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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Xyce Case Study

With the elimination of underground nuclear testing and declining defense budgets, science-based stockpile stewardship requires increased reliance on high performance modeling and simulation of weapon systems. Today's weapon systems are comprised of various electrical components and systems. As a result, there is a need for tools that will allow the use of massively parallel modeling and simulation techniques on high performance computers in existing and future weapons' electrical systems models. The Xyce Parallel Electronic Simulator is a SPICE (Simulation Program with Integrated Circuit Emphasis)- compatible circuit simulator designed to run on large-scale parallel computing platforms, though it can also execute efficiently on a variety of architectures including single processor workstations. As a mature platform for large-scale parallel circuit simulation, Xyce supports standard capabilities available in commercial simulators, in addition to various devices and models specific to Sandia's needs. Specifically, Xyce aids in the design and verification of electrical and electronic circuits and systems prior to weapons' manufacturing and deployment.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Energy Efficient Streaming Time Series Classification with Attentive Power Iteration

Efficiently processing time series data streams in real-time on resource-constrained devices offers significant advantages in terms of enhanced computational energy efficiency and reduced time-related risks. We introduce an innovative streaming time series classification network that utilizes attentive power iteration, enabling real-time processing on resource-constrained devices. Our model continuously updates a compact representation of the entire time series, enhancing classification accuracy while conserving energy and processing time. Notably, it excels in streaming scenarios without requiring complete time series access, enabling swift decisions. Experimental results show that our approach excels in classification accuracy and energy efficiency, with over 70% less consumption and threefold faster task completion than benchmarks. This work advances real-time responsiveness, energy conservation, and operational effectiveness for constrained devices, contributing to optimizing various applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Intrinsically stretchable electrode array enabled in vivo electrophysiological mapping of atrial fibrillation at cellular resolution

Electrophysiological mapping of chronic atrial fibrillation (AF) at high throughput and high resolution is critical for understanding its underlying mechanism and guiding definitive treatment such as cardiac ablation, but current electrophysiological tools are limited by either low spatial resolution or electromechanical uncoupling of the beating heart. To overcome this limitation, here we introduce a scalable method for fabricating a tissue-like, high-density, fully elastic electrode (elastrode) array capable of achieving real-time, stable, cellular level-resolution electrophysiological mapping in vivo. Testing with acute rabbit and porcine models, the device is proven to have robust and intimate tissue coupling while maintaining its chemical, mechanical, and electrical properties during the cardiac cycle. The elastrode array records epicardial atrial signals with comparable efficacy to currently available endocardial-mapping techniques but with 2 times higher atrial-to-ventricular signal ratio and >100 times higher spatial resolution and can reliably identify electrical local heterogeneity within an area of simultaneously identified rotor-like electrical patterns in a porcine model of chronic AF.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Tale of Two Domains: Cyber - Physical

As devices and systems continue to modernize and adopt integrated circuits, the use of cyber technology to deploy an application is the expectation. This deployment through cyber assets brings new cyber risk and cybersecurity is the practice of managing this risk. Cyber-risk is constantly changing due to the speed of technology advancement and the changing quality of the adversary. Cyber-Informed Engineering (CIE) mitigates cyber-risk through engineering controls where as the traditional practice of cybersecurity mitigates cyber-risk through cybersecurity controls. By clearly defining the cyber-physical boundary, engineering controls and cybersecurity controls can clearly demonstrate their complementary nature to provide layered defenses and successfully mitigate cyber-risk through independent controls. In this paper, a layered model of device decomposition of the the cyber-physical boundary is presented to provide clarity where engineering controls are used to reduce cyber-risk within the physics, functional materials, electronic, or integrated circuit layers and where cybersecurity controls are used to reduce cyber-risk within the machine code and application layers. By implementing both traditional cybersecurity controls and engineering controls, a more holistic approach to cybersecurity is achieved in protecting modern devices and systems, as well as a clear awareness in identifying, documenting, and authorizing the system’s cybersecurity protection scheme is achieved.

42 - ENGINEERING↗
DOE OSTI2020

Kinetic effects of self-organization in low-temperature magnetized plasmas (Final Report for DE-SC0019045: 9/1/2018-8/31/2019)

