while holding anything metal (be it an unpicker, a staff, a knife, some cutlery, a shield... anything that counts as being metallic), the JHSD will channel down into you doing many multiple thousands of damage, nearly destroying the metal item and very likely killing the caster in the process. It is suggested you only ever cast JHSD using an alias that "unholds all" or "unholds all except klein bottles" before casting, for safety.

If cast indoors, the cast will fail with the line; "You suddenly realise you're not outdoors, but not before hurling the torch straight up into the air, bursting it against the ceiling in a shower of hot sparks that rain down upon you." This will do a randomised amount of fire damage (1-500 damage measured) to you, unless you have a fire HEB shield in effect, which will protect you fully from this molten rain.

### Skills

Spellcheck results
 Scale 300 325 350 375 400 425 450 475 500 525 550

The following skills are used in the stages of this spell:

### Casting messages

Casting

You spit into the air.
You think of dragon's breath as you blow forcefully into the air, whistling a strange melodic dirge.
You strike the end of your staff solidly into the ground, setting it humming with power.
With your mind in focus, you sling the torch into the sky and meditate on all the summoned elements.

Success

A crackling blue serpent arrives from above, and flies toward the <target> in a flash of fury.

Failure

*A humming red serpent arrives from above, spins around you and flies off again ignoring the <target> totally.
*Thunder like a dragon roaring cuts through the air, then dies out again.

Note: Failing to control the serpent will result in it turning on the unfortunate caster.

Details needed.

To others

Geryon Womblesworth spits into the air.
Geryon Womblesworth presses his lips together and starts whistling a strange melodic dirge to the sky above.
Geryon Womblesworth pummels his staff solidly into the ground.
Geryon Womblesworth slings a torch into the sky and gazes into the heavens intently.
Geryon Womblesworth swings his staff at the torch as it falls.
A crackling blue serpent arrives from above, nods at Geryon Womblesworth and flies towards the <target> in a flash of fury.

### Degrees of success

The serpent can do varying degrees of damage.

• The serpent whips the <target> and makes his hair stand on end.
• The serpent wraps the <target> in its tail and spews red orbs of energy at his chest before fading away. Comically, the <target> now seems extra crispy as thaumic smoke curls away from his feet.
• The serpent engulfs the <target> in a flash of red, and there comes the smell of burning flesh.
• The serpent bites the <target> and red ribbons stream from every part of his body.
• The serpent passes completely through the <target>. A hole smokes where a torso used to be!

Details needed.


text:
## imqwerty one year ago save me answer this!!!

1. imqwerty

We have a quadrilateral ABCD with AB+CD+AC=20cm and the area of quadrilateral is 50cm^2. Find the length of diagonal BD.

2. imqwerty

3. imqwerty

@dan815

4. anonymous

i think problem is lacking information

5. imqwerty

no this is the whole problem.

6. imqwerty

what kind of information do we need other than provided nd how can we relate the information given above with that extra information that is needed.

7. anonymous

give some context about this problem, is it a school problem? maybe olimpics or something, idk. I think i need information about the quadrilateral, is it a trapezoid, or maybe a parallelogram. Does the problem comes with a graph?

8. imqwerty

no this information is nt given nd this is nt a school problem

9. anonymous

It's a university problem then

10. anonymous

course?

11. imqwerty

idk it ws given to me by my math professor at coaching

12. anonymous

All i can think of is Brahmagupta's formula $A=\sqrt{(s-a)(s-b)(s-c)(s-d)}$ where s=a+b+c+d, and a,b,c,d are the sides of the quadrilateral but i dont have any information about the quadrilateral being inscribed in a circle. So i'm sorry, i can't help you, keep bumping and maybe someone does it

13. imqwerty

thanks @RicardoDelfin


text:
# How to sketch y=(-3x^2 +1)/(x^2)

How to sketch y=(-3x^2 +1)/(x^2)

Related Precalculus Mathematics Homework Help News on Phys.org
Mentallic
Homework Helper

$$\frac{-3x^2+1}{x^2}=\frac{-3x^2}{x^2}+\frac{1}{x^2}=-3+\frac{1}{x^2}$$
so now you should be able to sketch the graph using already known graphs such as $y=\frac{1}{x^2}$


text:
# American Institute of Mathematical Sciences

2011, 2011(Special): 209-218. doi: 10.3934/proc.2011.2011.209

## Non ordered lower and upper solutions to fourth order problems with functional boundary conditions

 1 University of Santiago de Compostela, Department of Mathematical Analysis, Santiago de Compostela, Galicia 2 Centro de Investigação em Matemática e Aplicações da U.E. (CIMA-CE), Rua Romão Ramalho 59, 7000-671 Évora 3 Departamento de Matemática. Universidade de Évora, Centro de Investigação em Matemática e Aplicaçoes da U.E. (CIMA-UE), Rua Romão Ramalho, 59. 7000-671 Évora

Received  July 2010 Revised  April 2011 Published  October 2011

In this paper, given $f : I \times (C(I))^2 \times \mathbb{R}^2 \leftarrow \mathbb{R}$ a $L^1$ Carathéodory function, it is considered the functional fourth order equation $u^(iv) (x) = f(x, u, u', u'' (x), u''' (x))$ together with the nonlinear functional boundary conditions $L_0(u, u', u'', u (a)) = 0 = L_1(u, u', u'', u' (a))$ $L_2(u, u', u'', u'' (a), u''' (a)) = 0 = L_3(u, u', u'', u'' (b}, u''' (b)):$ Here $L_i, i$ = 0; 1; 2; 3, are continuous functions satisfying some adequate monotonicity assumptions. It will be proved an existence and location result in presence of non ordered lower and upper solutions and without monotone assumptions on the right hand side of the equation.
Citation: Alberto Cabada, João Fialho, Feliz Minhós. Non ordered lower and upper solutions to fourth order problems with functional boundary conditions. Conference Publications, 2011, 2011 (Special) : 209-218. doi: 10.3934/proc.2011.2011.209
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Impact Factor:


text:
Article

# Detection and Discrimination of Volatile Organic Compounds using a Single Film Bulk Acoustic Wave Resonator with Temperature Modulation as a Multiparameter Virtual Sensor Array

Authors:
To read the full-text of this research, you can request a copy directly from the authors.

