ARL-RP-0536 ● SEP 2015

US Army Research Laboratory

A Molecularly Imprinted Polymer (MIP)-

Coated Microbeam MEMS Sensor for Chemical 

Detection

by Ellen L Holthoff, Lily Li, Tobias Hiller, and Kimberly L Turner

A reprint from Proc. of SPIE Vol. 9455 94550W-1. 

Approved for public release; distribution unlimited.
NOTICES

Disclaimers

The findings in this report are not to be construed as an official Department of the 

Army position unless so designated by other authorized documents. 

Citation of manufacturer’s or trade names does not constitute an official 

endorsement or approval of the use thereof. 

Destroy this report when it is no longer needed. Do not return it to the originator. 
ARL-RP-0536 ● SEP 2015

US Army Research Laboratory

A Molecularly Imprinted Polymer (MIP)-

Coated Microbeam MEMS Sensor for Chemical 

Detection

by Ellen L Holthoff

Sensors and Electron Devices Directorate, ARL

Lily Li, Tobias Hiller, and Kimberly L Turner

Univ of California Santa Barbara, Department of Mechanical 

Engineering, Science Building, Room 3231 E, Santa Barbara, CA 93106

A reprint from Proc. of SPIE Vol. 9455 94550W-1. 

Approved for public release; distribution unlimited.

FOR OFFICIAL USE ONLY (delete if not FOUO)
REPORT DOCUMENTATION PAGE Form Approved

OMB No. 0704-0188

Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the 

data needed, and completing and reviewing the collection information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing the 

burden, to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. 

Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid 

OMB control number.

PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS.

1. REPORT DATE (DD-MM-YYYY)

Sep 2015

2. REPORT TYPE

Reprint

3. DATES COVERED (From - To)

4. TITLE AND SUBTITLE

A Molecularly Imprinted Polymer (MIP)-Coated Microbeam MEMS Sensor for 

Chemical Detection

5a. CONTRACT NUMBER

5b. GRANT NUMBER

5c. PROGRAM ELEMENT NUMBER

6. AUTHOR(S)

Ellen L. Holthoff (1), Lily Li (2), Tobias Hiller (2), and Kimberly L. Turner (2)

5d. PROJECT NUMBER

5e. TASK NUMBER

5f. WORK UNIT NUMBER

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)

(1) US Army Research Laboratory

ATTN: RDRL-SEE-E 

2800 Powder Mill Road, Adelphi, MD 20783

(2) University of California Santa Barbara, Department of Mechanical 

Engineering, Engineering Science Building, Room 3231 E Santa Barbara, CA 

93106, Department of Mechanical Engineering, Engineering Science Building, 

Room 3231 E, Santa Barbara, CA 93106

8. PERFORMING ORGANIZATION REPORT NUMBER

ARL-RP-0536

9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR'S ACRONYM(S)

11. SPONSOR/MONITOR'S REPORT NUMBER(S)

12. DISTRIBUTION/AVAILABILITY STATEMENT

Approved for public release; distribution unlimited.

13. SUPPLEMENTARY NOTES

A reprint from Proc. of SPIE Vol. 9455 94550W-1. 

14. ABSTRACT

Recently, microcantilever-based technology has emerged as a viable sensing platform due to its many advantages such as 

small size, high sensitivity, and low cost. However, microcantilevers lack the inherent ability to selectively identify hazardous 

chemicals (e.g., explosives, chemical warfare agents). The key to overcoming this challenge is to functionalize the top surface 

of the microcantilever with a receptor material (e.g., a polymer coating) so that selective binding between the cantilever and 

analyte of interest takes place. Molecularly imprinted polymers (MIPs) can be utilized as artificial recognition elements for 

target chemical analytes of interest. Molecular imprinting involves arranging polymerizable functional monomers around a 

template molecule followed by polymerization and template removal. The selectivity for the target analyte is based on the 

spatial orientation of the binding site and covalent or noncovalent interactions between the functional monomer and the 

analyte. In this work, thin films of sol-gel-derived xerogels molecularly imprinted for TNT and dimethyl methylphosphonate 

(DMMP), a chemical warfare agent stimulant, have demonstrated selectivity and stability in combination with a fixed-fixed 

beam microelectromechanical systems (MEMS)-based gas sensor. The sensor was characterized by parametric bifurcation 

noise-based tracking.

15. SUBJECT TERMS

Molecular imprinting, microcantilever, xerogel, chemical sensor, explosives detection

16. SECURITY CLASSIFICATION OF:

17. LIMITATION

 OF 

 ABSTRACT

UU

18. NUMBER

 OF 

 PAGES

19

19a. NAME OF RESPONSIBLE PERSON

Ellen L. Holthoff

a. REPORT

Unclassified

b. ABSTRACT

Unclassified

c. THIS PAGE

Unclassified

19b. TELEPHONE NUMBER (Include area code)

301-394-0939

Standard Form 298 (Rev. 8/98)

Prescribed by ANSI Std. Z39.18
A Molecularly Imprinted Polymer (MIP)-Coated Microbeam MEMS 

Sensor for Chemical Detection

Ellen L. Holthoff1, Lily Li2, Tobias Hiller2, and Kimberly L. Turner2 

1

U.S. Army Research Laboratory, RDRL-SEE-E, 2800 Powder Mill Road, Adelphi, MD 20783 

2

University of California Santa Barbara, Department of Mechanical Engineering, Engineering 

