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Description
Understanding the interplay between the electrical and mechanical properties of single molecules is of fundamental importance for molecular electronics. The sensitivity of charge transport to mechanical fluctuations is a key problem in developing long lasting molecular devices. Furthermore, harnessing this response to mechanical perturbation, molecular devices which can be mechanically gated can be developed. This thesis demonstrates three examples of the unique electromechanical properties of single molecules.
First, the electromechanical properties of 1,4-benzenedithiol molecular junctions are investigate. Counterintuitively, the conductance of this molecule is found to increase by more than an order of magnitude when stretched. This conductance increase is found to be reversible when the molecular junction is compressed. The current-voltage, conductance-voltage and inelastic electron tunneling spectroscopy characteristics are used to attribute the conductance increase to a strain-induced shift in the frontier molecular orbital relative to the electrode Fermi level, leading to resonant enhancement in the conductance.
Next, the effect of stretching-induced structural changes on charge transport in DNA molecules is studied. The conductance of single DNA molecules with lengths varying from 6 to 26 base pairs is measured and found to follow a hopping transport mechanism. The conductance of DNA molecules is highly sensitive to mechanical stretching, showing an abrupt decrease in conductance at surprisingly short stretching distances, with weak dependence on DNA length. This abrupt conductance decrease is attributed to force-induced breaking of hydrogen bonds in the base pairs at the end of the DNA sequence.
Finally, the effect of small mechanical modulation of the base separation on DNA conductance is investigated. The sensitivity of conductance to mechanical modulation is studied for molecules of different sequence and length. Sequences with purine-purine stacking are found to be more responsive to modulation than purine-pyrimidine sequences. This sensitivity is attributed to the perturbation of &pi-&pi stacking interactions and resulting effects on the activation energy and electronic coupling for the end base pairs.
First, the electromechanical properties of 1,4-benzenedithiol molecular junctions are investigate. Counterintuitively, the conductance of this molecule is found to increase by more than an order of magnitude when stretched. This conductance increase is found to be reversible when the molecular junction is compressed. The current-voltage, conductance-voltage and inelastic electron tunneling spectroscopy characteristics are used to attribute the conductance increase to a strain-induced shift in the frontier molecular orbital relative to the electrode Fermi level, leading to resonant enhancement in the conductance.
Next, the effect of stretching-induced structural changes on charge transport in DNA molecules is studied. The conductance of single DNA molecules with lengths varying from 6 to 26 base pairs is measured and found to follow a hopping transport mechanism. The conductance of DNA molecules is highly sensitive to mechanical stretching, showing an abrupt decrease in conductance at surprisingly short stretching distances, with weak dependence on DNA length. This abrupt conductance decrease is attributed to force-induced breaking of hydrogen bonds in the base pairs at the end of the DNA sequence.
Finally, the effect of small mechanical modulation of the base separation on DNA conductance is investigated. The sensitivity of conductance to mechanical modulation is studied for molecules of different sequence and length. Sequences with purine-purine stacking are found to be more responsive to modulation than purine-pyrimidine sequences. This sensitivity is attributed to the perturbation of &pi-&pi stacking interactions and resulting effects on the activation energy and electronic coupling for the end base pairs.
ContributorsBruot, Christopher, 1986- (Author) / Tao, Nongjian (Thesis advisor) / Lindsay, Stuart (Committee member) / Mujica, Vladimiro (Committee member) / Ferry, David (Committee member) / Arizona State University (Publisher)
Created2014
Description
Monitoring vital physiological signals, such as heart rate, blood pressure and breathing pattern, are basic requirements in the diagnosis and management of various diseases. Traditionally, these signals are measured only in hospital and clinical settings. An important recent trend is the development of portable devices for tracking these physiological signals non-invasively by using optical methods. These portable devices, when combined with cell phones, tablets or other mobile devices, provide a new opportunity for everyone to monitor one’s vital signs out of clinic.
This thesis work develops camera-based systems and algorithms to monitor several physiological waveforms and parameters, without having to bring the sensors in contact with a subject. Based on skin color change, photoplethysmogram (PPG) waveform is recorded, from which heart rate and pulse transit time are obtained. Using a dual-wavelength illumination and triggered camera control system, blood oxygen saturation level is captured. By monitoring shoulder movement using differential imaging processing method, respiratory information is acquired, including breathing rate and breathing volume. Ballistocardiogram (BCG) is obtained based on facial feature detection and motion tracking. Blood pressure is further calculated from simultaneously recorded PPG and BCG, based on the time difference between these two waveforms.
