Indian Institute of Science Bangalore
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Studies on chalcopyrite phosphides and phenolic acid-based derivatives towards lithium storage and chemical sensors
No full textLi-ion batteries are among the highly promising power sources for many emerging technologies, including electric vehicles and smart grids. However, an increased demand for energy density and long cycle life cannot be satisfied by the commercially available graphite anode at present as it represents a modest inherent specific capacity (372 mAh/g) and poses major safety risks due to lithium plating and subsequent growth of lithium dendrites. Si-based anodes have attracted significant attention due to their ultra-high theoretical capacity of 4200 mAh/g, but the practical application is limited due to their extreme volume expansion upon lithiation. In this context, the synergistic effect of combining group 14 elements (Si/Ge/Sn) with the group 12 (Zn/Cd) and 15 (P) elements is studied towards the formation of ternary chalcopyrite phosphides, which represent high performance with high initial coulombic efficiency, large specific capacity, suitable working potential, high-rate capability, and long-cycling life as compared to elemental Si-based anodes. The additional elements act as buffer matrix to cope with the volume expansion of Si-based anodes and also improve the lithium conductivity due to the formation of Li3P intermediate phases during alloying reactions. The phase change and lithiation intermediates are analyzed by using in-situ Raman and diffraction techniques. The application of these chalcopyrites is extended to photo-assisted anodes, where improved performance is observed along with self-charging characteristics under solar radiation. Further, these phosphides are studied for their humidity-sensing properties, where a fast response and high selectivity is observed for varying humidity conditions. In addition, phenolic acid-based derivatives are explored as potential organic electrode materials for Li-ion batteries, where highly reversible lithiation characteristics are analyzed by using Raman, FTIR, and XPS characterization techniques
Photo magnetic Investigation and Magneto-structural Correlation of Switchable Molecular Magnetic Materials
No full textModern life without magnetic materials is almost impossible to imagine. Mobile
phones, telecommunication, navigation, computer, television, credit cards, medical
equipment, data storage devices, and sensors are an integral part of modern life. The demand
and supply ratio of data storage devices is increasing day by day. To mitigate this, tremendous
effort is required toward the synthesis and development of high-density data storage devices.
Molecular systems exhibiting bistability i.e., a controlled and reversible change in their
physical properties by external stimuli have a tremendous possibility in molecular-scale
electronics e.g., data storage device, molecular qubits, quantum technology, molecular
spintronics, and nanotechnological application. In particular, molecular magnetism is a rapidly
growing field where molecules exhibiting photo- and thermo-chromism are of potential
interest. In this thesis, I have adopted a unique ‘complex as a ligand’ strategy to rationally
design and synthesize switchable molecular magnetic materials which exhibit interesting
physical properties such as single-molecule magnet (SMM), spin crossover (SCO), metal-tometal electron transfer (MMET) and electrical and thermal conductivity. A series of new
multifunctional homo-/hetero-bimetallic [Fe2Co2], [Fe2Fe2], and [Fe2Mn2] complexes have
been synthesized using a molecular approach. To understand better the contributing factors
for MMET properties, for example, ligand field effect, cooperativity, crystal matrix, and
electronic factors, we have performed detailed structural, magnetic, optical, spectroscopic,
and other physical characterization. Interestingly, some of these systems show interesting
on/off photo-switching and thermo- and photo-induced hysteresis effects. I have performed
a detailed study of the photo-induced metastable state along with the high-temperature
magneto-structural investigation. In other parts of my thesis, I have studied the singlemolecule magnet behavior in highly anisotropic Co(II) complexes and the spin state switching
behavior in Co(II) mono- and polymeric systems. In the last part of my thesis, I have coupled
both spin crossover and luminescence properties in a coordination polymer in which
concomitant change in both spin state and luminescence has been observed. Finally, I have
discussed the application of these switchable materials in optoelectronic devices
Studying the effect of Re on the Co-Ni-Al-Ti-Nb-Cr superalloy’s coarsening kinetics and establishing the high-throughput diffusion couple approach for alloy design
No full textThe studies are conducted to understand the effect of Re addition on microstructural evolution and coarsening kinetics of new Co-Ni-Al-Ti-Nb-Cr based superalloys. Lattice misfit is reduced by adding Re, confirmed from high-resolution XRD. As a result, the morphological transition from cuboidal to rounded cornered cubes is observed. Re solubility limit in the alloy is 3 at. % and excess Re promote the formation of TCP phases. Through APT analysis, it was found that there was no segregation of Re at the gamma/gamma prime interface. The Re addition helps retain the 0.2% proof strength up to 870°C with strength values greater than 650 MPa. However, the absence of yield strength anomaly (YSA) with Re is observed.
