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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Final Report DE-FE0031785 Mohsen Ahmadian, Ph.D. Demonstration of Proof of Concept of a Multiphysics Approach for Real-Time Remote Monitoring of Dynamic Changes in Pressure and Salinity in Hydraulically Fractured Networks

Hydraulic fracturing has evolved into a multistep process with varying flow rates, carrier fluids (e.g., gel or slickwater), proppant loadings, and proppant grain sizes. As a result, primary recovery from a hydraulically fractured tight-oil reservoir is often a tiny fraction of the original oil in place, ranging between 5 and 10%. As stated in the FOA1990, “part of this problem is due to the inability of current well completion processes to effectively stimulate the entire reservoir volume in contact with the wellbore. Innovative technologies are needed that can help improve the effectiveness of reservoir completion methods, maximize stimulated reservoir volumes, and optimize recovery over the entire producing life span of a well”. We first need to enhance the current fracture diagnostic techniques to improve a well-completion design. However, detecting and delineating a subsurface hydraulic fracture is extremely difficult because the induced fracture network is only fractionally propped, and these propped fractures are generally very thin. Microseismic and tiltmeter monitoring techniques can provide information on the fracture extent but provide little or no information on the movement and final distribution of proppant or production fluids. On the other hand, electromagnetic (EM) imaging has shown the capability to monitor proppant distribution throughout the fracture area, especially in the presence of Electrically Active Proppants (EAPs). A previous EM survey of hydraulic fracturing at the Devine Fracture Pilot Site (DFPS) and subsequent EM code developments demonstrated this survey as a robust technique to remotely interrogate the extent of the EAP-filled hydraulic fracture during its propagation. The objectives of the project were threefold: (1) to capitalize on the material properties of an EAP to demonstrate remote monitoring of relative changes in pressure, pressure, and flow that are commonly encountered during production from a hydraulically fractured reservoir; (2) to evaluate EM imaging tools, to achieve Objective 1 in near real-time; and (3) to develop a multi-physics joint inversion approach to precisely predict flow patterns and physiochemical changes within an EAP-filled fracture network. This research project was built upon our previous work at the Devine Test Site managed by the Bureau of Economic Geology (BEG) at The University of Texas at Austin (UT-Austin). It also leveraged a significant investment from the Advanced Energy Consortium (AEC) to address the DOE's interest in subsurface flow, containment, and characterization by multiple signals. This three-year and three-month project succeeded in demonstrating the feasibility of a real-time dynamic fluid flow mapping technique at Technology Readiness Level 5 (TRL5) by utilizing a commercially available surface-based Controlled-Source Electromagnetic (CSEM) method (Objectives 1, 2). We demonstrated that injections into an EAP-filled fracture could be successfully coupled with real-time electric field measurements on the surface, leading to remote monitoring of dynamic changes within the EAP-filled fracture. Furthermore, the observed electric field in our study is influenced by bottomhole pressure, flow rate, and salinity, which is demonstrated by comparing these parameters with the electrical field potentials. EM simulations solely based on assumptions of fracture conductivity changes during injection did not reproduce the whole measured electric field magnitudes. Preliminary estimates showed that including Streaming Potential (SP) in our geophysical model is likely needed to reduce the simulation misfit.

02 PETROLEUM↗
DOE OSTI2017

Development of Bulk Nanocrystalline Tungsten Alloys for Fusion Reactor Structures