The developed methods have been validated by comparisons against reference devices and through pilot studies. All of the aforementioned measurements are conducted without any physical contact between sensors and subjects. The work presented herein provides alternative solutions to track one’s health and wellness under normal living condition.
This thesis work develops camera-based systems and algorithms to monitor several physiological waveforms and parameters, without having to bring the sensors in contact with a subject. Based on skin color change, photoplethysmogram (PPG) waveform is recorded, from which heart rate and pulse transit time are obtained. Using a dual-wavelength illumination and triggered camera control system, blood oxygen saturation level is captured. By monitoring shoulder movement using differential imaging processing method, respiratory information is acquired, including breathing rate and breathing volume. Ballistocardiogram (BCG) is obtained based on facial feature detection and motion tracking. Blood pressure is further calculated from simultaneously recorded PPG and BCG, based on the time difference between these two waveforms.
The developed methods have been validated by comparisons against reference devices and through pilot studies. All of the aforementioned measurements are conducted without any physical contact between sensors and subjects. The work presented herein provides alternative solutions to track one’s health and wellness under normal living condition.
ContributorsShao, Dangdang (Author) / Tao, Nongjian (Thesis advisor) / Li, Baoxin (Committee member) / Hekler, Eric (Committee member) / Karam, Lina (Committee member) / Arizona State University (Publisher)
Created2016
Description
Studying charge transport through single molecules is of great importance for unravelling charge transport mechanisms, investigating fundamentals of chemistry, and developing functional building blocks in molecular electronics.
First, a study of the thermoelectric effect in single DNA molecules is reported. By varying the molecular length and sequence, the charge transport in DNA was tuned to either a hopping- or tunneling-dominated regimes. In the hopping regime, the thermoelectric effect is small and insensitive to the molecular length. Meanwhile, in the tunneling regime, the thermoelectric effect is large and sensitive to the length. These findings indicate that by varying its sequence and length, the thermoelectric effect in DNA can be controlled. The experimental results are then described in terms of hopping and tunneling charge transport models.
Then, I showed that the electron transfer reaction of a single ferrocene molecule can be controlled with a mechanical force. I monitor the redox state of the molecule from its characteristic conductance, detect the switching events of the molecule from reduced to oxidized states with the force, and determine a negative shift of ~34 mV in the redox potential under force. The theoretical modeling is in good agreement with the observations, and reveals the role of the coupling between the electronic states and structure of the molecule.
Finally, conclusions and perspectives were discussed to point out the implications of the above works and future studies that can be performed based on the findings.
First, a study of the thermoelectric effect in single DNA molecules is reported. By varying the molecular length and sequence, the charge transport in DNA was tuned to either a hopping- or tunneling-dominated regimes. In the hopping regime, the thermoelectric effect is small and insensitive to the molecular length. Meanwhile, in the tunneling regime, the thermoelectric effect is large and sensitive to the length. These findings indicate that by varying its sequence and length, the thermoelectric effect in DNA can be controlled. The experimental results are then described in terms of hopping and tunneling charge transport models.
Then, I showed that the electron transfer reaction of a single ferrocene molecule can be controlled with a mechanical force. I monitor the redox state of the molecule from its characteristic conductance, detect the switching events of the molecule from reduced to oxidized states with the force, and determine a negative shift of ~34 mV in the redox potential under force. The theoretical modeling is in good agreement with the observations, and reveals the role of the coupling between the electronic states and structure of the molecule.
Finally, conclusions and perspectives were discussed to point out the implications of the above works and future studies that can be performed based on the findings.
ContributorsLi, Yueqi, Ph.D (Author) / Tao, Nongjian (Thesis advisor) / Buttry, Daniel (Committee member) / Mujica, Vladimiro (Committee member) / Arizona State University (Publisher)
Created2017
Description
Antibiotic resistant bacteria are a worldwide epidemic threatening human survival. Antimicrobial susceptibility tests (ASTs) are important for confirming susceptibility to empirical antibiotics and detecting resistance in bacterial isolates. Current ASTs are based on bacterial culturing, which take 2-14 days to complete depending on the microbial growth rate. Considering the high mortality and morbidity rates for most acute infections, such long time frames are clinically impractical and pose a huge risk to a patient's life. A faster AST will reduce morbidity and mortality rates, as well as help healthcare providers, administer narrow spectrum antibiotics at the earliest possible treatment stage.