## Abstract

This paper describes the detection and discrimination of volatile organic compounds (VOCs) using an e-nose system based on a multiparameter virtual sensor array (VSA), which consists of a single-chip temperature-compensated film bulk acoustic wave resonator (TC-FBAR) coated with 20-bilayer self-assembled PSS / PDDA thin films. The high-frequency and microscale FBAR multiparameter VSA was realized by temperature modulation, which can greatly re-duce the cost and complexity compared to those of a traditional e-nose system and can allow it to operate at different temperatures. The discrimination effect depends on the synergy of temperature modulation and the sensing material. For proof-of-concept validation purposes, the TC-FBAR was exposed to six different VOC vapors at six different gas par-tial pressures by real-time VOC static detection and dynamic detection. The resulting frequency shifts and impedance responses were measured at different temperatures and evaluated using principal component analysis (PCA) and linear discriminant analysis (LDA), which revealed that all analytes can be distinguished and classified with more than 97% accuracy. To the best of our knowledge, this report is the first on an FBAR multiparameter VSA based on temperature modulation, and the proposed novel VSA shows great potential as a compact and promising e-nose system integrated in commercial electronic products.

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... 17 Among these methods, resonator sensors are most competitive in terms of sensitivity and resolution owing to the high quality factor of electromechanical resonators. 16 Film bulk acoustic wave resonators (FBARs), as piezoelectric transducers operating in the gigahertz regime, have been exploited for VOC detection based on the mass loading effect [18][19][20][21][22][23][24][25] and chemical reaction. 26 These sensors feature high sensitivity, miniature size, and low power consumption. ...
... [22][23][24] A single FBAR can also function as a virtual sensor array with temperature modulation to detect and discriminate VOCs. 25 The surfaces of FBARs are typically functionalized with polymers, 18 supramolecular monolayers, 25 or self-assembled monolayers 23,24 to realize selectivity and improved adsorption. Surface functionalization of the sensors plays a key role in recognition, sensitivity, selectivity, stability, and reversibility. ...
... FBAR arrays have also been used as electronic noses to achieve discrimination of VOCs. [22][23][24] A single FBAR can also function as a virtual sensor array with temperature modulation to detect and discriminate VOCs. 25 The surfaces of FBARs are typically functionalized with polymers, 18 supramolecular monolayers, 25 or self-assembled monolayers 23,24 to realize selectivity and improved adsorption. Surface functionalization of the sensors plays a key role in recognition, sensitivity, selectivity, stability, and reversibility. ...
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Film bulk acoustic wave resonators have demonstrated great potential in the detection of volatile organic compounds owing to their high sensitivity, miniature size, low power consumption, capacity for integration, and other beneficial characteristics. However, it is necessary to functionalize the surfaces of these resonators to enhance the adsorption and discrimination of volatile organic compounds. Here, we report a convenient and reliable method for functionalizing the surfaces of film bulk acoustic wave resonators with hydrophobins via self-assembly to enable highly sensitive and polarity sensitive detection of volatile organic compounds. Experiments conducted using various concentrations of five volatile organic compounds possessing different polarities demonstrated that the hydrophobin coating enhanced the responsivity of the proposed sensor. The obtained results were in good agreement with the Brunauer–Emmett–Teller model of multilayer physisorption, which suggests that the hydrophobin coating enhanced the sensitivity by improving the monolayer adsorption capacity. Our work demonstrates that the combination of multifunctional biosurfactants and microelectromechanical devices can permit high-performance gas sensing.
... Previous work using bulk acoustic wave resonators to sense VOCs has taken advantage of many of these sensitizers [30]- [38]. Of these, only Chang et al. used self-assembled monolayers as the functionalizing material [33]. ...
... THESE RESULTS DEMONSTRATE APPROXIMATELY THE SAME RELATIVE RESPONSE AND SELECTIVITY AS WAS MEASURED USING A RESIS-TIVE APPROACH FOR THE SAME RECEPTOR IN PREVIOUS WORK [16] the previous demonstrator of the thiourea monolayer for cyclohexanone detection [9]. Similar functionalized bulk acoustic wave sensors have shown limits of detection between 500 and 4 ppm, so a limit of detection of 1.11 ppm is competitive [33], [35], [37], [38], [40]. ...
... Integration of a sensing and control device to a printed circuit board eliminates some of the frequency drifting that plagues quartz crystal microbalance based sensors [73]. Finally, the limit of detection demonstrated here (1.11 ppm) is the lowest demonstrated for cyclohexanone among comparable chemiresistor and MEMs devices [9], [19], [24], [25], [38]. In particular, Heil et al and Zeng et al used gravimetric approaches resulting in limits of detection for cyclohexanone of 5 and 40 pppm respectively so our demonstration of 1.11 ppm is a significant improvement on this previous work. ...
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Functionalized gravimetric sensors are a promising path to small, versatile, real-time vapor sensors for volatile organic compounds. Many of these compounds can be dangerous to human health, but their nonreactive nature makes them notoriously difficult to sense. Unlike bulk acoustic resonators, chemiresistive devices have been investigated extensively and many researchers have used innovative synthesis strategies to functionalize these devices. In this work, we demonstrate how modifying a particular sensitizer for use with a bulk acoustic resonator significantly improves the sensitivity of the device (5 ppm vs. 1.11 ppm). Additionally, readout circuitry is described to avoid some problems that typically plague gravimetric sensors while simplifying the overall system. These strategies create a playbook for simple, fast, and sensitive systems for sensing volatile organic compounds, while also demonstrating the lowest limit of detection for cyclohexanone outside of gas chromatography/mass spectrometery in the literature. [2020-0053].
... Detection and discrimination of volatile organic compounds (VOCs), which are classified as hazard vapors with adverse short-and long-term consequences on the environment and human health 31 , is important in the continuous monitoring of indoor air quality, which therefore requires reliable sensors. Moreover, exhaled VOCs can serve as biomarkers to assist in the non-invasive identification of various diseases. ...
... Moreover, exhaled VOCs can serve as biomarkers to assist in the non-invasive identification of various diseases. For example, acetone indicates diabetes 14,[32][33][34][35] , whereas isoprene, toluene, and acetic acid are signals of lung cancer, 31,[36][37][38] and breath testing is therefore a highly promising approach for non-invasive cancer screening 39 . VOC analysis in patient breath offers insight into the metabolic processes in the anatomy/physiology that are altered by underlying diseases 40,41 , although a detailed impression of the metabolic route leading to these molecules is still under investigation 39 . ...
... Furthermore, dual or multiple signal transductions have been exploited, e.g., by evaluating both phase and attenuation shifts of a SAW sensor [87], by determining SAW sensor frequency shifts at different temperatures [88], or by measuring the frequency and dissipation shifts of a QCM sensor at multiple harmonics [89]. When conductive films are used as sensor coatings, changes of both the acoustic wave and the electrical properties of the coating can be evaluated [90][91][92]. As both multi-sensor arrays and virtual sensor arrays turned out to be well suited for multi-analyte detection, both were combined to virtual multi-sensor arrays to further enhance the performance [93,94]. ...