Science Building, Room 3231 E, Santa Barbara, CA 93106 

ABSTRACT 

Recently, microcantilever-based technology has emerged as a viable sensing platform due to its many advantages such 

as small size, high sensitivity, and low cost. However, microcantilevers lack the inherent ability to selectively identify 

hazardous chemicals (e.g., explosives, chemical warfare agents). The key to overcoming this challenge is to 

functionalize the top surface of the microcantilever with a receptor material (e.g., a polymer coating) so that selective 

binding between the cantilever and analyte of interest takes place. Molecularly imprinted polymers (MIPs) can be 

utilized as artificial recognition elements for target chemical analytes of interest. Molecular imprinting involves 

arranging polymerizable functional monomers around a template molecule followed by polymerization and template 

removal. The selectivity for the target analyte is based on the spatial orientation of the binding site and covalent or 

noncovalent interactions between the functional monomer and the analyte. In this work, thin films of sol-gel-derived 

xerogels molecularly imprinted for TNT and dimethyl methylphosphonate (DMMP), a chemical warfare agent stimulant, 

have demonstrated selectivity and stability in combination with a fixed-fixed beam microelectromechanical systems 

(MEMS)-based gas sensor. The sensor was characterized by parametric bifurcation noise-based tracking. 

 

Keywords: Molecular imprinting, microcantilever, xerogel, chemical sensor, explosives detection

1. INTRODUCTION 

Monitoring trace gases is of great importance in a wide range of applications. Rapid detection and identification of 

chemical warfare agents and energetic materials is a priority for Military and Homeland Defense applications. Detecting 

a diverse range of chemical agents requires an adaptable sensor platform capable of identifying threats before they cause 

harm. Research and development in hazardous-materials detection technology focuses on increasing speed, sensitivity, 

and selectivity, while reducing size and cost. Although the current state-of-the-art vapor detector (Joint Chemical Agent 

Detector (JCAD)) is lightweight, handheld, and easily attaches to a belt, it still provides added bulk to a soldier on foot 

patrol. Recently, microcantilever-based technology has emerged as a viable platform due to its many advantages such as 

small size, high sensitivity, and low cost.1, 2 However, microcantilevers lack the inherent ability to selectively identify 

chemicals of interest. The key to overcoming this challenge is to functionalize the top surface of the microcantilever 

with a sorbent layer (i.e., polymer) that allows for selective binding between the microbeam and analyte(s) of interest. 

Molecular imprinting involves arranging polymerizable functional monomers around a template, followed by 

polymerization and template removal.3

 This process is illustrated in Figure 1. Arrangement is generally achieved by 

noncovalent or reversible covalent interactions. In both types of molecular imprinting, once the template is removed, 

three-dimensional cavities are generated within the final materials that are complementary to the template molecule in 

size, shape, and functionality. Essentially, one creates a molecular “memory” within the imprinted polymer matrix. 

This allows preparation of polymers which are selective for the adsorption of the target molecule of interest. Other 

advantages of this technique include: robustness and stability under a wide range of chemical and physical conditions, 

and an ability to easily design recognition sites for a plethora of target chemicals (e.g., pesticides, energetic materials, 

pharmaceuticals and proteins).4, 5

Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XVI, 

edited by Augustus Way Fountain III, Proc. of SPIE Vol. 9455, 94550W · © 2015 

SPIE · CCC code: 0277-786X/15/$18 · doi: 10.1117/12.2179694

Proc. of SPIE Vol. 9455 94550W-1

Downloaded From: http://proceedings.spiedigitallibrary.org/ on 08/20/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx
Polymerizable

functional monomer

Polymerization

Formation of 

imprinted sites

Removal of

template molecule

Unoccupied 

template site

Polymer matrix Template

molecule

Assembly

Figure 1. Simplified schematic of MIP fabrication. 

In the current work, the polymer materials of interest are sol-gel-derived xerogels, which have been used as a platform 

for MIP-based sensor development.6-8 These materials are attractive because their physicochemical properties can be 

adjusted by choice of precursor(s) and the processing protocol.9

 Precursors were chosen based on potential interactions 

with the explosive 2,4,6-trinitrotoluene (TNT). These specific interactions allow for increased target recognition. For 

example, MIPs comprised of 3-aminopropyltriethoxysilane (APTES) have been shown to engage in strong noncovalent 

interactions with TNT molecules via the formation of a charge-transfer complex between the electron-deficient aromatic 

ring of nitro-aromatics and the electron-rich amino group of the precursor.10, 11 This interaction significantly improves 

polymer selectivity and affinity for TNT.5

 Similarly, hydrogen bond acidic precursors were chosen based on specific 

interactions with the chemical warfare agent (CWA) simulant dimethyl methyl phosphonate (DMMP) because they are 

strong sorbents for hydrogen bond basic vapor analytes and have been used in the sensing of basic organophosphorus 

vapors, such as those produced by DMMP.12 

A MIP alone does not meet the requirements for a sensor without some form of a transducer to convert the analyte 

interaction into a measureable signal. There is evidence in the literature of a variety of gravimetrical detection 

techniques applied to convert a MIP into a “sensor”.13-15 In recent years, low mass, high frequency and low cost 

micro/nano sensors utilizing mass loading of microcantilevers have drawn increasing attention in the area of gravimetric 

sensing1, 2, and MIPs have become an attractive thin film coating for many microelectromechanical systems (MEMS)-

based sensors.16, 17 In this work, molecularly imprinted xerogel thin films have demonstrated selectivity and stability in 

