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Detecting electronic hot spots is important for understanding the heat dissipation and thermal management of electronic and semiconductor devices. Optical thermoreflective imaging is being used to perform precise temporal and spatial imaging of heat on wires and semiconductor materials. We apply quantum squeezed light to perform thermoreflective imaging on micro-wires, surpassing the shot-noise limit of classical approaches. We obtain a far-field temperature sensing accuracy of 42 mK after 50 ms of averaging and show that a $256\times256$ pixel image can be constructed with such sensitivity in 10 minutes. We can further obtain single-shot temperature sensing of 1.6 K after only 10 $\mathrm{\mu s}$ of averaging enabling dynamical study of heat dissipation. Not only do the quantum images provide accurate spatio-temporal information about heat distribution, but the measure of quantum correlation provides additional information, inaccessible by classical techniques, that can lead to a better understanding of the dynamics. We apply the technique to both Al and Nb microwires and discuss the applications of the technique in studying electron dynamics at low temperatures.

Weather and soil conditions are particularly important when it comes to farming activities. Study of these factors and their role in nutrient and nitrate absorption rates can lead to useful insights with benefits for both the crop yield and the protection of the environment through the more controlled use of fertilizers and chemicals. There is a paucity of public data from rural, agricultural sensor networks. This is partly due to the unique challenges faced during the deployment and maintenance of IoT networks in rural agricultural areas. As part of a 5-year project called WHIN we have been deploying and collecting sensor data from production and experimental agricultural farms in and around Purdue University in Indiana. Here we release a dataset comprising soil sensor data from a representative sample of 3 nodes across 3 production farms, each for 5 months. We correlate this data with the weather data and draw some insights about the absorption of rain in the soil. We provide the dataset at: https://purduewhin.ecn.purdue.edu/dataset2021.

In this work, we demonstrate atomic-layer-deposited (ALD) single-channel indium oxide (In2O3) gate-all-around (GAA) nanoribbon FETs in a back-end-of-line (BEOL) compatible process. A maximum on-state current (ION) of 19.3 mA/{\mu}m (near 20 mA/{\mu}m) is achieved in an In2O3 GAA nanoribbon FET with a channel thickness (TIO) of 3.1 nm, channel length (Lch) of 40 nm, channel width (Wch) of 30 nm and dielectric HfO2 of 5 nm. The record high drain current obtained from an In2O3 FET is about one order of magnitude higher than any conventional single-channel semiconductor FETs. This extraordinary drain current and its related on-state performance demonstrate ALD In2O3 is a promising oxide semiconductor channel with great opportunities in BEOL compatible monolithic 3D integration.

The recent advancement of the Internet of Things (IoT) enables the possibility of data collection from diverse environments using IoT devices. However, despite the rapid advancement of low-power communication technologies, the deployment of IoT networks still faces many challenges. In this paper, we propose a hybrid, low-power, wide-area network (LPWAN) structure that can achieve wide-area communication coverage and low power consumption on IoT devices by utilizing both sub-GHz long-range radio and 2.4 GHz short-range radio. Specifically, we constructed a low-power mesh network with LoRa, a physical-layer standard that can provide long-range (kilometers) point-to-point communication using custom time-division multiple access (TDMA). Furthermore, we extended the capabilities of the mesh network by enabling ANT, an ultra-low-power, short-range communication protocol to satisfy data collection in dense device deployments. Third, we demonstrate the performance of the hybrid network with two real-world deployments at the Purdue University campus and at the university-owned farm. The results suggest that both networks have superior advantages in terms of cost, coverage, and power consumption vis-\`a-vis other IoT solutions, like LoRaWAN.