To understand the coarsening kinetics behavior of gamma prime precipitates in the alloys, isothermal heat treatment at temperatures of 900, 950 and 1000 deg. C for various times is conducted. By studying the temporal evolution of the following parameters during coarsening, the interpretations are made, and the correlations are established: precipitate size, PSD, lattice misfit, partitioning coefficients, morphological evolution, volume fraction, and micro-hardness. The rate constants (K) values for this class of alloys are comparable and better than many existing superalloys. Additionally, the activation energies for coarsening of the present alloys are estimated to be 260 and 240 kJ/mol, respectively, when 2 and 3 at. % Re are added.
The pseudo-binary diffusion couple approach is introduced to estimate the inter-diffusion coefficients in a multi-component system, in which only two elements will participate in developing the composition profiles. The same approach is examined for designing new alloys and validated for a recently developed superalloy system, Co-Ni-Al-Mo-Ta-Ti, where the effect of Cr is considered. The heat treatment conditions are established to transform the gradient of Cr in diffusion couple into corresponding microstructural evolution. The following changes can be evaluated using the diffusion couple method: morphological transition from cuboidal to spherical, evolution of precipitate volume fraction, the solubility limit of the Cr for the appearance of TCP phases, the evolution of micro-hardness and elastic modulus and the oxidation behavior (top oxide grain morphology and layer thickness)
Numerical Analysis to Understand Influence of Ventilation Systems on Thermal Comfort Parameters, Quality of Air, and Local Sweating
No full textThe body’s heat exchange mechanisms include sensible heat transfer at the skin surface (also called “Dry Heat exchange”) due to temperature differences (via conduction, convection, and radiation (long-wave and short-wave)), latent heat transfer (via moisture evaporating and diffusing through the skin, and through sweat evaporation on the surface), and sensible plus latent exchange via respiration from the lungs as the breathing process involves humidifying exhaled air with around 34◦C in normal resting person with more or less constant core temperature at 36◦C. It is important to predict comfort temperature in a built environment because the thermal comfort model has great potential for energy saving as well maintain a good well-being both at home and workplace and provide building sustainability. Hence, local sensation and local phenomenon (temperature gradients and velocity distribution) are gaining more popularity as CFD has become a very reliable and easy tool for in-depth analysis. Understanding this phenomenon is very crucial in understanding the adaptive thermal comfort. One of the most important physics that had been ignored for a long period of time which influences the thermal comfort of the occupant i.e., actual sweat analysis (modelling sweat as droplet or layered) based on local conditions. These local conditions are highly influenced by mechanical ventilation systems like using of fans and ac vents. Also, the quality of air determines the health and productivity of the occupant in any indoor environment. The higher concentration of carbon-dioxide causes dizziness, headache, and potential death in case it reaches a hazardous level. Similarly, air exchange from the outdoor to the indoor environment is necessary to remove bacteria, and viruses and to maintain fresh air for healthy breathing. The energy consumption in indoor environments is directly dependent on the ventilation systems that are used to maintain supposed Comfort Temperature and Air Quality. In this research, various ventilation methods are applied in indoor environments including Car Cabins, Conference Rooms, and Office Cubicles which are simulated in ANSYS CFX and FLUENT software using the κω-SST model.The use of a combination of a fan and ac vent or a fan with windows is found to be better in saving energy, maintaining air quality as well as keeping the temperature of the skin low. The Sweat is modelled as a combination of water (99 per cent) and NaCl (1 per cent) on a 1 cm X 1 cm area of skin surface to understand the effect of sweating on the skin temperature due to local conditions around the skin. Fans and AC vents are modelled in indoor environments to comprehend the influence of mechanical systems. This thesis aims to provide insights into the role of local conditions (velocity and temperature of the air) around the skin in determining the local skin temperature and the influence of mechanical ventilation systems on the quality of air as well. The concept presented in this paper has the potential to improve the popular thermoregulation models like FIALA, TANABE, and UCB or at least provide some idea about the possible incorporation of the sweating phenomenon considering the local environment to enhance their functionality. Likewise, the research aims to encourage further combined study on air quality and thermal comfort for energy efficient and safe design of indoor environment
Novel Algorithms for Improving Agricultural Planning and Operations using Artificial Intelligence and Game Theory
No full textThis dissertation work is motivated by the critical need to address a perennial global problem, namely, how to mitigate the distress of the small and marginal agricultural farmers in emerging economies. Key reasons behind the low returns, and losses, faced by the farmers include the inherent uncertainty in agriculture, unaffordability of advanced technologies, and lack of access to markets. This dissertation formulates and attempts to, at least partially solve, a few of these problems in agriculture, using artificial intelligence and game theory techniques. Novel solutions are proposed that assist the farmers and the state administration during various stages of the agricultural crop cycle, starting from the pre-sowing and sowing decisions and going right up to the harvesting of the produce. These solutions are: PREPARE (Prediction of Prices in Agriculture), ACRE (Agricultural Crop Recommendation Engine), CROP-S (Crop Planning System), and PROMISE (Procurement Mechanisms for Agricultural Inputs and Services).