In this dissertation, I developed a nonculture-based AST using an imaging and cell tracking technology. I track individual Escherichia coli O157:H7 (E. coli O157:H7) Uropathogenic Escherichia Coli (UPEC) cells, widely implicated in food-poisoning outbreaks and urinary tract infections respectively. Cells tethered to a surface are tracked on the nanometer scale, and phenotypic motion is correlated with bacterial metabolism. Antibiotic action significantly slows down motion of tethered bacterial cells, which is used to perform antibiotic susceptibility testing. Using this technology, the clinical minimum bactericidal concentration of an antibiotic against UPEC pathogens was calculated within 2 hours directly in urine samples as compared to 3 days using current gold standard tools.
Such technologies can make a tremendous impact to improve the efficacy and efficiency of infectious disease treatment. This has the potential to reduce the antibiotic mis-prescription steeply, which can drastically decrease the annual 2M+ hospitalizations and 23,000+ deaths caused due to antibiotic resistance bacteria along with saving billions of dollars to payers, patients, and hospitals.
In this dissertation, I developed a nonculture-based AST using an imaging and cell tracking technology. I track individual Escherichia coli O157:H7 (E. coli O157:H7) Uropathogenic Escherichia Coli (UPEC) cells, widely implicated in food-poisoning outbreaks and urinary tract infections respectively. Cells tethered to a surface are tracked on the nanometer scale, and phenotypic motion is correlated with bacterial metabolism. Antibiotic action significantly slows down motion of tethered bacterial cells, which is used to perform antibiotic susceptibility testing. Using this technology, the clinical minimum bactericidal concentration of an antibiotic against UPEC pathogens was calculated within 2 hours directly in urine samples as compared to 3 days using current gold standard tools.
Such technologies can make a tremendous impact to improve the efficacy and efficiency of infectious disease treatment. This has the potential to reduce the antibiotic mis-prescription steeply, which can drastically decrease the annual 2M+ hospitalizations and 23,000+ deaths caused due to antibiotic resistance bacteria along with saving billions of dollars to payers, patients, and hospitals.
ContributorsSyal, Karan (Author) / Tao, Nongjian (Thesis advisor) / Haydel, Shelley (Committee member) / Rege, Kaushal (Committee member) / Wang, Shaopeng (Committee member) / Haynes, Karmella (Committee member) / Arizona State University (Publisher)
Created2017
Description
In this thesis, a breadboard Integrated Microarray Printing and Detection System (IMPDS) was proposed to address key limitations of traditional microarrays. IMPDS integrated two core components of a high-resolution surface plasmon resonance imaging (SPRi) system and a piezoelectric dispensing system that can print ultra-low volume droplets. To avoid evaporation of droplets in the microarray, a 100 μm thick oil layer (dodecane) was used to cover the chip surface. The interaction between BSA (Bovine serum albumin) and Anti-BSA was used to evaluate the capability of IMPDS. The alignment variability of printing, stability of droplets array and quantification of protein-protein interactions based on nanodroplet array were evaluated through a 10 x 10 microarray on SPR sensor chip. Binding kinetic constants obtained from IMPDS are close with results from commercial SPR setup (BI-3000), which indicates that IMPDS is capable to measure kinetic constants accurately. The IMPDS setup has following advantages: 1) nanoliter scale sample consumption, 2) high-throughput detection with real-time kinetic information for biomolecular interactions, 3) real-time information during printing and spot-on-spot detection of biomolecular interactions 4) flexible selection of probes and receptors (M x N interactions). Since IMPDS studies biomolecular interactions with low cost and high flexibility in real-time manner, it has great potential in applications such as drug discovery, food safety and disease diagnostics, etc.