combination with a fixed-fixed beam MEMS cantilever.18, 19 Traditionally, mass sensing using MEMS resonators has 

been achieved based on the natural frequency shift due to an increase in resonator mass; however, noise has set the limit 

of detection for linear sensing.20 As an alternative to using changes in the natural frequency, nonlinear dynamics 

induced by parametric excitation have led to successful cantilever-based sensor designs.19, 21-23 Under nonlinear 

operation, the sensor is driven parametrically at twice its natural resonant frequency.24 This produces a bifurcation, 

which manifests as a sudden jump in the response amplitude. The critical location of the bifurcation mass tracking is 

recorded by repeatedly sweeping the frequency towards the critical point until a large change in amplitude occurs. The 

excitation frequency is then reset, and the process starts again.25, 26 Bifurcation mass sensing has demonstrated better 

detection sensitivity in the presence of measurement noise when compared to linear sensing in air27; however, the long 

settling time and its high dependency on sweep rate to noise ratio28, 29 make it less desirable. Much faster acquisition and 

a lower limit of detection were achieved with a noise squeezing method, where changes in phase noise were used as a 

precursor to the actual bifurcation event.30, 31 A noise-squeezing controller is implemented using a high speed 

LabVIEWTM field programmable gated array (FPGA) to keep the device operating close to the edge of instability and 

inhibiting large amplitude changes (Figure 2). As a result, close to three orders of magnitude improvement in 

acquisition rate is achieved. 

Proc. of SPIE Vol. 9455 94550W-2

Downloaded From: http://proceedings.spiedigitallibrary.org/ on 08/20/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx
A

Noise

Squeezing

control

1

Reset

R Bifurcation Tracking

Critical pt Critical

Lock in Pt

Frequency (2 w )

Figure 2. Schematic of both noise squeezing-based tracking (left) and bifurcation sweep-based tracking methods (right). The 

bifurcation sweep based tracking method tracks the bifurcation locations by repeatedly performing frequency sweeps towards a 

critical point until a large amplitude results. Then the device is relaxed to a zero stable state before the next sweep starts. In the noise 

squeezing control tracking method, the device approaches the critical point until the noise squeezes below some threshold, then

feedback control keeps the device close to the edge of instability while maintaining a small response amplitude. 

The goal of this research effort is to demonstrate that the MIP-coated microcantilever is an effective and robust chemical 

sensing scheme. The feasibility of the approach was assessed through polymer integration with fixed-fixed beam 

MEMS gas sensors using both noise-based and sweep-based bifurcation tracking, as well as the selectivity and stability 

of this sensor platform. 

2. EXPERIMENTAL 

2.1 Reagents and Materials 

Aminopropyltriethoxysilane (APTES), methyltriethoxysilane (C1-TriEOS), 3-mercaptopropyl-trimethoxysilane 

(MPTMS), tetraethoxysilane (TEOS), and hydroxymethyltriethoxysilane (HMTriEOS) were obtained from Gelest. TNT 

was purchased from Cerilliant. DMMP, ethanol, and HCl were obtained from Sigma-Aldrich. All solvents were HPLC 

grade. All chemicals were used as received unless otherwise noted. 

2.2 Device Fabrication 

The sensors are fixed-fixed beams of varied lengths and widths. The beam thickness was 2 μm. The values were chosen 

so that the natural frequencies of the beams were less than half the natural frequency of the shear piezo actuator (330 

kHz) used to drive the device. The microbeams were fabricated using a standard silicon on insulator (SOI) process [31]. 

The SOI wafer used was 2μm silicon (Si) device layer with 1 μm buried oxide and 520 μm Si handle. First, oxide was 

grown on both sides of the wafer. Silicon nitride (Si3N4) was deposited on the backside on top of silicon oxide; together 

they serve as masks to protect the backside for potassium hydroxide (KOH) etch in a later step. After front side oxide 

removal, it was then spun with photoresist and pattern was transferred. Then a deep reactive-ion etching was used to 

define the device features. Backside mask features were defined using photolithography and inductively coupled 

plasma. The front side was spun with a ProTEK® coating to protect features during backside release etch. The backside 

was opened by anisotropic KOH etch and stopped at the buried oxide. The device was then finished with removal of 

ProTEK and buried oxide layer. 

2.3 Molecularly Imprinted Xerogels 

Energetic MIP Preparation. A TNT stock solution was prepared at 9.85 x 10-3 M, in acetonitrile. Sol solutions were 

prepared by mixing C1-TriEOS (110 μL, 0.552 mmol), MPTMS (2.813 μL, 1.51 x 10-2 mmol), APTES (3.50 μL, 1.51 x 

Proc. of SPIE Vol. 9455 94550W-3

Downloaded From: http://proceedings.spiedigitallibrary.org/ on 08/20/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx
10-2 mmol), ethanol (1.25 mL, 21.4 mmol), and HCl (6.25 μL of 1M, 6.25 x 10-3 mmol). The C1-TriEOS, MPTMS, 

APTES, and HCl were added to the ethanol at room temperature and then stirred for 30 min to ensure a visually 

homogeneous sol solution. The TNT-doped sol solution was prepared by adding 150 μL of the TNT stock solution to 

the prehydrolyzed C1-TriEOS/MPTMS/APTES/HCl/ethanol sol solution. This sol solution was then vigorously mixed 

for 30 s with a touch mixer (Scientific Industries, Vortex-Genie 2). Xerogel thin films were formed by spin casting 

(4000 rpm, 2 min) a 50 μL aliquot of the final sol mixture onto a MEMS device using a spin coater (Laurell 

Technologies, model WS-400B-6NPP/LITE). The films were aged in the dark at room temperature for 2-3 days. TNT 

was extracted from the xerogel thin films with an ethanol/acetonitrile/acetic acid (v/v/v 8:2:1) solution. The xerogels 

were allowed to react with this solution at room temperature for 24 h. All xerogel thin films were subsequently rinsed 

with ethanol to remove the residual acidic solvent. 