Decades of continuous scaling has reduced the energy of unit computing to virtually zero, while energy-efficient communication has remained the primary bottleneck in achieving fully energy-autonomous IoT nodes. This paper presents and analyzes the trade-offs between the energies required for communication and computation in a wireless sensor network, deployed in a mesh architecture over a 2400-acre university campus, and is targeted towards multi-sensor measurement of temperature, humidity and water nitrate concentration for smart agriculture. Several scenarios involving In-Sensor-Analytics (ISA), Collaborative Intelligence (CI) and Context-Aware-Switching (CAS) of the cluster-head during CI has been considered. A real-time co-optimization algorithm has been developed for minimizing the energy consumption in the network, hence maximizing the overall battery lifetime of individual nodes. Measurement results show that the proposed ISA consumes ~467X lower energy as compared to traditional Bluetooth Low Energy (BLE) communication, and ~69,500X lower energy as compared with Long Range (LoRa) communication. When the ISA is implemented in conjunction with LoRa, the lifetime of the node increases from a mere 4.3 hours to 66.6 days with a 230 mAh coin cell battery, while preserving more than 98% of the total information. The CI and CAS algorithms help in extending the worst-case node lifetime by an additional 50%, thereby exhibiting an overall network lifetime of ~104 days, which is >90% of the theoretical limits as posed by the leakage currents present in the system, while effectively transferring information sampled every second. A web-based monitoring system was developed to archive the measured data in a continuous manner, and to report anomalies in the measured data., Comment: 15 pages with author info, 18 figures

In this article, we show how relativistic alpha stable processes can be used to explain quasi-ballistic heat conduction in semiconductors. This is a method that can fit experimental results of ultrafast laser heating in alloys. It also provides a connection to a rich literature on Feynman-Kac formalism and random processes that transition from a stable L\'evy process on short time and length scales to the Brownian motion at larger scales. This transition was captured by a heuristic truncated L\'evy distribution in earlier papers. The rigorous Feynman-Kac approach is used to derive sharp bounds for the transition kernel. Future directions are briefly discussed.

High performance thermoelectric materials for wide-range temperature applications still remains a challenge. In this study, we have produced high-quality homogeneous $In_{0.32}Ga_{0.68}N$ on ZnO substrates, with no phase separation at high Indium content, using metal organic chemical vapor deposition for thermoelectric applications. A record high room temperature figure of merit zT is obtained of 0.86, which is five times larger than that of SiGe, the current state of the art high temperature thermoelectric material. These materials are shown to have a nearly perfect doping concentration to maximize zT regardless of the scattering mechanism. This almost one order of magnitude increase in zT is due to large electrical conductivities from oxygen co-doping as well as low thermal conductivities from alloy scattering. The maximum power factor reached was $77.98x10^{-4} W/mK^{2}$ at 300K for $In_{0.32}Ga_{0.68}N$ alloys at a carrier concentration $~6.25x10^{20} cm^{-3}$. This work indicates that $In_{x}Ga_{1-x}N$ alloys have great potential for thermoelectric applications especially at a high temperature range.

Infrared (IR) imaging has become a viable tool for visualizing various chemical bonds in a specimen. The performance, however, is limited in terms of spatial resolution and imaging speed. Here, instead of measuring the loss of the IR beam, we utilize a pulsed visible light for a high-throughput, widefield sensing of the transient photothermal effect induced by absorption of single mid-IR pulses. To extract such transient signals, we built a virtual lock-in camera synchronized to the visible probe and IR light pulses with precisely-controlled delays, allowing sub-microsecond temporal resolution determined by the probe pulse width. Our widefield photothermal sensing (WPS) microscope enabled chemical imaging at a speed up to 1250 frames per second, with high spectral fidelity, and offering sub-micron spatial resolution. With the capability of imaging living cells and nanometer-scale polymer films, WPS microscopy opens a new way for high-throughput characterization of biological and material specimens., Comment: 24 pages, 6 figures

The self-heating effect is a severe issue for high-power semiconductor devices, which degrades the electron mobility and saturation velocity, and also affects the device reliability. On applying an ultrafast and high-resolution thermoreflectance imaging technique, the direct self-heating effect and surface temperature increase phenomenon are observed on novel top-gate \b{eta}-Ga2O3 on insulator field-effect transistors. Here, we demonstrate that by utilizing a higher thermal conductivity sapphire substrate rather than a SiO2/Si substrate, the temperature rise above room temperature of \b{eta}-Ga2O3 on the insulator field-effect transistor can be reduced by a factor of 3 and thereby the self-heating effect is significantly reduced. Both thermoreflectance characterization and simulation verify that the thermal resistance on the sapphire substrate is less than 1/3 of that on the SiO2/Si substrate. Therefore, maximum drain current density of 535 mA/mm is achieved on the sapphire substrate, which is 70% higher than that on the SiO2/Si substrate due to reduced self-heating. Integration of \b{eta}-Ga2O3 channel on a higher thermal conductivity substrate opens a new route to address the low thermal conductivity issue of \b{eta}-Ga2O3 for power electronics applications.