PREPARE: Accurate prediction of agricultural crop prices is a crucial input for decision-making by various stakeholders in agriculture: farmers, consumers, retailers, wholesalers, and the Government. PREPARE accurately predicts crop prices using historical price information, climatic conditions, soil type, location, and other key determinants. The proposed approach uses graph neural networks (GNNs) in conjunction with a standard convolutional neural network (CNN) model to exploit geospatial dependencies in prices. PREPARE works well with noisy legacy data and produces a performance that is at least 20% better than the state-of-the-art results in the literature.
ACRE: A key challenge faced by small and marginal farmers is to determine which crops to grow to maximize their utility. ACRE provides a rigorous, data-driven back-end for designing farmer-friendly mobile applications for assisting farmers in choosing crops. ACRE uses available data such as soil characteristics, weather conditions, and historical yield data, and uses machine learning/deep learning models to compute an estimated utility to the farmer. The main idea of ACRE is to generate several recommendations of portfolios of crops, with a ranking of portfolios based on the Sharpe ratio, a popular risk metric used for evaluating financial investments.
CROP-S: To minimize supply-demand mismatch and maximize the profits of the farmers, the Government or state administration can use CROP-S for district level agricultural crop planning. CROP-S uses data about predicted demands, transportation costs, compliance ratios (fraction of farmers who will follow the recommended crop plan), and historical data about yields and prices to arrive at an optimal allocation of crop acreages (number of acres cultivated under each crop) to districts.
PROMISE: Procuring agricultural inputs such as seeds, fertilizers, and pesticides, at desired quality levels and at affordable cost, forms a critical component of agricultural input operations. Farmer Producer Organisations (FPOs) or Farmer collectives (FCs), which are cooperative societies of farmers, offer an excellent opportunity for enabling cost-effective procurement of inputs with assured quality to the farmers. They take advantage of economies of scale to ensure that the farmers get good quality inputs at lower prices. The objective of PROMISE is to design sound, explainable mechanisms by which an FC will be able to procure agricultural inputs in bulk and distribute the inputs procured to the individual farmers who are members of the FC. In the methodology proposed, an FC engages qualified suppliers in a competitive, volume discount procurement auction in which the suppliers specify price discounts based on volumes supplied. The desiderata of properties for such an auction include: minimization of the total cost of procurement, incentive compatibility, individual rationality, social welfare maximization, fairness, and satisfying certain practical, business constraints. An auction satisfying all these properties is analytically infeasible. PROMISE uses a novel deep learning based approach to design an auction that satisfies all of these properties, except social welfare maximization, in a regret minimization sense.
The suite of AI based and game theory based solutions offered in this thesis, namely PREPARE, CROP-S, ACRE, and PROMISE, constitute a bouquet of innovative approaches towards mitigating the problems faced by small and marginal farmers in emerging economies.National Bank for Agriculture and Rural Development, Minister of Educatio
Evaluation of Cytogenotoxic Potential and Embryotoxicity of KRS Cauvery River Water in Zebrafish (Danio Rerio)
No full textPollutants and other forms of environmental stress (lifestyle and social behaviour) are of global concern due to significant adverse effects on human health. The term "exposome" has emerged as a concept in environmental health sciences, including environmental epidemiology, exposure science, and toxicology. It is the composite of an individual's lifetime exposures and how those exposures relate to health. A major source of individual exposure to the external environment, either directly or indirectly, is via drinking water since most pollutants in the air and soil end up in water bodies, including rivers. In India, one of the major rivers that receive different wastes is the Cauvery River (CR). The Cauvery River, an interstate river, flows eastward from Karnataka through Tamil Nadu and drains into the Bay of Bengal, providing potable water for over 150 million humans and animals and has long-sustained fishing and irrigation. However, indiscriminate discharge of waste into the river water causes unexplained health hazards to human and other animal species, like skeletal deformity and dwindling numbers of fish species in the river. However, in detail, the health hazard impacts of the Cauvery water have not been investigated so far. To investigate this phenomenon, we analyzed the biological, physical, and chemical parameters as well as microplastics present in the CR water and then evaluated the toxicity effects on the zebrafish (Danio rerio) model.