CWA MIP Preparation. Two different sol solutions were prepared. Solution #1 was prepared by mixing TEOS (1.26 

mL, 5.64 mmol), deionized distilled (d/d) H2O (205 μL, 11.4 mmol), ethanol (0.655 mL, 11.2 mmol), and HCl (5.62 μL 

of 0.1 M, 5.62 x 10-4 mmol). The TEOS, d/d H2O, and HCl were added to the ethanol at room temperature and then 

sonicated for 1 h to ensure a visually homogeneous sol solution. The DMMP-doped sol solution was prepared by adding 

75 μL of DMMP to the prehydrolyzed TEOS/H2O/HCL/ethanol sol solution. This sol solution was then vigorously 

mixed for 30 s with a touch mixer. Solution #2 was prepared by mixing TEOS (250 μL, 1.12 mmol), HMTriEOS (250 

μL, 1.11 mmol), d/d H2O (7.5 μL, 0.416 mmol), ethanol (250 μL, 4.28 mmol), and HCl (1 μL of 0.1 M, 1 x 10-4 mmol). 

The TEOS, HMTriEOS, d/d H2O, and HCl were added to the ethanol at room temperature and then stirred for 1 h to 

ensure a visually homogeneous sol solution. The DMMP-doped sol solution was prepared by adding 25 μL of DMMP 

to the prehydrolyzed TEOS/HMTriEOS/H2O/HCL/ethanol sol solution. This sol solution was then vigorously mixed for 

30 s with a touch mixer. For solutions #1 and #2, xerogel thin films were formed by spin casting (4000 rpm, 2 min) a 50 

μL aliquot of the final sol mixture onto a MEMS device using a spin coater. The films were aged in the dark at room 

temperature for 2-3 days. DMMP was extracted from the xerogel thin films with H2O. The xerogels were allowed to 

react with H2O at room temperature for 5 h. 

2.4 Control Xerogels 

Control xerogel thin films were prepared by following the exact reaction sequences described above except TNT and 

DMMP were eliminated. 

2.5 Sample Generation 

The trace gases were generated using a calibration gas generator (VICI Metronics, model: Dynacalibrator 190). The 

energetic gas (2,4-dinitrotoluene (DNT)) source was two certified permeation tubes (KIN-TEK, model: HRT-007.50-

2068/100) that were placed in the generator oven held at a constant temperature of 100 oC. The permeation rate for both 

tubes at this temperature was 383 ng/min. Although the MIPs were developed for the detection of TNT, the structurally 

similar compound 2,4-DNT was used for the mass sensing experiments. 2,4-DNT is a degradation product of the 

unstable TNT molecule, as well as a manufacturing impurity found in the explosive.32 Therefore, the detection of 2,4-

DNT would be beneficial in recognizing the presence of TNT in the field. The CWA gas (DMMP) source was a 

certified permeation tube (VICI Metronics, model: Dynacal 107-150-7845-C100, length: 15 cm) that was placed in the 

generator oven held at a constant temperature of 100 oC. The permeation rate at this temperature was 1180 ng/min. 

Nitrogen (N2) was used as the carrier gas. The flow rates were controlled by mass flow controllers (MFC). The 

concentration of the analyte/N2 mixture in parts per billion (ppb) can be calculated based on the flow rate and oven 

temperature for a specific permeation tube. 

2.6 Sensor Operation 

The device under testing is comprised of a fixed-fixed microbeam, as shown Figure 3. The sensing experiments are 

conducted in a closed chamber at atmospheric pressure and room temperature. Figure 4 depicts the basic elements 

required for gas sensing using the microbeam. The sensor was mounted on a shear piezo, driven by a function generator 

Proc. of SPIE Vol. 9455 94550W-4

Downloaded From: http://proceedings.spiedigitallibrary.org/ on 08/20/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx
(Agilent, model: 33512B) at nearly twice the resonant frequency (to drive parametric resonance) at a fixed voltage of 32 

V. The sensor response is detected by an optical laser Doppler vibrometer (LDV) (Polytec, model: OFV 511) and the 

signal is analyzed using a lock-in amplifier (Stanford Research Systems, model: SR830 DSP). The lock-in amplifier 

provides outputs that include the “in phase” component of the signal, Vsig cosφ (X) and the “quadrature” component, Vsig 

sinφ (Y). Amplitude and phase information of the signal can be calculated from the X and Y components. Based on the 

statistics of the phase, the FPGA controller (National Instruments, model: cRIO-9014 Compact Real-Time Control 

Board) provides feedback to the function generator to perform corresponding frequency modulation to remain at the 

edge of bifurcation instability. 

Figure 3. SEM image of a silicon fixed-fixed microbeam sensor coated with a MIP. 

Proc. of SPIE Vol. 9455 94550W-5

Downloaded From: http://proceedings.spiedigitallibrary.org/ on 08/20/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx
Figure 4. Simplified diagram of the experimental setup for gas sensing. 