... The FBARs were coated with conductive polymer films, and combinations of frequency with resistance or impedance readouts were evaluated, partly with additional modulation of the temperature. These setups allowed the differentiation between five aliphatic compounds or one aromatic and five aliphatic compounds [91,92]. A similar approach was performed when a one-port SAW resonator made of 128 • YX-LiNbO 3 was coated with a conductive material. ...
Article
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Bulk acoustic wave (BAW) and surface acoustic wave (SAW) sensor devices have successfully been used in a wide variety of gas sensing, liquid sensing, and biosensing applications. Devices include BAW sensors using thickness shear modes and SAW sensors using Rayleigh waves or horizontally polarized shear waves (HPSWs). Analyte specificity and selectivity of the sensors are determined by the sensor coatings. If a group of analytes is to be detected or if only selective coatings (i.e., coatings responding to more than one analyte) are available, the use of multi-sensor arrays is advantageous, as the evaluation of the resulting signal patterns allows qualitative and quantitative characterization of the sample. Virtual sensor arrays utilize only one sensor but combine it with enhanced signal evaluation methods or preceding sample separation, which results in similar results as obtained with multi-sensor arrays. Both array types have shown to be promising with regard to system integration and low costs. This review discusses principles and design considerations for acoustic multi-sensor and virtual sensor arrays and outlines the use of these arrays in multi-analyte detection applications, focusing mainly on developments of the past decade.
... Thin film bulk acoustic resonators (FBAR) [1][2][3][4][5] are a newer generation of products in piezoelectric acoustic wave device industry, which is vigorously replacing some applications of surface acoustic wave (SAW) resonators [6,7] and quartz crystal resonators [8] due to its higher resonance frequency and smaller size. FBAR have the typical layered structure, that is a piezoelectric thin film is sandwiched by metal electrodes on the Bragg reflection layers and the substrate [9][10][11]. ...
... where ρ (1) is the density of a piezoelectric thin film. A comma followed by two indexes denotes second-order partial differentiation with respect to the coordinate associated with the indexes. ...
... Complementing somewhat the virtual screening of receptor materials, Speller et al. devised a hardware virtual sensor array whose virtual sensors were the overtone responses of single Q-TSMR GGSs [236,237]. A virtual sensor array for VOCs was obtained by Zeng et al., modulating the temperature of a film bulk acoustic wave (FBAW) transducer covered with self-assembled organic films [238]. The exposure events to the same analyte at different partial pressures appeared as straight lines in the first two principal components (PC). ...
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Within the framework outlined in the first part of the review, the second part addresses attempts to increase receptor material performance through the use of sensor systems and chemometric methods, in conjunction with receptor preparation methods and sensor-specific tasks. Conclusions are then drawn, and development perspectives for gravimetric sensors are discussed.
... Zeng et al. performed PCA on the pattern data of a multiparameter virtual sensor array (VSA) for the discrimination of six VOCs. They found that two principal components could account for more than 97% of the accuracy [36]. PCA reduces redundancy within the sensor sensitivities for each class and projects the sensitivity data orthogonally to several unrelated dimensions to identify the maximum variable component that can be used to classify groups of odorants. ...
Article
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Artificial olfactory sensors that recognize patterns transmitted by olfactory receptors are emerging as a technology for monitoring volatile organic compounds. Advances in statistical processing methods and data processing technology have made it possible to classify patterns in sensor arrays. Moreover, biomimetic olfactory recognition sensors in the form of pattern recognition have been developed. Deep learning and artificial intelligence technologies have enabled the classification of pattern data from more sensor arrays, and improved artificial olfactory sensor technology is being developed with the introduction of artificial neural networks. An example of an artificial olfactory sensor is the electronic nose. It is an array of various types of sensors, such as metal oxides, electrochemical sensors, surface acoustic waves, quartz crystal microbalances, organic dyes, colorimetric sensors, conductive polymers, and mass spectrometers. It can be tailored depending on the operating environment and the performance requirements of the artificial olfactory sensor. This review compiles artificial olfactory sensor technology based on olfactory mechanisms. We introduce the mechanisms of artificial olfactory sensors and examples used in food quality and stability assessment, environmental monitoring, and diagnostics. Although current artificial olfactory sensor technology has several limitations and there is limited commercialization owing to reliability and standardization issues, there is considerable potential for developing this technology. Artificial olfactory sensors are expected to be widely used in advanced pattern recognition and learning technologies, along with advanced sensor technology in the future.
... Guang Zeng et al. fabricated a multiparameter virtual sensor array (VSA) using a temperaturecompensated FBAR with 20-bilayer self-assembled PSS/PDDA thin films to improve Fractal Fract. 2022, 6, 491 2 of 11 molecule absorption efficiency [24]. The authors used a DC heater for temperature control and VOC discrimination. ...
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This paper presents the FEM modeling and simulation of a thin-film bulk acoustic resonator (FBAR) for a tetrachloroethene (PCE) gas-sensing application. A zinc oxide layer is used as a piezoelectric material; an aluminum layer is used as the electrode material in the structure of the FBAR. Polyisobutylene (PIB) is used as the sensitive layer for PCE gas detection. The study was carried out in commercially available FEM-based COMSOL software. The proposed structure was exposed to six different organic gases with concentrations ranging from 0 to 1000 ppm. The structure showed high selectivity for PCE gas. Incorporating the 3rd-order Hilbert fractal geometry in the top electrode of the FBAR increased the sensitivity of the sensor which showed high selectivity for PCE gas detection. A sensitivity enhancement of 66% was obtained using fractal geometry on the top electrode of the FBAR without alteration in size or cost. In addition, a reduction in the cross-sensitivity was achieved. Further, the PIB layer thickness and active area of the FBAR were optimized to obtain high sensitivity. The equivalent circuit was also analyzed to understand the behavior of the sensing effect and mechanism.
... FBAR works at a frequency much higher than any other gravimetric sensor hence its use as an electronic nose gives much higher sensitivity. Chang [40], Lu [41], Sabani [42] and Zeng [43]. designed a FBAR sensor array using different sensitizers for detection of VOCs. ...