ContributorsXiao, Feng (Author) / Tao, Nongjian (Thesis advisor) / Borges, Chad (Committee member) / Guo, Jia (Committee member) / Arizona State University (Publisher)
Created2017
Description
Cytometry is a method used to measure and collect the physical and chemical characteristics of a population of cells. In modern medical settings, the trend of precision and personalized medicines has imposed a need for rapid point-of-care diagnostic technologies. A rapid cytometric method, which aims at detecting and analyzing cells in direct patient samples, is therefore desirable. This dissertation presents the development of light-scattering-based imaging methods for detecting and analyzing cells and applies the technology in four applications. The first application is tracking phenotypic features of single particles, thereby differentiating bacterial cells from non-living particles in a label-free manner. The second application is a culture-free antimicrobial susceptibility test that rapidly tracks multiple, antimicrobial-induced phenotypic changes of bacterial cells with results obtained within 30 – 90 minutes. The third application is rapid antimicrobial susceptibility testing (AST) of bacterial cell growth directly in-patient urine samples, without a pre-culture step, within 90 min. This technology demonstrated rapid (90 min) detection of Escherichia coli in 24 clinical urine samples with 100% sensitivity and 83% specificity and rapid (90 min) AST in 12 urine samples with 87.5% categorical agreement with two antibiotics, ampicillin and ciprofloxacin. The fourth application is a multi-dimensional imaging cytometry system that integrates multiple light sources from different angles to simultaneously capture time-lapse, forward scattering and side scattering images of blood cells. The system has demonstrated capacity to detect red blood cell agglutination, assess red blood cell lysis, and differentiate red and white blood cells for potential implementation in clinical hematology analyses. These large-volume, light-scattering cytometric technologies can be used and applied in clinical and research settings to study, detect, and analyze cells. These studies developed rapid point-of-care diagnostic and imaging technologies for collectively advancing modern medicine and global health.
ContributorsMo, Manni (Author) / Borges, Chad (Thesis advisor) / Tao (Deceased), Nongjian (Thesis advisor) / Wang, Shaopeng (Committee member) / Chiu, Po-Lin (Committee member) / Haydel, Shelley (Committee member) / Arizona State University (Publisher)
Created2020
Description
Air pollution has been linked to various health problems but how different air pollutants and exposure levels contribute to those diseases remain largely unknown. Researchers have mainly relied on data from government air monitoring stations to study the health effects of air pollution exposure. The limited information provided by sparse stations has low spatial and temporal resolution, which is not able to represent the actual exposure of individuals. A tool that can accurately monitor personal exposure provides valuable data for epidemiologists to understand the relationship between air pollution and certain diseases. It also allows individuals to be aware of any ambient air quality issues and prevent air pollution exposure. To build such a tool, sensors with features of fast response, small size, long lifetime, high sensitivity, high selectivity, and multi-analyte sensing are of great importance.
In order to meet these requirements, three generations of novel colorimetric sensors have been developed. The first generation is mosaic colorimetric sensors based on tiny sensor blocks and by detecting absorbance change after each air sample injection, the target analyte concentration can be measured. The second generation is a gradient-based colorimetric sensor. Lateral transport of analytes across the colorimetric sensor surface creates a color gradient that shifts along the transport direction over time, and the sensor tracks the gradient shift and converts it into analyte concentration in real-time. The third generation is gradient-based colorimetric arrays fabricated by inkjet-printing method that integrates multiple sensors on a miniaturized sensor chip. Unlike traditional colorimetric sensors, such as detection tubes and optoelectronic nose, that are typically for one-time use, the presented three generations of colorimetric sensors aim to continuously monitor multiple air pollutants and the sensor lifetime and fabrication methods have been improved over each generation. Ozone, nitrogen dioxide, formaldehyde and carbon monoxide are chosen as analytes of interest. The performance of sensors has been validated in the lab and field tests, proving the capability of the sensors to be used for personal exposure monitoring.
In order to meet these requirements, three generations of novel colorimetric sensors have been developed. The first generation is mosaic colorimetric sensors based on tiny sensor blocks and by detecting absorbance change after each air sample injection, the target analyte concentration can be measured. The second generation is a gradient-based colorimetric sensor. Lateral transport of analytes across the colorimetric sensor surface creates a color gradient that shifts along the transport direction over time, and the sensor tracks the gradient shift and converts it into analyte concentration in real-time. The third generation is gradient-based colorimetric arrays fabricated by inkjet-printing method that integrates multiple sensors on a miniaturized sensor chip. Unlike traditional colorimetric sensors, such as detection tubes and optoelectronic nose, that are typically for one-time use, the presented three generations of colorimetric sensors aim to continuously monitor multiple air pollutants and the sensor lifetime and fabrication methods have been improved over each generation. Ozone, nitrogen dioxide, formaldehyde and carbon monoxide are chosen as analytes of interest. The performance of sensors has been validated in the lab and field tests, proving the capability of the sensors to be used for personal exposure monitoring.