Zebrafish offers many advantages as a research model, including rapid development, optical transparency, a large number of offspring, and an excellent vertebrate model for toxicological research. We treated the zebrafish with KRS-CR water samples collected from three stations (fast-flowing water [X], slow-flowing [Y], and stagnant [Z] water), before and after filtration.
Firstly, we detected microscopic organisms (MO) such as Cyclops, Daphnia, Spirogyra,
Spirochaeta, and total coliform (Escherichia coli), which are bioindicators of water pollution present in the samples. All physicochemical parameters analyzed, including heavy metals before and after filtration of the water with Millipore filter paper (0.45 μm), were within the acceptable limits set by standard organizations, except for decreased dissolved oxygen (DO), and increased biochemical oxygen demand (BOD), and chemical oxygen demand (COD), which are indicators of hypoxic water conditions. We also identified the presence of microplastics (polybutene (≤ 15 μm), polyisobutene (≤ 20 μm), and polymethylpentene (≤ 3mm) as well as cyclohexyl functional group in CR water samples. Zebrafish embryos treated with the water samples, both before and after filtration, exert the same cytogenotoxic effects by inducing increased reactive oxygen species (ROS) production, which triggers subcellular organelle dysfunctions, DNA damage, apoptosis, pericardial oedema, skeletal deformities, and increased mortality. As a result, we observed that both water samples and zebrafish larvae had significantly less oxygen availability, due to the presence of plastic materials (polyisobutylene).
Plastic pollution has become a serious global concern. The plastic waste is broken down into minute particles known as microplastics (MPs) and released as granules, pellets, and/or powders, influencing biosystems. 'Microplastic' is a term for plastic particles without a universally established definition. In the literature, microplastic is often defined as plastic particles up to 5 mm in dimensions with no defined lower size limit. Among the three types of MPs observed in this study, we discovered that the concentration of polyisobutylene (PIB) (<10 μg/mL) was higher than that of the other MPs particles identified in the CR. Since the mechanism of polyisobutylene's toxicological effects is unknown, we synthesized, characterized, and determined the toxicity effects and accumulation of polyisobutylene (PIB) in zebrafish. Using the solvent evaporation method, we synthesized pristine and fluorescence PIB-MPs with particle sizes of < 2-10 μm. The PIB Raman peak (715.942 cm-1) and FTIR characterization tests showed that the samples have notable peaks at 1366 and 1388 wavenumber (cm-1), and zeta potential of approximately -40mV to -60 mV, indicating the inherent stability of the suspensions. Zebrafish larvae exposed to various concentrations (low and high concentrations) of PIB-MP showed reduced swimming and hyperactivity, delayed hatching, increased ROS, and changes in mRNA levels of genes (mnsod, cu/znsod, gsr, and gstp1) encoding antioxidant proteins. Interestingly, we observed that the PIB-MP accumulated in all three gut regions (proximal intestine, middle intestine, and distal intestine) of both larvae and adult fish within 7 to 21 days, respectively. Histopathological examination of the gut revealed increased vacuolation as well as damage to the intestinal mucosa. The immunohistochemistry results showed an enhanced expression of two proinflammatory cytokines (TNF-α and IL-18) in the gut and tail regions of treated fish, which ultimately led to an increase in apoptosis. The build-up of these PIB particles generates adverse consequences in zebrafish larvae and adults. The most frequent phenotypic manifestation we found was skeletal abnormalities, which ultimately led to higher mortality. Our findings show that KRS-CR water can cause cytogenotoxic and embryotoxic defects in zebrafish due to hypoxic water conditions triggered by the PIB microplastic influx. The present study, with its comprehensive analysis of biological and physicochemical parameters in Cauvery River water, offers valuable insights for the evaluation of environmental health hazards. By identifying the presence of microplastics in the river, the study highlights the potential risks posed by this specific microplastic (PIB-MP) to the environment and human health. The cytogenotoxic and embryotoxic effects observed in the zebrafish highlight the potentially hazardous nature of the water, indicating a need for further investigation and implementation of appropriate mitigation measures. Such information is crucial for policymakers, regulatory bodies, and/or environmental agencies as it provides a scientific basis for developing effective strategies and interventions to mitigate the adverse impacts of microplastics in river water. The findings can help in designing targeted and efficient river water treatment strategies, aiming to reduce microplastic contamination and ensure the provision of safe and clean water resources for communities and ecosystems in other to protect the health of both aquatic organisms, animals, and human populations dependent on the river water for various purposes.Department of Biotechnology, Government of India (DBT) and The World Academic of Science (TWAS), Italy postgraduate fellowship (FR number 3240300004
