Bulk acoustic wave modes in quartz for sensing measurand-induced mechanical and electrical property changes

Schmitt, Ron F; Allen, John; Vetelino, J.F.; Parks, J.M.; Zhang, Chao

doi:10.1016/s0925-4005(01)00591-3

Cited by 18 publications

(14 citation statements)

References 19 publications

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“…During large changes in the resonant peak position or intensity, lock-in electronics may lose the position of the harmonic peak and begin tracking the position of undesirable spurious mode, causing discontinuous jumps in measured impedance spectra. , To avoid this, spurs are often fitted separately from main resonance peaks and removed by subtraction or disregarded completely . The separation between spurious resonances and main harmonic peaks decreases with harmonic numbers, leading to significant distortion and coupling of spurs to resonant peaks at high harmonics. ,, For cases in which the quality factor of a spurious peak is higher than that of the harmonic peak, tracking of the spurious peak position yields higher sensitivity in frequency shift measurement than does tracking of the harmonic peak. While commercial QCM control software often records resonant peak parameters only, IMECS control software tracks and records full QCM conductance spectral information, which enables correlation analysis between main resonance peak behavior and the behavior of spurious overtone peaks.…”

Section: Resultsmentioning

confidence: 99%

“…70 The separation between spurious resonances and main harmonic peaks decreases with harmonic numbers, leading to significant distortion and coupling of spurs to resonant peaks at high harmonics. 62,67,68 For cases in which the quality factor of a spurious peak is higher than that of the harmonic peak, tracking of the spurious peak position yields higher sensitivity in frequency shift measurement than does tracking of the harmonic peak. While commercial QCM control software often records resonant peak parameters only, IMECS control software tracks and records full QCM conductance spectral information, which enables correlation analysis between main resonance peak behavior and the behavior of spurious overtone peaks.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

“…66 During large changes in the resonant peak position or intensity, lock-in electronics may lose the position of the harmonic peak and begin tracking the position of undesirable spurious mode, causing discontinuous jumps in measured impedance spectra. 67,68 To avoid this, spurs are often fitted separately from main resonance peaks and removed by subtraction 69 or disregarded completely. 70 The separation between spurious resonances and main harmonic peaks decreases with harmonic numbers, leading to significant distortion and coupling of spurs to resonant peaks at high harmonics.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

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Machine Intelligence-Centered System for Automated Characterization of Functional Materials and Interfaces

Muckley

Vasudevan

Sumpter

et al. 2022

ACS Appl. Mater. Interfaces

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Classic design of experiment relies on a time-intensive workflow that requires planning, data interpretation, and hypothesis building by experienced researchers. Here, we describe an integrated, machine-intelligent experimental system which enables simultaneous dynamic tests of electrical, optical, gravimetric, and viscoelastic properties of materials under a programmable dynamic environment. Specially designed software controls the experiment and performs on-the-fly extensive data analysis and dynamic modeling, real-time iterative feedback for dynamic control of experimental conditions, and rapid visualization of experimental results. The system operates with minimal human intervention and enables time-efficient characterization of complex dynamic multifunctional environmental responses of materials with simultaneous data processing and analytics. The system provides a viable platform for artificial intelligence (AI)-centered material characterization, which, when coupled with an AI-controlled synthesis system, could lead to accelerated discovery of multifunctional materials.

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Section: Resultsmentioning

confidence: 99%

Section: ■ Results and Discussionmentioning

confidence: 99%

Section: ■ Results and Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Machine Intelligence-Centered System for Automated Characterization of Functional Materials and Interfaces

Muckley

Vasudevan

Sumpter

et al. 2022

ACS Appl. Mater. Interfaces

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“…is a frequency constant (the electromechanical coupling constant) of AT-cut quartzes and is defined as the half of the propagation velocity of the acoustic wave in a TSM quartz resonators, and is 1665 m•s −1 . [204,[287][288][289] The quartz disks used in this work have a fundamental mode of 5 MHz, which corresponds to a plate thickness of 330 µm.…”

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confidence: 99%

Label-free and Multi-parametric Monitoring of Cell-based Assays with Substrate-embedded Sensors