ContributorsLin, Chenwen (Author) / Tao, Nongjian (Thesis advisor) / Borges, Chad R (Committee member) / Hayes, Mark A. (Committee member) / Arizona State University (Publisher)
Created2019
Description
Quantifying molecular interactions is pivotal for understanding biological processes at molecular scale and for screening drugs. Although various detection technologies have been developed, it is still challenging to quantify the binding kinetics of small molecules because the sensitivities of the mainstream technologies scale down with the size of the molecule. To address this problem, two different optical detection methods, charge sensitive optical detection (CSOD) and virion
ano-oscillators, are developed to measure the binding-induced charge change instead of the mass change, which enables quantification of the binding kinetics for both large and small molecules.
In particular, the nano-oscillator approach provides a unique capability to image individual nanoparticles and measure the size and charge of each nanoparticle simultaneously. This approach is applied to measure one of the smallest biological particles - single protein molecules. By tracking the oscillation of each protein molecule, the size, charge, and mobility are measured in real-time with high precision. This capability also allows to monitor the conformation and charge changes of single protein molecules upon ligand binding. Measuring the size and charge of single proteins opens a new revenue to protein analysis and disease biomarker detection at the single molecule level.
The virion
ano-oscillators and the single protein approach employ a scheme where a particle is tethered to the surface with a polymer molecule. The dynamics of the particle is governed by two important forces: One is entropic force arising from the conformational change of the molecular tether, and the other is solvent damping on the particle and the molecule. The dynamics is studied by varying the type of the tether molecule, size of the particle, and viscosity of the solvent. The findings provide insights into single molecule studies using not only tethered particles, but also other approaches, including force spectroscopy using atomic force microscopy and nanopores.
ano-oscillators, are developed to measure the binding-induced charge change instead of the mass change, which enables quantification of the binding kinetics for both large and small molecules.
In particular, the nano-oscillator approach provides a unique capability to image individual nanoparticles and measure the size and charge of each nanoparticle simultaneously. This approach is applied to measure one of the smallest biological particles - single protein molecules. By tracking the oscillation of each protein molecule, the size, charge, and mobility are measured in real-time with high precision. This capability also allows to monitor the conformation and charge changes of single protein molecules upon ligand binding. Measuring the size and charge of single proteins opens a new revenue to protein analysis and disease biomarker detection at the single molecule level.
The virion
ano-oscillators and the single protein approach employ a scheme where a particle is tethered to the surface with a polymer molecule. The dynamics of the particle is governed by two important forces: One is entropic force arising from the conformational change of the molecular tether, and the other is solvent damping on the particle and the molecule. The dynamics is studied by varying the type of the tether molecule, size of the particle, and viscosity of the solvent. The findings provide insights into single molecule studies using not only tethered particles, but also other approaches, including force spectroscopy using atomic force microscopy and nanopores.