3. RESULTS AND DISCUSSION 

There are several key challenges to overcome in the development of a MIP-coated microbeam MEMS sensing platform 

including: (1) developing a strategy for MIP integration to enable target interaction without compromising the frequency 

operation of the device; (2) developing a MIP formulation that is stable and integrated with the MEMS sensor to allow 

for practical application in the field; and (3) ensuring that the developed MIP allows for template removal, analyte 

reintroduction, and also provides selectivity for the target analyte components. 

3.1 MIP Integration and Sensor Performance 

MIP for Explosives Detection. The integrated MIP for explosives detection has shown that it is selective to 2,4-DNT and 

has demonstrated reliable reversibility and stability.18 In this work, the gas sensing experiment was performed with the 

noise-squeezing controller at a concentration of 0.93 parts-per-billion (ppb) 2,4-DNT. Figure 5 presents the change in 

the natural frequency of the microbeam sensor over time as it is challenged with 2,4-DNT. A single response cycle 

included 15 minutes of pure N2 followed by 10 minutes of 2,4-DNT. The sensor was reset (i.e., the absorbed 2,4-DNT 

molecules released from the polymer matrix) using pure N2 (purge). It is clear from Figure 5 that the polymer coating 

does not compromise the frequency operation of the device. The response is reversible after 9 cycles. During gas 

sensing experiments, switching from 2,4-DNT to pure N2 by manually turning the corresponding valves caused the 

frequency to drop sharply before returning to an upward trend (see example circled in Figure 5). This was observed in 

both the noise-based and sweep-based bifurcation sensing strategies. This is not an artifact of the control. It is unique to 

the analyte sensing, as it is not visible in a similar experiment using water vapor (data not shown). One possible 

Lock-in Amplifier

Proc. of SPIE Vol. 9455 94550W-6

Downloaded From: http://proceedings.spiedigitallibrary.org/ on 08/20/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx
u.yo ppu LIN i

min

200

o

-200

-400

N

-600

R. -800

-1000

-1200

-1400

-1600o

1 2 3

Time (fir)

4 5 6

explanation is that the release of 2,4-DNT molecules from the polymer uses so much energy that the beam is cooled and 

its natural frequency lowered for a brief moment, until it returns to room temperature.33 

Figure 5. Natural frequency versus time plot for a typical MIP-coated microbeam sensor when it is challenged by 0.93 ppb 2,4-DNT 

and reset with N2. The response is reversible after 9 cycles. The linear frequency drift of 0.05 Hz/min was accounted for in the post 

processing. 

Further experiments were conducted at higher concentrations of 2,4-DNT. These experiments were carried out by the 

noise squeezing bifurcation sensing method (Figure 6) and the bifurcation sweep tracking method previously described19

(Figure 7) for comparison. Figures 6 and 7 present sensor response data as a function of 2,4-DNT concentration. An 

increasing concentration of the analyte was introduced after the steady state of the previous (lower) concentration of 

analyte was reached. Hence, after each concentration of 2,4-DNT was introduced, no pure N2 was used to release the 

absorbed 2,4-DNT molecules. The motivation for this test came from the observation that the coatings would not fully 

recover following an N2 purge. It was therefore necessary to understand potential saturation effects. Each 2,4-DNT 

concentration increase resulted in a larger shift of natural frequency at saturation state in reference to the initial state 

(i.e., before introduction of 2,4-DNT). Therefore, this experiment was valid in finding the absorption calibration curve 

for the sensor. 

2.03 

ppb 3.63 

ppb 5.44 

ppb 

10.88 

ppb 

18.13 

ppb 

12.80 

ppb 13.60

ppb 

1.38

ppb 

Figure 6. Data collected using the noise squeezing bifurcation tracking method. Natural frequency versus time plot for a typical MIPcoated microbeam sensor when it is challenged with increasing concentrations of 2,4-DNT. Absorbed 2,4-DNT was not completely 

purged from the sensor using pure N2 after the first cycle (i.e., 1.38 ppb 2,4-DNT), therefore the frequency did not return to the initial 

frequency. 

Proc. of SPIE Vol. 9455 94550W-7

Downloaded From: http://proceedings.spiedigitallibrary.org/ on 08/20/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx
N2

200

150

Bifurcation Sweep Method A Noise Squeezing Method A

A

5 10 15 20

Concentration (ppb)

200

0

-200

-400

-600

-800

-1000

-12000

0.5 1Time (hr)1.5 2

2.03 

ppb 

3.63 

ppb 

5.44 

ppb 

10.88 

ppb 

Figure 7. Data collected using the bifurcation sweep tracking method. Natural frequency versus time plot for a typical MIP-coated 

microbeam sensor when it is challenged with increasing concentrations of 2,4-DNT. Absorbed 2,4-DNT was not completely purged 

from the sensor using pure N2 after the first cycle (i.e., 2.03 ppb 2,4-DNT), therefore the frequency did not return to the initial 

frequency. 

The response profiles from a 2,4-DNT-responsive MIP-coated microbeam MEMS sensor to increasing concentrations of 

2,4-DNT are illustrated in Figure 8. Data from both the noise squeezing bifurcation tracking and the bifurcation sweep 

tracking methods is shown. For both methods, the frequency shift increases as the 2,4-DNT concentration increases and 

the results exhibit excellent linearity. Coefficients of determination (R2

) can be found in Figure 8. Specific limit of 

detection (LOD) values are also provided in Figure 8. It is important to note that the frequency shift shown in all figures 

in this work (for 2,4-DNT detection) corresponds to the drive frequency shift. Therefore, to relate them to the natural 

frequency shift, a multiplication factor of 0.5 is needed. The Allan deviation34 was used to quantify the frequency 

stability of the background signal (i.e, the minimum frequency that can be detected). The LOD was calculated by taking 

the minimum frequency and dividing it by the slope of the linear function. 