Oberleitner

2018

Springer Theses

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These cellular responses and the accompanying changes of physicochemical parameters are what is to be detected and transferred into a measurable electrical signal by the transducer units of the label-free biosensor devices (Fig. 1-1). There are various types of transducers, distinguishable by the underlying physicochemical phenomenon: electrochemical (including potentiometric, amperometric, and impedimetric), optical, thermometric, piezoelectric, and magnetic transduction. [8] Tab. 1-1 gives an LAPSLight-addressable potentiometric sensors (LAPSs) are multilayer field-effect devices similar to ISFETs [66] . A LAPS consists of a doped semiconductor covered with an insulator layer and a chemosensitive layer. The device is immersed in an electrolyte solution. The semiconductor is connected with a reference electrode in contact with the electrolyte (Fig. 1-2 B; reviewed in [10,17,[67][68][69][70] with respect to biological and cell-based applications). The insulator material of LAPSs is typically made up either of a single SiO 2 layer 1.1 Label-free Biosensors for Cell-based Assays 7 chip-based systems for the label-free and continuous monitoring of DO in cell-based assays, i.e. the oxygen consumption rate (OCR) of cells. [47,48,50,53,54,57,[60][61][62] The sensor chips with integrated amperometric oxygen sensors are typically build up as multi-parametric sensors and contain further physicochemical transducer structures like e.g. for cell morphology testing and ECAR monitoring. Besides the direct measurement of DO, the amperometric sensors are also capable of sensing indirectly any species that is consumed or produced in an oxidase-based enzymatic reaction (amperometric enzyme sensor) via the oxygen or hydrogen peroxide concentration. For this purpose, the amperometric pO 2 sensor is coated with a layer in which the respective enzyme is immobilized and which enables free diffusion of all reactants between the bulk solution and the sensor surface. This approach was first presented by Clark and Lyons as an amperometric sensor for glucose [85] and has also been applied as transduction method in cell-based assays for the label-free determination and monitoring of glucose and lactose [78,79] . A list of physiologically relevant analytes that have been successfully monitored by amperometric enzyme sensors is given in [86] . ECISElectrical impedance-based sensing of adherent cells, also termed as electric cell-substrate impedance sensing (ECIS), utilizes the property of cells to impede AC current flow when they are in close contact to the substrate, i.e. a small gold-film working electrode (Fig. 1-2 D). This technique was presented first by Giaever and Keese in 1984 [87] as "morphological biosensor for mammalian cells" [88] . The principle of ECIS, the method of impedance spectroscopy, and the analysis, physiological meaning, and modeling of impedance data are extensively addressed in the methods section 3.4 Electric Cell-Substrate Impedance Sensing (ECIS). Briefly summarized, ECIS enables the time-resolved, label-free, and ...

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“…QCM sensitivity is extremely high, allowing one to measure changes as small as a few nanograms 7 . At present, QCMs are used to monitor film thickness, detect the presence of toxic gases, and measure the progression of molecular interactions such as moisture uptake in paints 8 .…”

Section: Introductionmentioning

confidence: 99%

Rapid Inspection of Carbon Nanotube Quality

Hooker

Geiss

Schilt

et al.

Nanostructured Materials and Nanotechnology

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Carbon nanotubes have unique properties of interest for applications in aerospace, electronics, and biotechnology. However, the properties of different batches of carbon nanotubes can vary considerably depending on chemical purity and the nanotube types present (e.g., diameter and chirality distribution). Distinguishing the constituents of each nanotube batch is challenging, with many different techniques used in concert. Thermogravimetric analysis (TGA) provides one measure of nanotube purity by assessing the material's thermal stability (i.e., how it oxidizes with temperature). Unfortunately, however, TGA analysis requires a relatively large specimen for each measurement (several milligrams), making it inappropriate for rapid screening of incoming materials. Moreover, the measurement provides only an average purity for the analyzed sample, and variability can occur on a much finer level. As many applications will utilize only a small quantity of nanotubes, new approaches are needed to assess variability for a much smaller specimen size. This paper describes a new analysis method that uses a quartz crystal as a miniature microbalance for determining mass changes at elevated temperature. Thin nanotube coatings are spray deposited onto the crystals, and shifts in a crystal's resonance frequency are directly correlated with changes in coating mass during heating due to volatilization of different carbon species. By monitoring the response of the crystal at one or more temperatures, different nanotube specimens can be directly compared. This paper demonstrates concept feasibility by comparing quartz crystal results with conventional TGA analysis and discusses methods for applying the technique in process and quality control settings.

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Bulk acoustic wave modes in quartz for sensing measurand-induced mechanical and electrical property changes

Cited by 18 publications

References 19 publications

Machine Intelligence-Centered System for Automated Characterization of Functional Materials and Interfaces

Machine Intelligence-Centered System for Automated Characterization of Functional Materials and Interfaces

Label-free and Multi-parametric Monitoring of Cell-based Assays with Substrate-embedded Sensors

Rapid Inspection of Carbon Nanotube Quality

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