ContributorsMa, Guangzhong, Ph.D (Author) / Tao, Nongjian (Thesis advisor) / Wang, Shaopeng (Thesis advisor) / Ros, Alexandra (Committee member) / Guo, Jia (Committee member) / Arizona State University (Publisher)
Created2019
Description
Global industrialization and urbanization have led to increased levels of air pollution. The costs to society have come in the form of environmental damage, healthcare expenses, lost productivity, and premature mortality. Measuring pollutants is an important task for identifying its sources, warning individuals about dangerous exposure levels, and providing epidemiologists with data to link pollutants with diseases. Current methods for monitoring air pollution are inadequate though. They rely on expensive, complex instrumentation at limited fixed monitoring sites that do not capture the true spatial and temporal variation. Furthermore, the fixed outdoor monitoring sites cannot warn individuals about indoor air quality or exposure to chemicals at worksites. Recent advances in manufacturing and computing technology have allowed new classes of low-cost miniature gas sensor to emerge as possible alternatives. For these to be successful however, there must be innovations in the sensors themselves that improve reliability, operation, and their stability and selectivity in real environments. Three novel gas sensor solutions are presented. The first is the development of a wearable personal exposure monitor using all commercially available components, including two metal oxide semiconductor gas sensors. The device monitors known asthma triggers: ozone, total volatile organic compounds, temperature, humidity, and activity level. Primary focus is placed on the ozone sensor, which requires special circuits, heating algorithm, and calibration to remove temperature and humidity interferences. Eight devices are tested in multiple field tests. The second is the creation of a new compact optoelectronic gas sensing platform using colorimetric microdroplets printed on the surface of a complementary-metal-oxide-semiconductor (CMOS) imager. The nonvolatile liquid microdroplets provide a homogeneous, uniform environment that is ideal for colorimetric reactions and lensless optical measurements. To demonstrate one type of possible indicating system gaseous ammonia is detected by complexation with Cu(II). The third project continues work on the CMOS imager optoelectronic platform and develops a more robust sensing system utilizing hydrophobic aerogel particles. Ammonia is detected colorimetrically by its reaction with a molecular dye, with additives and surface treatments enhancing uniformity of the printed films. Future work presented at the end describes a new biological particle sensing system using the CMOS imager.
ContributorsMallires, Kyle Reed (Author) / Tao, Nongjian (Thesis advisor) / Forzani, Erica (Thesis advisor) / Wiktor, Peter (Committee member) / Wang, Di (Committee member) / Alford, Terry (Committee member) / Xian, Xiaojun (Committee member) / Arizona State University (Publisher)
Created2020
Description
Antibiotic resistance is a very important issue that threatens mankind. As bacteria
are becoming resistant to multiple antibiotics, many common antibiotics will soon
become ineective. The ineciency of current methods for diagnostics is an important
cause of antibiotic resistance, since due to their relative slowness, treatment plans
are often based on physician's experience rather than on test results, having a high
chance of being inaccurate or not optimal. This leads to a need of faster, pointof-
care (POC) methods, which can provide results in a few hours. Motivated by
recent advances on computer vision methods, three projects have been developed
for bacteria identication and antibiotic susceptibility tests (AST), with the goal of
speeding up the diagnostics process. The rst two projects focus on obtaining features
from optical microscopy such as bacteria shape and motion patterns to distinguish
active and inactive cells. The results show their potential as novel methods for AST,
being able to obtain results within a window of 30 min to 3 hours, a much faster
time frame than the gold standard approach based on cell culture, which takes at
least half a day to be completed. The last project focus on the identication task,
combining large volume light scattering microscopy (LVM) and deep learning to
distinguish bacteria from urine particles. The developed setup is suitable for pointof-
care applications, as a large volume can be viewed at a time, avoiding the need
for cell culturing or enrichment. This is a signicant gain compared to cell culturing
methods. The accuracy performance of the deep learning system is higher than chance
and outperforms a traditional machine learning system by up to 20%.
are becoming resistant to multiple antibiotics, many common antibiotics will soon
become ineective. The ineciency of current methods for diagnostics is an important
cause of antibiotic resistance, since due to their relative slowness, treatment plans
are often based on physician's experience rather than on test results, having a high
chance of being inaccurate or not optimal. This leads to a need of faster, pointof-
care (POC) methods, which can provide results in a few hours. Motivated by
recent advances on computer vision methods, three projects have been developed
for bacteria identication and antibiotic susceptibility tests (AST), with the goal of
speeding up the diagnostics process. The rst two projects focus on obtaining features
from optical microscopy such as bacteria shape and motion patterns to distinguish
active and inactive cells. The results show their potential as novel methods for AST,
being able to obtain results within a window of 30 min to 3 hours, a much faster
time frame than the gold standard approach based on cell culture, which takes at
least half a day to be completed. The last project focus on the identication task,
combining large volume light scattering microscopy (LVM) and deep learning to
distinguish bacteria from urine particles. The developed setup is suitable for pointof-
care applications, as a large volume can be viewed at a time, avoiding the need
for cell culturing or enrichment. This is a signicant gain compared to cell culturing
methods. The accuracy performance of the deep learning system is higher than chance
and outperforms a traditional machine learning system by up to 20%.
ContributorsIriya, Rafael (Author) / Turaga, Pavan (Thesis advisor) / Wang, Shaopeng (Committee member) / Grys, Thomas (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2020