Figure 8. Response profiles from a 2,4-DNT-responsive MIP-coated microbeam MEMS sensor to increasing concentrations of 2,4-

DNT using both the noise squeezing method and bifurcation sweep tracking method. Note that the frequency shift in this figure 

corresponds to the drive frequency, so the actual natural frequency shift is half of what is indicated. Error bars are negligible. 

R2 = 0.9941 

LOD = 0.06 ppb 

R2 = 0.9985 

LOD = 0.0005 ppb

Proc. of SPIE Vol. 9455 94550W-8

Downloaded From: http://proceedings.spiedigitallibrary.org/ on 08/20/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx
Experimental results demonstrate that noise-squeezing control for bifurcation sensing is a better sensing strategy than the 

bifurcation sweep method previously described.19 It uses the statistics of the phase noise as a precursor to the 

bifurcation event, and the control time is less than 10 ms. The average time for a bifurcation sweep method to track a 

bifurcation event is 15 to 20 seconds, depending on sweep rate. More than three orders of magnitude improvement in 

acquisition is achieved using the noise squeezing method for bifurcation detection. The advantage of the noise 

squeezing method is evident in the frequency stability of the sensor, which is over two orders of magnitude smaller than 

that of the bifurcation sweep method. This is significant because it means two orders improvement in ultimate 

sensitivity of the sensor. Furthermore, fast data acquisition employing the noise squeezing strategy not only results in 

higher confidence on the estimation of the bifurcation locations, but also enables more information on the response 

dynamics of the MIP. As a result, the noise squeezing-based bifurcation tracking can be used for other applications in 

addition to mass sensing, for example, to characterize the absorption kinetics of the MIP to further improve surface 

coating chemistry. It should be noted that the sensor sensitivity to the absorption of 2,4-DNT is directly correlated to the 

surface coating chemistry. 

As expected, the response from a control-coated microbeam MEMS sensor when it was challenged by 2,4-DNT was 

inferior compared to the MIP-coated sensor. This data has been previously described using the bifurcation sweep 

tracking method.19

MIP for CWA Detection. The integrated MIP for CWA detection was designed based on specific hydrogen bonding 

interactions with DMMP and have been demonstrated for gas phase sensing of the organophosphorus vapors produced 

by this analyte.12 In this work, the gas sensing experiment (i.e., sensor response cycles over a period of time at a single 

DMMP concentration) was performed with the noise-squeezing controller (data not shown). The following results are 

for a MIP coating derived from sol solution #1. MIP-coated cantilevers for which the polymer coating was derived from 

sol solution #2 were not investigated due to an inability to get the cantilevers to bifurcation. 

Further experiments were conducted at higher concentrations of DMMP. These experiments were carried out by the 

noise squeezing bifurcation sensing method. Figure 9 presents sensor response data as a function of DMMP 

concentration. An increasing concentration of the analyte was introduced after the steady state of the previous (lower) 

concentration of analyte was reached. Hence, after each concentration of DMMP was introduced, no pure N2 was used 

to release the absorbed DMMP molecules. Each DMMP concentration increase resulted in a larger shift of natural 

frequency at saturation state in reference to the initial state (i.e., before introduction of DMMP). Therefore, this 

experiment was valid in finding the absorption calibration curve for the sensor. 

Proc. of SPIE Vol. 9455 94550W-9

Downloaded From: http://proceedings.spiedigitallibrary.org/ on 08/20/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx
3.80 

ppb

6.78 

ppb

10.17 

ppb

23.93

ppb

Figure 9. Data collected using the noise squeezing bifurcation tracking method. Excitation versus time plot for a typical MIP-coated 

microbeam sensor when it is challenged with increasing concentrations of DMMP. Absorbed DMMP was not completely purged 

from the sensor using pure N2 after the first cycle (i.e., 3.80 ppb DMMP), therefore the frequency did not return to the initial 

frequency. 

 

A similar set of experiments were conducted using a control-coated microbeam MEMS sensor. Figure 10 presents 

sensor response data as a function of DMMP concentration. Due to the presence of hydrogen bond acidic precursors in 

the control xerogel and the resulting strong sorbent functionality for organophosphorus vapor, it was expected that 

DMMP would react with this polymer. 

Proc. of SPIE Vol. 9455 94550W-10

Downloaded From: http://proceedings.spiedigitallibrary.org/ on 08/20/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx
3.80 

ppb

6.78 

ppb

23.93

ppb

Figure 10. Data collected using the noise squeezing bifurcation tracking method. Excitation versus time plot for a typical controlcoated microbeam sensor when it is challenged with increasing concentrations of DMMP. Absorbed DMMP was not completely 

purged from the sensor using pure N2 after the first cycle (i.e., 3.80 ppb DMMP), therefore the frequency did not return to the initial 

frequency. 