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Research in the area of breath biomarkers for non-invasive diagnosis continues to grow with the developments in Electronic Nose (E-Nose) sensing techniques. Sensors are embedded in E-Nose to detect different biomarkers present breath, tissue, urine or blood. These biomarkers are used in preliminary diagnosis for fatal diseases. E-nose mechanism can be related with that of olfactory system of humans. Gravimetric sensors which sense change in mass are predominantly used in E-Nose application. This review paper provides a detailed overview of gravimetric sensors, their principle of operation, fabrication methodology, important technical parameters, and their application in E-Nose for breath bio markers detection. Four types of gravimetric sensors are covered in this review paper, 1) Quartz Crystal Microbalance (QCM) sensor 2) Surface Acoustic Wave (SAW) sensor 3) Thin-Film Bulk Acoustic Resonator (FBAR) 4) Microcantilever. The summary of sensitizers and data processing algorithms which is important for the development of gravimetric E-Nose systems is also presented in this paper.
... With the rapid development of society, deteriorating environmental problems and personal healthcare have been widely concerned. Therefore, effective detection of gases, including volatiles, toxic gases, moisture, and explosives, becomes more and more important in human daily life health and future production [1][2][3][4][5][6][7][8][9][10]. Specifically, in addition to the moisture, there are more than 3000 kinds of volatiles in the samples from human exhaled breath and skin headspace, which provide abundant information about metabolic disorders or dysfunctions of the human body [11][12][13]. ...
Article
With the progress of intelligent and digital healthcare, wearable sensors are attracting considerable attention due to their portable and real-time monitoring capabilities. Among them, wearable gas sensors, which can detect both gas markers from the human body and hazardous gas from the environment, are particularly gaining tremendous interest. To ensure the gas sensors can be worn and carried easily, most of them were fabricated on flexible substrates. However, some traditional fabrication techniques of gas sensors such as lithography and chemical vapor deposited, are incompatible with most flexible substrates due to the flexible substrates cannot endure the harsh fabricated conditions, for instance, high temperature. Therefore, fabrication techniques for wearable gas sensors are extremely limited, thus a summary of which is necessary. Here, recent advances in the fabrication techniques of wearable gas sensors are presented. Fabrication techniques included coating techniques, printing techniques, spinning techniques, and transferring techniques are discussed in detail, respectively.
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The field of chemical (gas) sensing has witnessed an unprecedented increase in device sensitivity with single molecule detection now becoming a reality. In contrast to this, the ability to distinguish or discriminate between gas species, has lagged behind. This is problematic and results in a high rate of false alarms. Here, we demonstrate a short period sinusoidal thermal modulation strategy to quantitatively and rapidly identify two industrially relevant gases (hydrogen sulfide (H2S) and sulfur dioxide (SO2)) by using a single semiconducting metal oxide sensor device. By applying sinusoidal heating voltages with a fixed short period, we were able to simultaneously obtain distinct patterns of dynamic responses. These characteristic patterns were adopted to build and validate a gas recognition library. Our approach does not rely on large-scale sensor arrays and complex algorithms and is amenable to real-time and low-power gas monitoring.
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Gravimetric resonators based on Micro/Nanoelectromechanical System (M/NEMS) are potential candidates in developing smaller, less expensive, and higher performance gas sensors. Metal organic frameworks (MOFs), with high surface areas, recently come into focus as advanced nano-porous sensitive materials in micro gravimetric gas sensors. The surface of MOFs on those sensors is critical in offering water stability and varying absorption behaviors. However, the influences of surface on sensing performance are less explored and the strategy to tune surface properties of MOFs mounted on gravimetric resonators is still rare. In this paper, a straightforward strategy to engineer surface properties of MOFs, specifically Cu3(benzenetricarboxylate)2 (known as HKUST-1), is reported and the surface hydrophilicity/hydrophobicity of HKUST-1 is tuned by chemical vapor deposition combined with monolayer self-assembly. It is found out that the hybrid inorganic and organic surface engineering strategy not only preserves the absorption capacity of inner MOFs but also significantly enhances sensor stability toward water.
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3D porous flower-like ZnO microstructures loaded by large-size Ag were successfully synthesized via a simple two-stage method. XRD and XPS results proved that the synthesized Ag/ZnO was a pure phase. SEM and TEM results showed that the Ag nanoparticles with large size (about 400 nm) were successfully loaded on the porous flower-like ZnO. The sensitivity of Ag/ZnO was 268 to 200 ppm ethanol at 300 °C, which was 6 times higher than that of pure ZnO. In addition, the sensor of Ag/ZnO exhibited a faster response/recovery behavior and a lower detection limit. The enhanced gas sensing performance of Ag/ZnO has been explained from three aspects: the “spillover effect” of Ag, the formation of metal-semiconductor heterojunction and the role of “electronic sensitization”.
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Here we present a critical review related to the important acoustic device technologies being used for the gas sensing applications. Acoustic devices find wide applications in chemical and biological sensing due to miniaturized size, high sensitivity, integration with on-field electronics, ruggedness and wireless sensing ability. An overview on the acoustic devices such as quartz crystal microbalance (QCM), Film bulk acoustic wave resonators (FBAR), and surface acoustic wave resonators (SAW) is discussed with their working principle, selection of piezoelectric, electrode material for fabrication, resonance frequencies, operation of the respective acoustic device-based gas sensors, temperature dependency and sensing layers for different gases. Recent advancements made in acoustic devices based on gas sensing technology, their structures and working mechanism along with their fabrication method, as well as the recent advances made in the design are reviewed and discussed.
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Two-dimensional transition metal carbides/nitrides, known as MXenes, have recently received significant attention for gas sensing applications. However, MXenes have strong adsorption to many types of volatile organic compounds (VOCs), and therefore gas sensors based on MXenes generally have low selectivity and poor performance in mixtures of VOCs due to cross-sensitivity issues. Herein, we developed a Ti3C2Tx-based virtual sensor array (VSA) which allows both highly accurate detection and identification of different VOCs, as well as concentration prediction of the target VOC in variable backgrounds. The VSA’s responses from the broadband impedance spectra create a unique fingerprint of each VOC without a need for changing temperatures. Based on the methodologies of principal component analysis and linear discrimination analysis, we demonstrate highly accurate identifications for different types of VOCs and mixtures using this MXene based VSA. Furthermore, we demonstrate an accuracy of 93.2% for the prediction of ethanol concentrations in the presence of different concentrations of water and methanol. The high level of identification and concentration prediction shows a great potential of MXene based VSA for detection of VOCs of interest in the presence of known and unknown interferences.