Renormalization Group Summation at High Orders and Implications to the Determination of Some Standard Model Parameters
No full textIn perturbation theory, predictions from theories like Quantum Chromodynamics (QCD)
are obtained by evaluating Feynman diagrams to high orders. Such calculations for re sults for various processes are already available in the literature, and their theoretical
predictions depend on various parameters. With the availability of a large amount of
data from experiments, it is possible to extract these parameters by comparing theoretical
predictions with data. However, due to the finite order terms available from theory, any
parameter determination depends on the perturbative scheme used and the choice of the
renormalization scale. Once a renormalization scheme is fixed, the variation of the renor malization scale in a certain range can lead to large uncertainties, and optimizing pertur bative series with respect to such free parameters is necessary. We have achieved such op timization using the renormalization group summed perturbation theory (RGSPT), and the resulting perturbative series is significantly less sensitive to the renormalization scale
dependence. It is a renormalization group (RG) improved version of the fixed order per turbation theory (FOPT), where the running RG-logarithms are summed to all orders
using the RG equation. Once these running logarithms are summed, various operations
such as analytic continuation, contour integrals, and Borel-Laplace transform are found
to have enhanced convergence and scale variation improvement compared to a FOPT
analysis. These operations are important in the precision determination of pQCD param eters using methods such as QCD sum rules
Flavivirus RNA replication: Probe development, structural dynamics, and role of zinc ions.
No full textFlaviviruses share a typical genome architecture where the highly conserved UTRs flank a central coding region. They also share a common genome replication strategy called genome cyclization where the UTRs interact to form a long-range, dynamic, 3D RNA interactome. Recent studies focused on the involvement of the capsid coding region in modulating these UTR interactions. Along similar lines, we have investigated the effect of CCR on the UTRs interactions in Dengue using ensemble FRET with cyanine dye-labeled Dengue UTRs. As a part of this study, we have developed a novel, generic chemoenzymatic, bead-based method for base-specific modification of RNA called “T7 RNA polymerase extension-based RNA modification (TERM)”. Here, we describe TERM development, demonstrate the synthesis of single, site-specific cyanine dye-labeled Dengue UTRs and discuss the UTR interaction studies performed using the TERM-synthesized cyanine dye-labeled UTRs. Our results bridge the knowledge gap in understanding the role of the capsid coding region in Flavivirus UTRs
Capacity Computation and Coding for Input-Constrained Channels
No full textThe setting of the transmission of information over noisy, binary-input, memoryless channels is today well-understood, owing to the work of several information theorists, beginning with Claude Shannon. It is known that it is impossible to transmit information reliably over such channels at rates larger than the fundamental limit that is the capacity of the channel. Moreover, progress made in the last three decades has led to the construction of explicit, practically-implementable coding schemes that achieve rates arbitrarily close to the capacities of such channels. Now, suppose that the inputs of the memoryless channel are required to obey an additional constraint, which stems from physical limitations of the medium over which transmission or storage occurs. What then can be said about the fundamental limits of information transmission over such input-constrained channels, with and without decoder feedback? Is it possible to design good constrained coding schemes of high rate over these channels? If the channel introduces errors adversarially, instead of randomly, how much information can then be sent through, reliably? This dissertation explores answers to such questions.
We first derive computable lower bounds on the capacities of runlength limited (RLL) input-constrained memoryless channels, such as the binary symmetric and binary erasure channels (BSC and BEC, respectively), by considering random Markov input distributions that respect the constraint. These bounds unify well-known approaches in the literature, and extend them to the so-called input-driven finite-state channels (FSCs). For the special case of the BEC with a no-consecutive-ones input constraint, we discuss an iterative stochastic approximation algorithm that numerically computes achievable rates that are very close to known upper bounds on the capacity of the channel. We also derive improved analytical lower bounds, for this specific channel.