Figure 11 illustrates the microcantilever response profiles from DMMP-responsive and control xerogel coatings to 

increasing concentrations of DMMP. For the MIP-coated MEMS sensor, the frequency shift increases as the DMMP 

concentration increases. Binding properties were calculated using the Langmuir-Fruendlich (LF) isotherm, which is 

capable of modeling MIPs.35 Non-specific binding is evident in the results from the blank (control) xerogel. These 

results demonstrate the selectivity and increased sensitivity of the MIP for DMMP. Coefficients of determination (R2

) 

can be found in Figure 11. Specific limit of detection (LOD) values are also provided in Figure 11. It is important to 

note that two different models were used to fit the response data for the energetic and CWA MIP-coated cantilevers. 

The polymer formulations and binding properties of each of these MIPs is very different, and therefore the response 

profiles were expected to vary as well. 

 

Proc. of SPIE Vol. 9455 94550W-11

Downloaded From: http://proceedings.spiedigitallibrary.org/ on 08/20/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx
R2 = 0.9979

LOD = 0.00135 ppb

R2 = 0.9986

LOD = 0.0077 ppb

Figure 11. Response profiles from a DMMP-responsive MIP-coated and control coated microbeam MEMS sensor to increasing 

concentrations of DMMP using the noise squeezing method. 

3.2 MIP Stability 

In an effort to improve MIP adhesion to the MEMS device, the xerogel precursor, MPTMS, was included in the polymer 

formulation used to prepare the MIP for energetic recognition. The thiol group in this precursor chemisorbs onto a gold 

surface, which was applied to the microcantilever during device fabrication. This polymer showed excellent adhesion 

and stability, with no apparent degradation after 2 years, which is necessary for practical field use. Further testing is 

needed to determine the stability of the MIP for CWA recognition. 

3.3 MIP Selectivity 

To assess the selectivity of the MIP-coated microbeam MEMS sensors for 2,4-DNT and DMMP, the devices should be 

challenged by molecules that are structurally similar to the energetic and CWA analytes of interest. To demonstrate 

selectivity of the MIP for energetic detection, a MIP-coated microbeam sensor was challenged with toluene vapor. 

Toluene is the backbone molecule of both 2,4-DNT and TNT. This data has been previously described using the 

bifurcation sweep tracking method.19 The selectivity of the MIP for CWA detection has not yet been assessed. 

4. CONCLUSION AND FUTURE WORK 

The work reported here validates the MIP-coated microcantilever sensing concept and demonstrates the feasibility of this 

MEMS sensor for the detection of explosive compounds and CWAs. To date, this is one of the only demonstrations of a 

MIP-coated microbeam MEMS sensing platform for these targets. Although preliminary, the data suggests that this 

combination is an effective and robust chemical nanosensing scheme. Further investigations will focus on refinement of 

the MIP (i.e., xerogel formulation) for improved selectivity. Finally, the MIP-coated microcantilever sensor platform 

evaluation should be expanded to include other explosives and chemical warfare agents of interest to the Army. A 

successful MIP-coated microbeam MEMS sensing format could reduce sensor cost and size, while maintaining the high 

sensitivity, selectivity, and portability needed for military applications. 

Proc. of SPIE Vol. 9455 94550W-12

Downloaded From: http://proceedings.spiedigitallibrary.org/ on 08/20/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx
5. REFERENCES 

[1] H. P. Lang et al., A chemical sensor based on micromechanical cantilever array for the identification of gases 

and vapors. Appl. Phys. A 66, 561 (1998). 

[2] F. M. Battiston et al., A chemical sensor based on a microfabricated cantilever array with simultaneous 

resonance-frequency and bending readout. Sens. Actuators, B 77, 122 (2001). 

[3] M. Yan, O. Ramstrom, Eds., Molecularly Imprinted Materials: Science and Technology, (Marcel Dekker, New 

York, NY, 2005). 

[4] E. L. Holthoff, F. V. Bright, Molecularly templated materials in chemical sensing. Anal. Chim. Acta 594, 147 

(2007). 

[5] N. R. Walker et al., Selective detection of gas-phase TNT by integrated optical waveguide spectrometry using 

molecularly imprinted sol-gel sensing films. Anal. Chim. Acta 593, 82 (2007). 

[6] A. L. Graham, C. A. Carlson, P. L. Edmiston, Development and characterization of molecularly imprinted solgel materials for the selected detection of DDT. Anal. Chem. 74, 458 (2002). 

[7] M. K. P. Leung, C.-F. Chow, M. H. W. Lam, A sol-gel derived molecular imprinted luminescent PET sensing 

material for 2,4-dichlorophenoxyacetic acid. J. Mater. Chem. 11, 2985 (2001). 

[8] E. L. Shughart, K. Ahsan, M. R. Detty, F. V. Bright, Site selectively templated and tagged xerogels for 

chemical sensors. Anal. Chem. 78, 3165 (2006). 

[9] C. J. Brinker, G. W. Scherer, Sol-Gel Science. (Academic Press, New York, NY, 1989). 

[10] A. Rose, Z. Zhu, C. F. Madigan, T. M. Swager, V. Bulovic, Sensitivity gains in chemosensing by lasing action 

in organic polymers. Nature 434, 876 (2005). 

[11] C. Xie et al., Molecular imprinting at walls of silica nanotubes for TNT recognition. Anal. Chem. 80, 437 

(2008). 

[12] I. Levitsky, S. G. Krivoshlykov, Rational design of a nile red/polymer composite film for fluorescence sensing 

of organophosphonate vapors using hydrogen bond acidic polymers. Anal. Chem. 73, 3441 (2001). 