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This article proposes a novel structured aluminum nitrate (AlN) thin film based piezoelectric micromachined ultrasonic transducer (PMUT) with superior ultrasonic performances that can directly be applied for pulse-echo imaging. The bottom electrode of the PMUT is thickened and serves both as the electrical layer and supporting layer. Large numbers of elements are parallelly connected to form square arrays. This method can not only improve the acoustic output but also reduce the total impedance. The ultrasonic transmitting, receiving behaviors of our developed 6.37 MHz (in air) PMUT array containing vibration elements of horizontal x vertical $= 20 \times 20$ are investigated. It can generate superior acoustic output with a normalized value of 1.71 kPa $\cdot \text{V}^{\mathbf {-1}}\,\,\cdot$ mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−2</sup> at 3.6 mm away in deionized water media. Thanks to the lager acoustic output and reduced electrical impedance, ultrasonic pulse-echo imaging with our developed PMUT array is realized only with the assistance of a switch to separate the ultrasound transmission and reception process. We have mechanically scanned a mark in steel plate and generate a B-mode image with great accuracy using the recorded pulse-echo signals. These demonstrate the superior acoustic behavior of our developed PMUT array and open an avenue to the development of portable ultrasonic imaging devices.
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Herein, we present switching-peptides for a one-step immunoassay, without the need for additional antibody treatment or washing steps to detect antigen–antibody interactions. Fluorescently labeled switching-peptides were dissociated from the immobilized antibody soon after the antigens were bound to the binding pockets. In this study, four different parts of the antibody (IgG) frame regions were chemically synthesized, and these peptides were bound to immobilized antibodies as switching-peptides. We presented the design principle of switching-peptides and used Pymol software, based on the changes in thermodynamic parameters, to study the interaction between antibodies and switching-peptides. The binding properties of switching-peptides were analyzed based on Förster resonance energy transfer between switching-peptides as well as between switching-peptides and antibodies (IgGs) isolated from different animals. The binding constants of the four switching-peptides to antibodies were estimated to be in the range of 1.48–3.29 μM. Finally, the feasibility of using switching-peptides for the quantitative one-step immunoassay was demonstrated by human hepatitis B surface antigen (hHBsAg) detection and statistical comparison of the assay results with those of conventional ELISA. The limit of detection for HBsAg was determined to be 56 ng/mL, and the dynamic range was estimated to be 136 ng/mL–33 μg/mL. These results demonstrate the feasibility of the one-step immunoassay for HBsAg.
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In this paper, we have modeled and analyzed affinities and kinetics of volatile organic compounds (VOCs) adsorption (and desorption) on various surface chemical groups using multiple self-assembled monolayers (SAMs) functionalized film bulk acoustic resonator (FBAR) array. The high-frequency and micro-scale resonator provides improved sensitivity in the detections of VOCs at trace levels. With the study of affinities and kinetics, three concentration-independent intrinsic parameters (monolayer adsorption capacity, adsorption energy constant and desorption rate) of gas-surface interactions are obtained to contribute to a multi-parameter fingerprint library of VOC analytes. Effects of functional group's properties on gas-surface interactions are also discussed. The proposed sensor array with concentration-independent fingerprint library shows potential as a portable electronic nose (e-nose) system for VOCs discrimination and gas-sensitive materials selections.
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Combining vapour sensors into arrays is an accepted compromise to mitigate poor selectivity of conventional sensors. Here we show individual nanofabricated sensors that not only selectively detect separate vapours in pristine conditions but also quantify these vapours in mixtures, and when blended with a variable moisture background. Our sensor design is inspired by the iridescent nanostructure and gradient surface chemistry of Morpho butterflies and involves physical and chemical design criteria. The physical design involves optical interference and diffraction on the fabricated periodic nanostructures and uses optical loss in the nanostructure to enhance the spectral diversity of reflectance. The chemical design uses spatially controlled nanostructure functionalization. Thus, while quantitation of analytes in the presence of variable backgrounds is challenging for most sensor arrays, we achieve this goal using individual multivariable sensors. These colorimetric sensors can be tuned for numerous vapour sensing scenarios in confined areas or as individual nodes for distributed monitoring.
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Improvements in the responses of semiconductor gas sensors and reductions in their detection limits toward volatile organic compounds (VOCs) are required in order to facilitate the simple detection of diseases, such as cancer, through human-breath analysis. In this study, we introduce a heater-switching, pulse-driven, micro gas sensor composed of a microheater and a sensor electrode fabricated with Pd-SnO2-clustered nanoparticles as the sensing material. The sensor was repeatedly heated and allowed to cool by the application of voltage to the microheater; the VOC gases penetrate into the interior of the sensing layer during its unheated state. Consequently, the utility factor of the pulse-driven sensor was greater than that of a conventional, continuously heated sensor. As a result, the response of the sensor to toluene was enhanced; indeed, the sensor responded to toluene at levels of 1 ppb. In addition, according to the relationship between its response and concentration toluene, the pulse-driven sensor in this report can detect toluene at concentrations of 200 ppt and even lower. Therefore, the combination of a pulse-driven microheater and a suitable material designed to detect toluene resulted in improved sensor response, and facilitated ppt-level toluene detection. This sensor may play a key role in the development of medical diagnoses based on human breath.
Article
This paper reported a high-performance e-nose type chemiresistive gas sensor composed of graphene oxide (GO) doped poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) nanowires. Large scale and well-defined sub-100 nm nanowires were prepared using nanoscale soft lithography in a highly efficient and facile way, facilitating subsequent device integration. The responses of the nanowire sensors to volatile organic compounds (VOCs) can be tuned by the different polymer components, which are utilized to constitute unique identification codes for ethanol, n-hexane, acetone and p-xylene and realize the discrimination of different VOCs. Besides, the score plot and classification matrix obtained respectively from the principal component analysis (PCA) and linear discriminant analysis (LDA) provide sufficient information to differentiate different VOCs.
Article
This paper describes the detection of volatile organic compounds (VOCs) using an e-nose system based on a virtual sensor array (VSA). The VSA was realized by seven different resonant modes of a single piezotransduced silicon bulk acoustic wave resonator (PSBAR) which can greatly reduce the complexity of a conventional e-nose system. The PSBAR was designed and fabricated using standard CMOS compatible process. The resonant modes of the PSBAR and its capability of VOCs discrimination were theoretically explored through finite element analysis. The discrimination effect was enhanced by the non-uniform adsorption of gas molecules on the top, side and bottom regions of the resonator. Score plots and radar fingerprints obtained respectively from principal component analysis (PCA) and fitted coefficient of adsorption isotherms for each VOC compose sufficient information to successfully discriminate different VOCs. The proposed novel VSA shows great potential as a compact and promising e-nose system.