The research goal of this Early Career Research Program project is to advance the science of low temperature magnetized plasmas using first-principles kinetic, e.g., solving the Boltzmann equation, models. A better understanding of the plasma transport properties, such as electrical resistivity and thermal conductivity must be obtained to better control and design magnetized plasma sources. A key physical phenomenon in low-temperature magnetized plasmas is the self-organization of plasma flows, e.g., coherent plasma structures and transition between different discharge modes. Understanding the physics of coherent plasma structures has been identified as one of the four important frontier topics in a recent workshop by the Office of Fusion Energy Science. These self-emerging plasma patterns results from the nonlinear coupling between plasma constituents (ions, electrons, and neutral atoms), electromagnetic fields, and materials. The physics of low-temperature magnetized plasmas is particularly complex because (i) the collisionless instabilities affect collisional phenomena (ionization, transport, etc.) and vice versa and (ii) the presence of materials (sheath, electron injection, etc.) influences the bulk plasma properties in low-temperature plasma (LTP) devices. Computational models of these plasma flows remain challenging because the plasma density can vary several orders of magnitudes, a wide range of temporal and spatial scales must be resolved, the phenomena are inherently three-dimensional, and various physical processes, such as wall interaction, instabilities, inelastic collisions, etc., must be simultaneously and self-consistently taken into account. Understanding the fundamental transport mechanisms in cross-field configurations enables additional controllability of plasma properties and electron energy distribution functions (EEDFs).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Simulating Thermoelectric Devices Using the MOOSE Framework

Thermoelectric generators (TEG) are devices that generate energy by converting heat into electricity or provide cooling via the Peltier effect. This feature of thermoelectric devices originates from the Seebeck, Peltier, Thomson, and Joule heating effects. TEGs can be applied in energy and thermal management systems such as waste heat recovery and refrigeration, respectively. Thermoelectric device design is influenced by the material selection and the device's geometry operating conditions. Therefore, predicting, verifying, and validating thermoelectric device performance using simulations tools is essential to deploying thermoelectric devices in industry. The Multiphysics Object-Oriented Simulation Environment (MOOSE) Framework is an open-source simulation tool capable of modeling simple to complex systems. In this work, we demonstrate MOOSE's thermoelectric device modeling capabilities by simulating a unicouple, module, and exhaust gas recovery system. The Seebeck, Peltier, Thomson, and Joule heating physics are implemented into MOOSE. The MOOSE thermoelectric physics were thoroughly verified and validated using published COMSOL® results and experimental data. In addition, thermoelectric modules were integrated into an exhaust gas recovery system using the MOOSE MultiApp function as a demonstration of the model's ability. The verification and validation results and exhaust gas heat recovery system showcases MOOSE's capability to model thermoelectric devices and integrate these devices into practical energy systems.

42 - ENGINEERING↗
DOE OSTI2020

Moisture-Driven Formation and Growth of Quasi-2-D Organolead Halide Perovskite Crystallites

Ruddlesden–Popper phase quasi-2-D organolead halide perovskites like n-butylammonium methylammonium lead iodide (nBA-MAPI) exhibit improved moisture stability over typical 3-D perovskite materials, making them exciting for use in a variety of applications such as photovoltaic (PV) devices. This improved stability is the result of a unique disproportionation-based degradation mechanism that protects the bulk of the nBA-MAPI from extensive damage through the formation of a protective, low-n surface layer. In addition to this surface layer, nBA-MAPI films also exhibit the dynamic growth of micrometer-scale crystallites and cracks at the surface of the film, unique and potentially important byproducts of quasi-2-D perovskite disproportionation. Here, we present a detailed study of these crystallites using several analytical techniques including photoluminescence spectroscopy (PL), confocal fluorescence microscopy (CFM), atomic force microscopy (AFM) combined with time-of-flight-secondary ion mass spectrometry (ToF-SIMS), and others in an effort to better understand the relationship between material disproportionation and crystallite growth. Our results show that the crystallites form after exposure to humid air and confirm that they are composed of low-n phases of nBA-MAPI. The crystallites are found to extend into the interior of the film and exhibit continued growth while exposed to moisture over 72 h. This growth is accompanied by both a decrease in the bulk 2-D phase and an increase in a 3-D-like phase in the surface PL spectra, indicating that the crystallites are likely a product of moisture-driven disproportionation. Importantly, similar crystallites are also observed to form within model PV devices, indicating that such processes must be accounted for when designing future devices containing materials like nBA-MAPI.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Carrier capture and emission by substitutional carbon impurities in GaN vertical diodes

A model was developed for the operation of a GaN pn junction vertical diode which includes rate equations for carrier capture and thermally activated emission by substitutional carbon impurities and carrier generation by ionizing radiation. The model was used to simulate the effect of ionizing radiation on the charge state of carbon. These simulations predict that with no applied bias, carbon is negatively charged in the n-doped layer, thereby compensating n-doping as experimentally observed in diodes grown by metal-organic chemical vapor deposition. With reverse bias, carbon remains negative in the depletion region, i.e., compensation persists in the absence of ionization but is neutralized by exposure to ionizing radiation. This increases charge density in the depletion region, decreases the depletion width, and increases the capacitance. The predicted increase in capacitance was experimentally observed using a pulsed 70 keV electron beam as the source of ionization. In additional confirming experiments, the carbon charge-state conversion was accomplished by photoionization using sub-bandgap light or by the capture of holes under forward bias.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Iso-cost-performance of thermal energy storage