Next, we consider the special case of the -runlength limited (RLL) constraint, which mandates that any pair of successive s be separated by at least s. We design explicit coding schemes, derived from Reed-Muller (RM) codes, for transmission over binary-input memoryless symmetric (BMS) channels, whose inputs respect the constraint. In particular, we provide constructions using constrained subcodes of RM codes, analytically compute their rates, and derive converse upper bounds on the rates of the largest constrained subcodes of RM codes. We also provide a Fourier-theoretic perspective on the problem of counting arbitrarily-constrained codewords in general linear codes, which can help estimate the rates achievable by using linear codes over input-constrained BMS channels. We illustrate the utility of our method using the somewhat surprising observation that for different constraints of interest, the Fourier transforms of the indicator functions of the constraints are efficiently computable.
We then shift our attention to the setting of the -RLL input-constrained BEC in the presence of noiseless feedback from the decoder. We demonstrate a simple, labelling-based, zero-error feedback coding scheme, which we prove to be feedback capacity-achieving, and, as a by-product, obtain an explicit characterization of the feedback capacity. The feedback capacity thus computed is an upper bound on the non-feedback capacity of such a channel. Numerical comparisons made with upper bounds on the non-feedback capacity then reveal that that feedback increases the capacity of such a channel, at least for select values of .
Finally, we consider the setting of an input-constrained adversarial channel, where there is an upper bound on the number of bit-flip errors that the channel can introduce, and we seek to design codes that can be recovered with zero error. We present numerical upper bounds on the sizes of the largest such codes, via a version of Delsarte’s linear program. We observe that for different constraints of interest, our upper bounds beat the “generalized sphere packing bounds” that are the state-of-the-art.Prime Minister's Research Fellowship, Qualcomm Innovation Fellowship Indi
Strain engineering of 2D NEMS for resonant sensing
No full text2D material-based nanoelectromechanical systems have emerged as excellent tools for force measurement with extreme sensitivity levels. Most sensing methods with 2D nanoelectromechanical (2D NEMS) systems utilize frequency tuning of the resonant mode in response to external stimuli. However, the interaction of the harsh external stimulus with the delicate 2D NEMS limited these devices’ utility only in the research labs. We propose a fabrication and packaging method for 2D NEMS devices to extend their application outside the research labs. Under the proposed scheme, the 2D NEMS is coupled to the external stimulus through substrate strain. The substrate acts as a protective barrier between the NEMS and the environment. At the same time, the substrate also influences the strain on the 2D NEMS. The external stimulus changes the strain on the substrate and hence on the 2D NEMS device. The strain change on 2D NEMS changes the frequency of vibration modes. 2D materials such as graphene have a high Young’s modulus. High Young’s modulus allows the strain to frequency transductions with high accuracy and sensitivity. We report the most straightforward application of this scheme for pressure sensing with a responsivity of 20Hz/Pa.
Using the proposed scheme, we also demonstrate the ability to utilize duffing nonlinear response of the graphene resonator for pressure sensing. The resonant response of the 2D nanoresonators becomes nonlinear, even at very small excitation voltages. The nonlinear response of the 2D nanoresonators shows sharp amplitude jumps at the bifurcation points and hysteresis. We utilize the sharp amplitude jumps to realize the bifurcation amplifier for pressure sensing. While the hysteresis in the frequency response is used to demonstrate basic logic operations such as OR, AND, and XOR with pressure pulse as input and vibration amplitude as output.
The external stimulus can also have a dynamic variation that can excite the substrate’s vibration modes. In this case, the frequency tuning of the 2D NEMS is also dynamic as it follows the strain on the substrate. Utilizing this principle, we report the ability of the 2D NEMS to track the dynamic stimulus with a frequency component as high as 40kHz. Characterizing time-varying stimuli is crucial for accelerometers, acoustic sensors, and vibrometers. We demonstrate the use of highly responsive 2D nanoresonators for such dynamic sensing.
Since the proposed 2D NEMS package allows external stimulus to couple to the 2D NEMS efficiently, the 2D NEMS is also susceptible to various environmental noise sources. We use the Allan Deviation of the frequency fluctuations to study the performance of these devices against noise. The measurements reveal that the primary cause of the frequency fluctuations of the 2D NEMS is the temperature of the surrounding air. These measurements provide crucial insights into designing a sensor with the required sensitivity, bandwidth and noise isolation. The barrier-substrate design can be changed according to specific applications to achieve the intended transduction. This concept can be extended easily for sensing inertial forces, biological stimuli, and temperature