[13] F. Horemans et al., MIP-based biomimetic sensor for the impedimetric detecion of histamine in different pH 

environments. Sens. Actuators, B 148, 392 (2010). 

[14] R. Thoelen et al., A MIP-based impedimetric sensor for the detection of low-MW molecules. Biosens. 

Bioelectron. 23, 913 (2008). 

[15] D. Croux et al., Development of multichannel quartz crystal microbalances for MIP-based biosensing. Phys. 

Status Solidi A 209, 892 (2012). 

[16] C. Ayela, F. Vandevelde, D. Lagrange, K. Haupt, L. Nicu, Combining resonant piezoelectric micromembranes 

with molecularly imprinted polymers. Angew. Chem. Int. Ed. 46, 9271 (2007). 

[17] J. A. Garcia-Calzon, M. E. Diaz-Garcia, Characterization of binding sites in molecularly imprinted polymers. 

Sens. Actuators, B 123, 1180 (2007). 

[18] E. L. Holthoff, D. N. Stratis-Cullum, M. E. Hankus, A nanosensor for TNT detection based on molecularly 

imprinted polymers and surface enhanced Raman scattering. Sensors 11, 2700 (2011). 

[19] K. L. Turner, C. B. Burgner, Z. Yie, E. L. Holthoff, paper presented at the 2012 IEEE Sensors, Taipei, Taiwan, 

28-31 Oct 2012. 

[20] K. L. Ekinci, Y. T. Yang, M. L. Roukes, Ultimate limits to inertial mass sensing based upon 

nanoelectromechanical systems. J. Appl. Phys. 95, 2682 (2004). 

[21] V. Kumar et al., paper presented at the ASME 2011 International Design Engineering Technical Conferences 

and Computers and Information in Engineering Conference, 2011. 

[22] J. F. Rhoads et al., Generalized parametric resonance in electrostatically actuated microelectromechanical 

oscillators. J. Sound Vibration 296, 797 (2006). 

[23] M. Napoli, R. Baskaran, K. L. Turner, b. Bamieh, paper presented at the IEEE The Sixteenth Annual 

International Conference on Micro Electro Mechanical Systems, 2003, Kyoto, Japan, 23 Jan 2003. 

[24] W. Zhang, K. L. Turner, Application of parametric resonance amplification in a single-crystal silicon microoscillator based mass sensor. Sens. Actuators, A 122, 23 (2005). 

[25] N. Miller, C. B. Burgner, M. Dykman, S. W. Shaw, K. L. Turner, Fast estimation of bifurcation conditions 

using noisy response data. Proc. SPIE 7647, 76470O (2010). 

[26] C. B. Burgner, N. Miller, S. W. Shaw, K. L. Turner, paper presented at the Solid-State Sensor, Actuator, and 

Microsystems Workshop, Hilton Head, SC, 2010. 

Proc. of SPIE Vol. 9455 94550W-13

Downloaded From: http://proceedings.spiedigitallibrary.org/ on 08/20/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx
[27] Z. Yie, M. A. Zielke, C. B. Burgner, K. L. Turner, Comparison of parametric and linear mass detection in the 

presence of detection noise. J. Micromech. Microeng. 21, 025027 (2011). 

[28] M. Evstigneev, Statistics of forced thermally activated escape events out of a metastable state: most probable 

escape force and escape-force moments. Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 78, (2008). 

[29] P. Mandel, T. Erneux, The slow passage through a steady bifurcation: Delay and memory effects. J. Stat. Phys. 

48, 1059 (1987). 

[30] C. B. Burgner, K. L. Turner, N. Miller, S. W. Shaw, paper presented at the ASME 2011 International Design 

Engineering Technical Conferences and Computers and Information in Engineering Conference, 2011. 

[31] L. L. Li, E. L. Holthoff, L. A. Shaw, C. B. Burgner, K. L. Turner, Noise squeezing controlled parametric 

bifurcation tracking of MIP-coated microbeam MEMS sensor for TNT explosive gas sensing`. J. MEMS 23, 

(2014). 

[32] M. E. Walsh, T. F. Jenkins, P. G. Thorne, Laboratory and analytical methods for explosives residues in soil. J. 

Energ. Mater. 13, 357 (1995). 

[33] T. Hiller, L. L. Li, E. L. Holthoff, B. Bamieh, K. L. Turner, System identification, design and implementation 

of amplitude feedback control on a nonlinear parametric MEM resonator for trace nerve agent sensing. J. 

MEMS early access online, (2015). 

[34] D. W. Allan, Statistics of atomic frequency standards. Proc. IEEE Sensors 54, 221 (1966). 

[35] I. Umpleby, R. J., S. C. Baxter, Y. Chen, R. N. Shah, K. D. Shimizu, Characterization of molecularly imprinted 

polymers with the Langmuir-Freundlich isotherm. Anal. Chem. 73, 4584 (2001). 

Proc. of SPIE Vol. 9455 94550W-14

Downloaded From: http://proceedings.spiedigitallibrary.org/ on 08/20/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx
14 

 1 DEFENSE TECH INFO CTR 

(PDF) DTIC OCA

 2 US ARMY RSRCH LAB

(PDF) IMAL HRA MAIL & RECORDS MGMT

 TECHL LIB

 1 GOVT PRNTG OFC

(PDF) A MALHOTRA

 4 US ARMY RSRCH LAB

(PDF) ATTN RDRL SEE E

 M FARRELL

 E HOLTHOFF

 P PELLEGRINO

 G WOOD