The so-called Boltzmann Tyranny defines the fundamental thermionic limit of the subthreshold slope (SS) of a metal-oxide-semiconductor field-effect transistor (MOSFET) at 60 mV/dec at room temperature and, therefore, precludes the lowering of the supply voltage and the overall power consumption. Adding a ferroelectric negative capacitor to the gate stack of a MOSFET may offer a promising solution to bypassing this fundamental barrier. Meanwhile, two-dimensional (2D) semiconductors, such as atomically thin transition metal dichalcogenides (TMDs) due to their low dielectric constant, and ease of integration in a junctionless transistor topology, offer enhanced electrostatic control of the channel. Here, we combine these two advantages and demonstrate for the first time a molybdenum disulfide (MoS2) 2D steep slope transistor with a ferroelectric hafnium zirconium oxide layer (HZO) in the gate dielectric stack. This device exhibits excellent performance in both on- and off-states, with maximum drain current of 510 {\mu}A/{\mu}m, sub-thermionic subthreshold slope and is essentially hysteresis-free. Negative differential resistance (NDR) was observed at room temperature in the MoS2 negative capacitance field-effect-transistors (NC-FETs) as the result of negative capacitance due to the negative drain-induced-barrier-lowering (DIBL). High on-current induced self-heating effect was also observed and studied., Comment: 23 pages, 14 figures

We have demonstrated that depletion/enhancement-mode b-Ga2O3 on insulator field-effect transistors can achieve a record high drain current density of 1.5/1.0 A/mm by utilizing a highly doped b-Ga2O3 nano-membrane as the channel. b-Ga2O3 on insulator field-effect transistor (GOOI FET) shows a high on/off ratio of 1010 and low subthreshold slope of 150 mV/dec even with 300 nm thick SiO2. The enhancement-mode GOOI FET is achieved through surface depletion. An ultra-fast, high resolution thermo-reflectance imaging technique is applied to study the self-heating effect by directly measuring the local surface temperature. High drain current, low Rc, and wide bandgap make the b-Ga2O3 on insulator field-effect transistor a promising candidate for future power electronics applications.

Suitably superimposed grey-medium solutions of the Boltzmann transport equation (BTE) provide a simple yet accurate description of non-grey quasiballistic heat conduction in transient thermal grating experiments. Recent applications of similar strategies based on kinetic and McKelvey-Schockley-Landauer theory to time-periodic transport predicted notable conductivity suppression only at heating frequencies comparable to phonon scattering rates, in contrast to lengthscale criteria observed by several prior studies. Here we show that the frequency-integrated grey-medium approximation (FIGMA) is ill suited to tackle temporally periodic quasiballistic transport. Starting from first-principles phonon dispersions and scattering rates, we obtain semi-analytic 1D BTE solutions for semi-infinite structures subjected to sinusoidal surface heating and compare these to the approximate model counterparts. We find FIGMA-based approaches to overestimate the semiconductor surface temperature by up to one and characteristic heating frequencies for onset of quasiballistic effects by up to three orders of magnitude respectively. Our study reasserts that experimentally observed heating-frequency dependent apparent conductivities originate in the overlap of the characteristic length scale of the thermal gradient with phonon mean free paths.