Article
Herein, a simplistic quartz crystal microbalance (QCM) approach for discrimination of petroleum based fuels is presented. In this regard, a quartz crystal microbalance (QCM) virtual multisensor array (V-MSA) was employed to discriminate between different petroleum based fuels and to detect gasoline adulteration with high accuracy. First, an ionic liquid based V-MSA was used to discriminate between four fuel types (petroleum ether, gasoline, kerosene, and diesel). Subsequently, the system was used to successfully discriminate between three gasoline grades as a precursor for studies of gasoline adulteration. Finally, the system was used to detect and determine the nature of several gasoline adulterants at different v/v ratios (1%, 10%, 20% and 40%). Excellent accuracy (100%) was achieved for each study extolling the potential of this approach. This report represents the first example of a QCM sensor array utilized for detection of gasoline adulteration.
Article
This paper describes the detection of volatile organic compounds (VOCs) using an e-nose type integrated microfabricated sensor array, in which each resonator is coated with different supramolecular monolayers: p-tert-butyl calix[8]arene (Calix[8]arene), 2,3,7,8,12,13,17,18-octaethyl-21H,23H-porphine (Porphyrin), beta-cyclodextrin (β-CD) and cucurbit[8]uril (CB[8]). Supramolecular monolayers fabricated by Langmuir-Blodgett techniques work as specific sensing interface for different VOCs recognition which increase the sensor selectivity. Microfabricated ultra-high working frequency transducers (4.4 GHz) enable their high sensitivity towards monolayer sensing which facilitate the analyses of VOCs adsorption isotherms and kinetics. Two affinity constants (K1, K2) are obtained for each VOC, which indicate the gas molecule adsorption happen inside and outside of the supramolecular cavities. Additional kinetic information (adsorption/desorption rate constants (ka, kd)) are obtained, thus enrich the sensing matrix (△f, K1, K2, ka, kd) which can be used as fingerprint patterns for highly specific detection and discrimination of VOCs.
Article
Herein, we demonstrate an alternative strategy for creating QCM-based sensor arrays by use of a single sensor to provide multiple responses per analyte. The sensor, which simulates a virtual sensor array (VSA), was developed by depositing a thin film of ionic liquid, either 1-octyl-3-methylimidazolium bromide ([OMIm][Br]) or 1-octyl-3-methylimidazolium thiocyanate ([OMIm][SCN]), onto the surface of a QCM-D transducer. The sensor was exposed to 18 different organic vapors (alcohols, hydrocarbons, chlorohydrocarbons, nitriles) belonging to the same or different homologous series. The resulting frequency shifts (Δf) were measured at multiple harmonics and evaluated using principal component analysis (PCA) and discriminant analysis (DA) which revealed that analytes can be classified with extremely high accuracy. In almost all cases, the accuracy for identification of a member of the same class, i.e. intraclass discrimination, was 100% as determined by use of quadratic discriminant analysis (QDA). Impressively, some VSAs allowed classification of all 18 analytes tested with nearly 100% accuracy. Such results underscore the importance of utilizing lesser exploited properties which influence signal transduction. Overall, these results demonstrate excellent potential of the virtual sensor array strategy for detection and discrimination of vapor phase analytes utilizing the QCM. To the best of our knowledge, this is the first report on QCM VSAs, as well as an experimental sensor array, that is based primarily on viscoelasticity, film thickness, and harmonics.
Article
The scope of the applications of breath sensors is abundant in disease diagnosis. Lung cancer diagnosis is a well-fitting health-related application of this technology, which is of utmost importance in the health sector, because lung cancer has the highest death rate among all cancer types, and it brings a high yearly global burden. The aim of this review is first to provide a rational basis for the development of breath sensors for lung cancer diagnostics from a historical perspective, which will facilitate the transfer of the idea into the rapidly evolving sensors field. Following examples with diagnostic applications include colorimetric, composite, carbon nanotube, gold nanoparticle-based, and surface acoustic wave sensor arrays. These select sensor applications are widened by the state-of-the-art developments in the sensors field. Coping with sampling sourced artifacts and cancer staging are among the debated topics, along with the other concerns like proteomics approaches and biomimetic media utilization, feature selection for data classification, and commercialization.
Article
The use of molecularly modified Si nanowire field effect transistors (SiNW FETs) for selective detection in liquid phase has been successfully demonstrated. In contrast, selective detection of chemical species in the gas phase has been rather limited. In this paper, we show that the application of artificial intelligence on deliberately controlled SiNW FET device parameters can provide high selectivity towards specific volatile organic compounds (VOCs). The obtained selectivity allows identifying VOCs in both single-component and multi-component environments as well as estimating the constituent VOC concentrations. The effect of the structural properties (functional group and/or chain length) of the molecular modifications on the accuracy of VOC detection is presented and discussed. The reported results have the potential to serve as a launching pad for the use of SiNW FET sensors in real-world counteracting conditions and/or applications.
Article
A micromachined metal oxide gas sensor operated with temperature modulation allows discrimination between air, H2 and CO in less than 1s. Furthermore, the actual humidity level and gas concentration can be estimated. We tested gas concentrations of 3–12ppm H2 and 12–100ppm CO at five relative humidity levels between 30 and 70%. While H2 can be identified for all concentrations, certain identification of CO requires concentrations above 20ppm and also determination of the relative humidity level from the sensor data.
Article
Molecularly modified silicon nanowire field effect transistors (SiNW FETs) are starting to appear as promising devices for sensing various volatile organic compounds (VOCs). Understanding the connection between the molecular layer structure attached to the SiNWs and VOCs is essential for the design of high performance sensors. Here, we explore the chain length influence of molecular layers on the sensing performance to polar and nonpolar VOCs. SiNW FETs were functionalized with molecular layers that have similar end (methyl) group and amide bridge bond, but differ in their alkyl chain lengths. The resulting devices were then exposed to polar and nonpolar VOCs in various conditions. Our results showed that the sensing response to changing the threshold voltage (ΔVth) and changing the relative hole mobility (Δµh/µh-a) have a proportional relationship to the VOC concentration. On exposure to a specific VOC concentration, ΔVth response increased with the chain length of the molecular modification. In contrast, Δµh/µh-a did not exhibit any obvious reliance on the chain length of the molecular layer. Analysis of the responses with an electrostatic-based model suggests that the sensor response in ΔVth is dependent on the VOC concentration, VOC vapor pressure, VOC-molecular layer binding energy, and VOC adsorption induced dipole moment changes of molecular layer. Understanding the relationship between the silicon nanowires' molecular layer structure and the VOCs is essential for the design of high performance sensors.