As thermal energy storage (TES) systems gain increasing recognition as next-generation energy storage solutions, evaluating their techno-economic performance is crucial. This perspective analyzes the cost-performance of latent heat-based TES systems and introduces the concept of iso-cost-performance—maintaining a constant cost per unit energy ($\$$/kWh) despite material degradation. Using an empirical degradation model, we show that after 1200 thermal cycles, the thermal conductivity and volumetric energy density of a paraffin-based phase change material (PCM) decreased by 36.0% and 26.1%, respectively, resulting in a 31.2% reduction in the figure of merit (FOM) and, consequently, the system cost-performance. However, by introducing thermally conductive additives to enhance effective thermal conductivity, the TES system can recover its initial FOM, achieving iso-cost-performance operation. This framework quantitatively demonstrates how degradation-mitigation strategies—such as improving thermal conductivity—can offset material degradations and maintain long-term cost-effectiveness. Beyond PCM-based TES, the proposed FOM-based approach provides a generalized pathway for cost-performance optimization across various TES technologies.

25 ENERGY STORAGE↗
DOE OSTI2024

Modeling and Design of the Triton OWC System (Final Report)

Two versions of the Triton Oscillating Water Column type device will be modeled in WEC Sim. First, a model of a wave-tank scale device which can be tuned and validated against tank test data. Second, a model of the deployment-scale device will be constructed following the method of the tank-scale device to ensure that relevant physics are captured. In the latter case, the geometry, PTO architecture, and other design details are not yet finalized, so the model will serve as a platform for design iteration as time and budget allows. A subset of this iteration will be automated using existing WEC-Sim capabilities. A primary focus of this work will be familiarizing Triton personnel with the WEC-Sim workflow and model details so that the model of the deployment device can continue to be enhanced after project end.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Open‐Air Combustion Synthesis with Rapid Plasma Processing of Large‐Area Transparent Conducting Oxides

A vacuum-free, high-throughput synthesis of indium tin oxide (ITO) via Combustion Oxidation with Rapid Plasma Processing (CORP) utilizes a solution-based exothermic combustion reaction to generate the oxide with tunable control of either amorphous or crystalline phases. A subsequent open-air, forming gas plasma treatment is used to introduce oxygen vacancies and promote crystallization. Here, the evolution of the oxide structure is elucidated by extended X-ray absorption spectroscopy fine structure analysis. Using CORP, fabrication of 300 cm 2 of ITO possessing a champion sheet resistance of 38 Ω sq. −1 , visible transmission of 89%, conductivity stability for over 250 days, roughness < 2nm, and Haacke figure of merit (%T 550nm 10 /R s ) of 0.012 Ω −1 is achieved. Cost modeling of CORP demonstrates up to a 67% reduction in price for TCOs using fully continuous, in-line unit operations compared with vacuum sputtering. The work shows a path toward a low-cost, vacuum-free manufacturing method for TCOs at commercial scales.

42 ENGINEERING↗
DOE OSTI2021

A comparison of efficiency-aware model-predictive control approaches for wave energy devices

In this study, we compare four different formulations of model predictive control that attempt to maximise electrical power generated by a wave energy converter (WEC). Control laws include (1) pure maximisation of mechanical power, (2) maximisation of mechanical power with a control penalty factor, (3) maximisation of electrical power using power conversion efficiency, and (4) maximisation of electrical power using the full electro-mechanical model of a system. For this study, a wave-to-wire model is developed for a floating spherical buoy connected to a permanent magnet synchronous generator. The performance of the controllers, including the mechanical and electrical power outputs, is compared in irregular wave conditions for the unconstrained and force-constrained scenarios. The results demonstrate that the controller designed to maximise mechanical power is not suitable for practical applications and may lead to negative electrical power output due to the non-ideal power take-off efficiency. Moreover, the replacement of the power take-off dynamics by the efficiency coefficient does not guarantee the maximum electrical power production.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Structure–Property Correlation of Hierarchically Porous Carbons for Fluorocarbon Adsorption

Although traditional commercially available porous carbon-fluorocarbon working pairs have shown promising applicability for adsorption cooling, advancements in synthetic carbons may further improve performance. Moreover, insights into structure-property relationships that target higher sorption capacities within these synthesized carbons may guide such materials' future design. We utilized hierarchically porous synthetic carbons (HPCs) with colossal microporous and mesoporous characterized by high surface areas (up to 2689 m 2 /g) and pore volumes (up to 10.31 cm 3 /g) towards fluorocarbon R134a adsorption. This unique pore topology leads to exceptional R134a uptake, ~250 wt.%, outperforming the highest uptake carbon material to date, Maxsorb III (~220 wt.%). Additionally, material characterizations reveal that the outstanding R134a capacity may be attributed to textural properties and oxygen-terminated functional groups more than graphitization of the material. Most importantly, HPCs are efficiently utilized in a two-bed model chiller device, where the performance shows excellent working capacity (105 wt%, ~1.5 times the value of reported carbon materials/R134a). Fluorocarbons adsorption on HPCs also displays fast kinetics (equilibrium time: ~2 min) mainly driven by physical adsorption (Qst: ~27 kJ/mol), characteristic of swiftly reversible behavior adsorption-desorption behaviors. This work provides a fundamental understanding of the applicability of HPCs/R134a working pair for adsorption cooling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaics

Process optimization of photovoltaic devices is a time-intensive, trial-and-error endeavor, which lacks full transparency of the underlying physics and relies on user-imposed constraints that may or may not lead to a global optimum. Herein, we demonstrate that embedding physics domain knowledge into a Bayesian network enables an optimization approach for gallium arsenide (GaAs) solar cells that identifies the root cause(s) of underperformance with layer-by-layer resolution and reveals alternative optimal process windows beyond traditional black-box optimization. Our Bayesian network approach links a key GaAs process variable (growth temperature) to material descriptors (bulk and interface properties, e.g., bulk lifetime, doping, and surface recombination) and device performance parameters (e.g., cell efficiency). For this purpose, we combine a Bayesian inference framework with a neural network surrogate device-physics model that is 100× faster than numerical solvers. With the trained surrogate model and only a small number of experimental samples, our approach reduces significantly the time-consuming intervention and characterization required by the experimentalist. As a demonstration of our method, in only five metal organic chemical vapor depositions, we identify a superior growth temperature profile for the window, bulk, and back surface field layer of a GaAs solar cell, without any secondary measurements, and demonstrate a 6.5% relative AM1.5G efficiency improvement above traditional grid search methods.

14 SOLAR ENERGY↗
DOE OSTI2023

Using machine learning with optical profilometry for GaN wafer screening

Abstract To improve the manufacturing process of GaN wafers, inexpensive wafer screening techniques are required to both provide feedback to the manufacturing process and prevent fabrication on low quality or defective wafers, thus reducing costs resulting from wasted processing effort. Many of the wafer scale characterization techniques—including optical profilometry—produce difficult to interpret results, while models using classical programming techniques require laborious translation of the human-generated data interpretation methodology. Alternatively, machine learning techniques are effective at producing such models if sufficient data is available. For this research project, we fabricated over 6000 vertical PiN GaN diodes across 10 wafers. Using low resolution wafer scale optical profilometry data taken before fabrication, we successfully trained four different machine learning models. All models predict device pass and fail with 70–75% accuracy, and the wafer yield can be predicted within 15% error on the majority of wafers.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A 3D simulation comparison of carrier transport in green and blue c-plane multi-quantum well nitride light emitting diodes

Until recently, the electrical efficiency of green nitride light-emitting diodes (LEDs) was considerably lower than that of blue LEDs. This is particularly surprising as one would expect a reduced forward voltage with increasing emission wavelength. In this paper, we theoretically investigated the impact of the number of quantum wells on the forward voltage of III-nitride LEDs with x = 0.15 (blue) and x = 0.24 (green) In x Ga1–xN QWs. The simulated dependence of current density (J) on applied diode bias (V) shows a significant increase of 1.9 V in the forward voltage between one and five quantum well (QW) c-plane green LED structures. Artificially turning off the polarization fields in the simulation does not entirely suppress this effect. Due to the large band offsets in the green LED multiple QW stack, simulations indicate a sequential band filling of the QW sequence. Furthermore, this mechanism should not be limited to c-plane LEDs and could also be present in nonpolar or semipolar devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Phoebe: a high-performance framework for solving phonon and electron Boltzmann transport equations

Understanding the electrical and thermal transport properties of materials is critical to the design of electronics, sensors, and energy conversion devices. Computational modeling can accurately predict material properties but, in order to be reliable, requires accurate descriptions of electron and phonon states and their interactions. While first-principles methods are capable of describing the energy spectrum of each carrier, using them to compute transport properties is still a formidable task, both computationally demanding and memory intensive, requiring integration of fine microscopic scattering details for estimation of macroscopic transport properties. To address this challenge, we present Phoebe—a newly developed software package that includes the effects of electron–phonon, phonon–phonon, boundary, and isotope scattering in computations of electrical and thermal transport properties of materials with a variety of available methods and approximations. This open source C++ code combines MPI-OpenMP hybrid parallelization with GPU acceleration and distributed memory structures to manage computational cost, allowing Phoebe to effectively take advantage of contemporary computing infrastructures. We demonstrate that Phoebe accurately and efficiently predicts a wide range of transport properties, opening avenues for accelerated computational analysis of complex crystals.

36 MATERIALS SCIENCE↗