Anomalous diffusion constitutes a relation between tracer flux and tracer density gradient that is inherently nonlocal in space and/or time. Previous studies emphasize the non-Gaussian character of the tracer distribution that arises from adjusted constitutive relations but did not investigate the flux-gradient memory itself. Here, we present a universal analytic framework that enables systematic characterisation of nonlocality in a wide variety of transport regimes. A generalised diffusivity kernel $D^{\ast}$ fully embodies the spatiotemporal flux memory with respect to the gradient. An extension of the flux-gradient relation for subdiffusive transport is also proposed. Several conservation and invariance properties can be deduced, including that Poissonian flight processes have no flux memory in time while fractional time diffusion has no flux memory in space. We derive analytical expressions for $D^{\ast}(x,t)$ in several types of anomalous transport dynamics that are commonly encountered in practice, being fractional diffusion equations, tempered L\'evy superdiffusion, and tempered fractional time diffusion. This detailed knowledge of the shape and nature of the flux memory, and the corresponding length and time scales over which nonlocal effects are physically important, remain completely hidden in conventional analyses based on tracer distributions or flux-gradient diagrams. Practical capabilities include the interpretation of microscale heat superdiffusion experiments. Overall, the theory can serve as a valuable framework for anomalous transport dynamics across multiple disciplines.

Thermal transport at short length and time scales inherently constitutes a nonlocal relation between heat flux and temperature gradient, but this is rarely addressed explicitly. Here, we present a formalism that enables detailed characterisation of the delocalisation effects in nondiffusive heat flow regimes. A convolution kernel $\kappa^{\ast}$, which we term the nonlocal thermal conductivity, fully embodies the spatiotemporal memory of the heat flux with respect to the temperature gradient. Under the relaxation time approximation, the Boltzmann transport equation formally obeys the postulated constitutive law and yields a generic expression for $\kappa^{\ast}$ in terms of the microscopic phonon properties. Subsequent synergy with stochastic frameworks captures the essential transport physics in compact models with easy to understand parameters. A fully analytical solution for $\kappa^{\ast}(x')$ in tempered L\'evy transport with fractal dimension $\alpha$ and diffusive recovery length $x_{\text{R}}$ reveals that nonlocality is physically important over distances $\sqrt{2-\alpha} \,\,x_{\text{R}}$. This is not only relevant to quasiballistic heat conduction in semiconductor alloys but also applies to similar dynamics observed in other disciplines including hydrology and chemistry. We also discuss how the previously introduced effective thermal conductivity $\kappa_{\text{eff}}$ inferred phenomenologically by transient thermal grating and time domain thermoreflectance measurements relates to $\kappa^{\ast}$. Whereas effective conductivities depend on the experimental conditions, the nonlocal thermal conductivity forms an intrinsic material property. Experimental results indicate nonlocality lengths of 400$\,$nm in Si membranes and $\simeq 1\,\mu$m in InGaAs and SiGe, in good agreement with typical median phonon mean free paths.

Nearly all experimental observations of quasi-ballistic heat flow are interpreted using Fourier theory with modified thermal conductivity. Detailed Boltzmann transport equation (BTE) analysis, however, reveals that the quasi-ballistic motion of thermal energy in semiconductor alloys is no longer Brownian but instead exhibits L\'evy dynamics with fractal dimension $\alpha < 2$. Here, we present a framework that enables full 3D experimental analysis by retaining all essential physics of the quasi-ballistic BTE dynamics phenomenologically. A stochastic process with just two fitting parameters describes the transition from pure L\'evy superdiffusion as short length and time scales to regular Fourier diffusion. The model provides accurate fits to time domain thermoreflectance raw experimental data over the full modulation frequency range without requiring any `effective' thermal parameters and without any a priori knowledge of microscopic phonon scattering mechanisms. Identified $\alpha$ values for InGaAs and SiGe match ab initio BTE predictions within a few percent. Our results provide experimental evidence of fractal L\'evy heat conduction in semiconductor alloys. The formalism additionally indicates that the transient temperature inside the material differs significantly from Fourier theory and can lead to improved thermal characterization of nanoscale devices and material interfaces.