Article
Multilayer films of organic compounds on solid surfaces have been studied for more than 60 years because they allow fabrication of multicomposite molecular assemblies of tailored architecture. However, both the Langmuir-Blodgett technique and chemisorption from solution can be used only with certain classes of molecules. An alternative approach—fabrication of multilayers by consecutive adsorption of polyanions and polycations—is far more general and has been extended to other materials such as proteins or colloids. Because polymers are typically flexible molecules, the resulting superlattice architectures are somewhat fuzzy structures, but the absence of crystallinity in these films is expected to be beneficial for many potential applications.
Article
Tropical Morpho butterflies are famous for their brilliant iridescent colours, which arise from ordered arrays of scales on their wings. Here we show that the iridescent scales of the Morpho sulkowskyi butterfly give a different optical response to different individual vapours, and that this optical response dramatically outperforms that of existing nano-engineered photonic sensors. The reflectance spectra of the scales provide information about the nature and concentration of the vapours, allowing us to identify a range of closely related vapours–water, methanol, ethanol and isomers of dichloroethylene when they are analysed individually. By comparing the reflectance as a function of time for different vapours, we deduce that wing regions with scale structures of differing spatial periodicity give contributions to the overall spectral response at different wavelengths. Our optical model explains the effect of different components of the wing scales on the vapour response, and could steer the design of new man-made optical gas sensors.
Article
An emerging approach for diagnosing LC relies on volatile organic compounds (VOC), viz. organic compounds with relatively high vapor pressure or volatility, that can be detected in the headspace of cancer cells or blood samples, and/or in the exhaled breath. Identification, separation, and integration of the peaks in measured chromatograms for each sample. This might involve the use of Gaussian and non-Gaussian peak-fitting software, algorithms for the numerical calculation of the peak area, and algorithms for background compensation. Using internal standards might improve the reliability of the results, allowing a compensation of spectral shifts prior to the peak integration. The available statistical tests differ in the assumptions concerning the tested groups or populations: Gaussian and non-Gaussian populations, paired and unpaired groups, comparison between two or more groups.
Article
Carbon nanotube field-effect transistors (NTFETs) coated with poly(ethyleneimine) (PEI) and starch polymers exhibit electrical conductance changes upon exposure to CO2 gas in air at ambient temperature (see Figure). This observation has furnished nanoelectronic CO2 sensors. Their small size and low power consumption has enormous potential in wireless sensing for industrial and medical CO2 sensor units.
Article
In this study, responses of a sensor array were employed to establish a quality index model able to describe the different picking date of peaches. The principal component regression (PCR) and partial least-squares regressions (PLS) model represent very good ability in describing the quality indices of the selected three sets of peaches in calibration and prediction. The results showed that the PLS model represents a good ability in predicting quality index, with high correlation coefficients (R = 0.86 for penetrating force [CF]; R = 0.83 for sugar content [SC]; R = 0.83 for pH) and relatively low standard error of prediction (SEP; 8.77N, 0.299 °Brix, and 0.2 for CF, SC, and pH, respectively). The PCR model had high correlation coefficients (R = 0.84, 0.82, 0.78 for CF, SC, and pH, respectively) between predicted and measured values and a relatively low SEP (7.33N, 0.44 °Brix, 0.21 for CF, SC, and pH, respectively) for prediction. These results prove that the electronic noses have the potential to assess fruit quality indices. KeywordsPeach–Quality–Principal component regression (PCR)–Partial least-squares regressions (PLS)–Electronic nose
Article
The human nose is still the primary ‘instrument’ used to assess the smell or flavour of various industrial products today, despite considerable and sustained attempts to develop new electronic instrumentation capable of mimicking its remarkable ability. In this paper we review the research effort that has been carried out over the past 25 years or so to create an electronic nose. In doing so, we first provide a definition for the term electronic nose, and then discuss some of the technologies that have been explored in what is essentially an intelligent chemical array sensor system. Finally, we summarize the applications of electronic noses to date and suggest where future applications may lie.
Article
A novel gas sensor composed of electrospun nanofibrous membranes and quartz crystal microbalance (QCM) was successfully fabricated. The electrospun nanofibers with diameter of 100–400 nm can be deposited on the surface of QCM by electrospinning the homogenous blend solutions of cross-linkable poly(acrylic acid) (PAA) and poly(vinyl alcohol) (PVA). A series of nanofibrous membranes with various weight percentage of PAA to PVA were fabricated and characterized regarding their morphology and sensitivity to NH3. Sensing experiments were examined by measuring the resonance frequency shifts of QCM which due to the additional mass loading. The results showed that the sensing properties were mainly affected by the content of PAA component in nanofibrous membranes, concentration of NH3, and relative humidity. Additionally, the sensitivity of nanofibrous membranes coated (NMC) QCM sensor was much higher than that of continuous films coated QCM sensor.
Article
Silicon nanowire field-effect transistors (Si NW FETs) have been used as powerful sensors for chemical and biological species. The detection of polar species has been attributed to variations in the electric field at the conduction channel due to molecular gating with polar molecules. However, the detection of nonpolar analytes with Si NW FETs has not been well understood to date. In this paper, we experimentally study the detection of nonpolar species and model the detection process based on changes in the carrier mobility, voltage threshold, off-current, off-voltage, and subthreshold swing of the Si NW FET. We attribute the detection of the nonpolar species to molecular gating, due to two indirect effects: (i) a change in the dielectric medium close to the Si NW surface and (ii) a change in the charged surface states at the functionality of the Si NW surface. The contribution of these two effects to the overall measured sensing signal is determined and discussed. The results provide a launching pad for real-world sensing applications, such as environmental monitoring, homeland security, food quality control, and medicine.
Article
An eight-sensor array coupling a chemoselective room-temperature ionic liquid (RTIL) with quartz crystal microbalance (QCM) transduction is presented in this work in order to demonstrate the power of this approach in differentiating closely related analytes in sensory devices. The underlying mechanism behind the specific sensory response was explored by (i) studying mass loading and viscoelasticity effects of the sensing layers, predominantly through variation in damping impedance, the combination of which determines the sensitivity; (ii) creation of a solvation model based on Abraham's solvation descriptors which reveals the fact that polarizability and lipophilicity are the main factors influencing the dissolution of gas analytes into the RTILs; and (iii) determination of enthalpy and entropy values for the studied interactions and comparison via a simulation model, which is also effective for pattern discrimination, in order to establish a foundation for the analytical scientist as well as inspiration for synthetic pathways and innovative research into next-generation sensory approaches. The reported sensors displayed an excellent sensitivity with detection limit of <0.2%, fast response and recovery, and a workable temperature range of 27-55 °C and even higher. Linear discriminant analysis (LDA) showed a discrimination accuracy of 86-92% for nitromethane and 1-ethyl-2-nitrobenzene, 71% for different mixtures of nitromethane, and 100% for these analytes when thermodynamic parameters were used as input data. We envisage applications to detecting other nitroaromatics and security-related gas targets, and high-temperature or real-time situations where manual access is restricted, opening up new horizons in chemical sensing.