This project developed a technology for manufacturing bulk ultrafine tungsten materials that are at or near full density for fusion reactor structural applications, aiming to improve ductility and toughness of tungsten before and after irradiation. The project involved the development of fabrication processes for making bulk ultrafine grained W, the development of new alloys of ultrafine grained W and evaluations of properties of these specific materials. The goal of this fabrication process is to produce fully dense bulk W with ultrafine grain sizes, with uniform distributions of grain size and additives. To date there is no known process that could be used to make ultrafine grained tungsten in a fully dense state and in a cost-acceptable fashion. The specific technology described in this proposal for making ultrafine grained tungsten involves a suite of nano-particle processing and sintering techniques. The program also developed new alloys of ultrafine grained W, e.g. W-(Ta,V,Ti)-TiC alloys to improve ductility and toughness before and after irradiation. By completing this project, we achieved the following objectives: • Demonstrated experimentally the feasibility of producing bulk ultrafine grained tungsten alloys (at or near 100% dense, <1000 nm grain size) using the proposed process • Demonstrated the proposed ultrafine grained W alloys, namely, W-(Ta, V, Ti)-TiC, can indeed be made using the proposed process • Demonstrated that the properties of nano tungsten alloys meet the requirements for fusion reactor applications. The overall goal was to harness the potential of ultrafine grained W produced using the proposed processes as the core structural materials for future fusion reactors. The project was very successful overall, meeting all milestones and surpassing project goals in terms of process development and material’s blistering resistance properties. A novel process similar to the conventional press-and-sinter powder metallurgy method was developed for producing ultrafine grain tungsten from nanosize tungsten powders. Grain growth was significantly controlled during sintering by certain alloy compositions, particularly Ti, and most compositions sintered to maximum densification. To optimize this process, the effect of processing parameters on the densification and grain growth of nano-W powders was investigated. Near-fully densified tungsten was obtained at sintering temperatures between 1100 and 1300 °C, and both Ar and H2 sintering atmospheres were investigated. The Ar sintering atmosphere was determined to more favorably promote densification and minimize grain growth. The nanosized tungsten powder compacts were subjected to reduction in H2 as a part of the sintering cycle. The reduction temperature was found to have significant effects on the sintering of nano-W powder, primarily as a result of grain coarsening, which was seen at temperatures as low as 700 °C. In an effort to inhibit grain growth, the effect of Ti-based additives on the densification and grain growth of nano-W powders was investigated in this project. The addition of 1 wt.% Ti into tungsten led to more than a 63% decrease in average grain size of sintered samples at comparable density levels. Compared to conventional high temperature sintering, a lower temperature sintering cycle for a longer hold time resulted in both near-full density and fine grain size. The roles of the Ti additives include not only the inhibition of grain growth, but also the potential absorption of oxygen from W particles. The project has resulted in the publication; thus far, of six peer reviewed journal articles and seven conference presentations, as well as a master’s thesis. Two additional journal articles are currently in preparation. Presentations and articles were a particular focus of the second half of the project, once significant experimentation had been performed and analyzed. As part of our efforts to disseminate information of our results, the W research teams with Prof. Fang had a strong presence at multiple international conferences during 2015 and 2016. Several research groups in the US are now performing experiments using the ultrafine grained W materials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Radial storage efficiency for CO 2 injection: Quantifying effectiveness of local flow control methods

Basin-scale geologic carbon sequestration will require hundreds of injection wells, each of which has costs related to property rights and regulatory requirements that correlate with the areal size of the carbon dioxide plume. These surface-footprint-related issues motivate maximizing storage efficiency radially away from each well. Radial storage efficiency (RSE) is defined here as the ratio of the volumetrically weighted carbon dioxide free-phase saturation within a given radius away from the injection well to the available pore space within that same radius. Maximizing RSE effectively minimizes the radial extent of the CO 2 plume. Optimizing RSE around individual wells requires local flow control injection strategies that can increase the uniformity of the filling of pore space around the well over the entire length of the perforated injection interval despite differences in local formation transmissivity. The goal of uniform filling of the storage reservoir starting from the well outward is to maximize carbon dioxide sweep and trapping locally outward from the well in all of the layers of the storage region before buoyancy forces predominate and drive carbon dioxide upward where it will spread laterally under lower-permeability layers. Example simulations of carbon dioxide injection into a layered storage system with and without local flow control are presented to show the advantage of uniformly filling all layers and how RSE can be used to quantify storage efficiency for the two different injection approaches. Published 2021. This article is a U.S. Government work and is in the public domain in the USA.