Semiconductor alloys exhibit a strong dependence of effective thermal conductivity on measurement frequency. So far this quasi-ballistic behaviour has only been interpreted phenomenologically, providing limited insight into the underlying thermal transport dynamics. Here, we show that quasi-ballistic heat conduction in semiconductor alloys is governed by L\'evy superdiffusion. By solving the Boltzmann transport equation (BTE) with ab initio phonon dispersions and scattering rates, we reveal a transport regime with fractal space dimension $1 < \alpha < 2$ and superlinear time evolution of mean square energy displacement $\sigma^2(t) \sim t^{\beta} (1 < \beta < 2)$. The characteristic exponents are directly interconnected with the order $n$ of the dominant phonon scattering mechanism $\tau \sim \omega^{-n} (n>3)$ and cumulative conductivity spectra $\kappa_{\Sigma}(\tau;\Lambda)\sim (\tau;\Lambda)^{\gamma}$ resolved for relaxation times or mean free paths through simple relations $\alpha = 3-\beta = 1 + 3/n = 2 - \gamma$. The quasi-ballistic transport inside alloys is no longer governed by Brownian motion, but instead dominated by L\'evy dynamics. This has important implications for the interpretation of thermoreflectance (TR) measurements with modified Fourier theory. Experimental $\alpha$ values for InGaAs and SiGe, determined through TR analysis with a novel L\'evy heat formalism, match ab initio BTE predictions within a few percent. Our findings lead to a deeper and more accurate quantitative understanding of the physics of nanoscale heat flow experiments.

A recently developed Shastry's formalism for energy transport is used to analyze the temporal and spatial behaviors of the energy and heat transport in metals under delta function excitation at the surface. Comparison with Cattaneo's model is performed. Both models show the transition between nonthermal (ballistic) and thermal (ballistic-diffusive) regimes. Furthermore, because the new model considers the discrete character of the lattice, it highlights some new phenomena such as damped oscillations in the energy transport both in time and space. The energy relaxation of the conduction band electrons in metals is considered to be governed by the electron-phonon scattering, and the scattering time is taken to be averaged over the Fermi surface. Using the new formalism, one can quantify the transfer from nonthermal modes to thermal ones as energy propagates in the material and it is transformed into heat. While the thermal contribution shows a wave-front and an almost exponentially decaying behavior with time, the nonthermal part shows a wave-front and a damped oscillating behavior. Two superimposed oscillations are identified; a fast oscillation that is attributed to the nonthermal nature of energy transport at very short time scales and a slow oscillation that describes the nature of the transition from the nonthermal regime to the thermal regime of energy transport., Comment: 60pages, 2 tables and 11 figures

The observation of pure phonon confinement effect in germanium nanowires is limited due to the illumination sensitivity of Raman spectra. In this paper we measured Raman spectra for different size germanium nanowires with different excitation laser powers and wavelengths. By eliminating the local heating effect, the phonon confinement effect for small size nanowires was clearly identified. We have also fitted the Raman feature changes to estimate the size distribution of nanowires for the first time., Comment: 11 pages,15 figures

A modified algorithm is proposed to include Pauli exclusion principle in Monte-Carlo simulations. This algorithm has significant advantages to implement in terms of simplicity, speed and memory storage. We show that even in moderately high applied fields, one can estimate electronic distribution with a shifted Fermi sphere without introducing significant errors. Furthermore, the free-flights must be coupled to state availability constraints; this leads to substantial decrease in carrier heating at high fields. We give the correct definition for electronic temperature and show that in high applied fields, the quasi Fermi level is valley dependent. The effect of including Pauli exclusion principle on the band profile; electronic temperature and quasi Fermi level for inhomogeneous case of a single barrier heterostructure is illustrated.

In this manuscript, we solve a nonlinear optimization problem in the study of maximizing cooling temperature using inhomogeneous thermoelectric materials.

The Monte Carlo technique is used to calculate electrical as well as thermoelectric transport properties across thin film heterostructures. We study a thin InGaAsP barrier layer sandwiched between two InGaAs contact layers, when the barrier thickness is in 50nm-2000nm range. We found that with decreasing size, the effective Seebeck coefficient is increased substantially. The transition between pure ballistic thermionic transport and fully diffusive thermoelectric transport is also described.

Thermoelectric properties of a nanocontact made of two capped single wall nanotubes (SWNT) are calculated within the tight-binding approximation and Green's function method. It is found that semiconducting nanotubes can have high Seebeck coefficient very near the actual Fermi energy. This in turn leads to very high figures of merit easily exceeding one. Modifying the properties by shifting the chemical potential can be achieved by doping or application of a (nano-)gate voltage. The presence of impurities near the contact also strongly modify the properties and this can be taken advantage of, in order to design devices with high thermopower and figures of merit., Comment: 12 pages 6 figures