Article
By functionalizing the surfaces of ZnO nanobelts (NBs) with a thin self-assembled molecular layer, the electrical and optoelectronic performances of a single NB-based device are drastically improved. For a single NB-based device, due to energy band tuning and surface modification, the conductance was enhanced by 6 orders of magnitude upon functionalization; a coating molecule layer has changed a Schottky contact into an Ohmic contact without sophisticated deposition of multilayered metals. A functionalized NB showed negative differential resistance and exhibited huge improved photoconductivity and gas sensing response. The functionalized molecular layer also greatly reduced the etching rate of the ZnO NBs by buffer solution, largely extending their life time for biomedical applications. Our study demonstrates a new approach for improving the physical properties of oxide NBs and nanowires for device applications.
Article
Olfaction exhibits both high sensitivity for odours and high discrimination between them. We suggest that to make fine discriminations between complex odorant mixtures containing varying ratios of odorants without the necessity for highly specialized peripheral receptors, the olfactory systems makes use of feature detection using broadly tuned receptor cells organized in a convergent neurone pathway. As a test of this hypothesis we have constructed an electronic nose using semiconductor transducers and incorporating design features suggested by our proposal. We report here that this device can reproducibly discriminate between a wide variety of odours, and its properties show that discrimination in an olfactory system could be achieved without the use of highly specific receptors.
Article
A QCM device employing ionic liquids as the sensing materials for organic vapors has been developed and evaluated. The sensing mechanism is based on the fact that the viscosity of the ionic liquid membrane decreases rapidly due to solubilization of analytes in the ionic liquids. This change in viscosity, which varies with the chemical species of the vapors and the types of ionic liquids, results in a frequency shift of the corresponding quartz crystal. The QCM sensor demonstrated a rapid response (average response time of less than 2 s) to organic vapors with an excellent reversibility because of the fast diffusion of analytes in ionic liquids. Furthermore, the ionic liquids, with zero vapor pressure and stable chemical properties, ensure a long-term shelf life for the sensor.
Article
The sensing ability of individual SnO(2) nanowires and nanobelts configured as gas sensors was measured before and after functionalization with Pd catalyst particles. In situ deposition of Pd in the same reaction chamber in which the sensing measurements were carried out ensured that the observed modification in behavior was due to the Pd functionalization rather than the variation in properties from one nanowire to another. Changes in the conductance in the early stages of metal deposition (i.e., before metal percolation) indicated that the Pd nanoparticles on the nanowire surface created Schottky barrier-type junctions resulting in the formation of electron depletion regions within the nanowire, constricting the effective conduction channel and reducing the conductance. Pd-functionalized nanostructures exhibited a dramatic improvement in sensitivity toward oxygen and hydrogen due to the enhanced catalytic dissociation of the molecular adsorbate on the Pd nanoparticle surfaces and the subsequent diffusion of the resultant atomic species to the oxide surface.
Article
The development of the electronic nose have paved the way for the classification of bacteria, to monitor air quality on the space shuttle, or to check the spoilage of foodstuff. However, the electronic nose still is unable to discriminated between flavors, perfumes, smells and as a replacement for the human nose. Although it has been used to detect some important nonodorant gases, it is not adapted to substances of daily importance in mammalian life such as the scent of other animals, foodstuff or spoilage. Due to such limitations, the electronic nose was developed to mimic the human nose. It turns out that the human nose's unequaled performance is not due to the high number of different human receptor cells, but their selectivity and their unsurpassed sensitivity for some analyte gases. As such, the success of the electronic nose will not rely on increasing the number of individual sensors and creating redundant information by adding more similar sensors, but rather on DNA, molecular, imprinted molecules or even mobilized natural receptors, which promise to increase the sensitivity and importantly selectivity. An increase in the sensitivity can be achieved by appropriate sample pretreatment and preconcentration techniques, whereas filters and separation units can be used to increase the selectivity and reduce interfering substances.
Conference Paper
Pellistors are well known for the detection of combustible gases. In this paper we present a simple preparation technique for micro pellistors based on a commercially available Si substrate, which is normally used for semiconducting gas sensitive layers. Catalytically active layers are achieved by drop deposition of very low volumes of noble metal containing solutions. Temperature cycling and intelligent signal processing are used to achieve high selectivity. Due to low thermal time constants discrimination between gasoline and diesel fumes is achieved within two seconds, allowing the development of a fuel sensor for integration in fuel nozzles which can prevent filling the car tank with the wrong fuel.
Article
To improve the selectivity of semiconductor gas sensors, temperature modulation is often used. We present a study showing the potential of this technique with information gained comparable to multisensor systems. A dynamic operating mode coupled with a low-complexity evaluation strategy allows the identification of six organic solvent vapors over a wide concentration range (2-200 ppm) with a single sensor, for example, for leak detection systems. The system features low false alarm rates; in addition, interference by other gases, such as CO or NO<sub>2</sub>, can be suppressed. For even higher identification power, switching on-line between different temperature cycles was studied, which provides better information for critical decisions.
Differential Solute Gas Response in Ionic-Liquid-Based QCM Arrays: Elucidating Design Factors Responsible for Discriminative Explosive Gas Sensing
• H Kulah
• K Suematsu
• W Harano
• T Oyama
• Y Shin
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• T Stelzner
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• S Christiansen
• H Haick
• A Lichtenstein
• E Havivi
• R Shacham
• E Hahamy
• R Leibovich
• A Pevzner
• V Krivitsky
• G Davivi
• I Presman
• R Elnathan
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Molecular Weight Sensing Properties of Ionic Liquid-Polymer Composite Films: Theory and Experiment
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• D J Hayes
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New Method for Selectivity Enhancement of SiC Field Effect Gas Sensors for Quantification of
• C Bur
• P Reimann