03 NATURAL GAS↗
DOE OSTI2017

Effective photocatalytic degradation of paracetamol using La-doped ZnO photocatalyst under visible light irradiation

Highlights: • La doping enhanced photocatalytic activity of ZnO under visible light irradiation. • The 1.0 wt% La-doped ZnO was optimal for enhancing photocatalytic activity. • 99% APAP was degraded and 85% TOC was removed under visible light irradiation. • A detail photodegradation pathways were proposed using identified intermediates. - Abstract: Visible light-driven photocatalysts of lanthanum (La) doped ZnO nanoparticles were successfully prepared by a facile precipitation method using various La doping concentrations (0.5, 1.0 and 1.5 wt%). La doping did not modify the crystallinity of ZnO significantly, but enhanced the optical absorption of visible light due to the reduction in particle size and band gap energy. La-doped ZnO photocatalysts were applied to treat 100 mg/L paracetamol in aqueous solution under visible light irradiation after 3 h. 1.0 wt% La-doped ZnO photocatalyst showed the highest photocatalytic activity for the degradation of paracetamol with a degradation efficiency of 99% and TOC removal of 85%. Based on the chemical analysis of photocatalytic products detected, proposed mechanism for paracetamol removal by La-doped ZnO nanoparticles under visible light illumination including radical generation with use of photocatalytic degradation and subsequent reaction pathways was proposed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Rapid and Energy‐Efficient Synthesis of Disordered Rocksalt Cathodes

Abstract Lithium‐rich transition metal oxides with a cation‐disordered rocksalt structure (disordered rocksalt oxides or DRX) are promising candidates for sustainable, next‐generation Li‐ion cathodes due to their high energy densities and compositional flexibility, enabling Co‐ and Ni‐free battery chemistries. However, current methods to synthesize DRX compounds require either high temperature (≈1000 °C) sintering for several hours, or high energy ball milling for several days in an inert atmosphere. Both methods are time‐ and energy‐intensive, limiting the scale up of DRX production. The present study reports the rapid synthesis of various DRX compositions in ambient air via a microwave‐assisted solid‐state technique resulting in reaction times as short as 5 min, which are more than two orders of magnitude faster than current synthesis methods. The DRX compounds synthesized via microwave are phase‐pure and have a similar short‐ and long‐range structure as compared to DRX materials synthesized via a standard solid‐state route, resulting in nearly identical electrochemical performance. In some cases, microwave heating allows for better particle size and morphology control. Overall, the rapid and energy‐efficient microwave technique provides a more sustainable route to produce DRX materials, further incentivizes the development of next‐generation DRX cathodes, and is key to accelerating their optimization via high‐throughput studies.

25 ENERGY STORAGE↗
DOE OSTI2026

Machine learning insights into microstructural origins of transport and mechanical properties in porous microstructures

Multifunctional porous materials are increasingly needed across various fields, but their complex microstructures create significant challenges due to the intricate microstructure-property relationships. This complexity, combined with limitations of traditional analysis methods, hinders efforts to understand and optimize microstructure–property relationships. Here, to address this, we integrate physics-based mesoscale modeling with interpretable machine learning (ML) to uncover how microstructural features govern effective diffusivity and elastic modulus. At constant porosity, we show diffusivity varies by over 150 × and modulus by ∼50 ×, highlighting the power of microstructure engineering. Statistical analysis reveals bimodal behavior in diffusivity and unimodal in modulus. ML identifies connectivity as the dominant factor, while modulus is also sensitive to domain size and feature interactions. Controlled simulations further highlight domain shape as a critical feature for modulus. This framework enables efficient exploration of microstructure-property correlations, offering new insights to guide the design of advanced porous materials.

Bicontinuous microstructure↗
DOE OSTI2016

Direct conversion of hydride- to siloxane-terminated silicon quantum dots

Here, peripheral surface functionalization of hydride-terminated silicon quantum dots (SiQD) is necessary in order to minimize their oxidation/aggregation and allow for solution processability. Historically thermal hydrosilylation addition of alkenes and alkynes across the Si-H surface to form Si-C bonds has been the primary method to achieve this. Here we demonstrate a mild alternative approach to functionalize hydride-terminated SiQDs using bulky silanols in the presence of free-radical initiators to form stable siloxane (~Si-O-SiR 3 ) surfaces with hydrogen gas as a byproduct. This offers an alternative to existing methods of forming siloxane surfaces that require corrosive Si-Cl based chemistry with HCl byproducts. A 52 nm blue shift in the photoluminescent spectra of siloxane versus alkyl-functionalized SiQDs is observed that we explain using computational theory. Model compound synthesis of silane and silsesquioxane analogues is used to optimize surface chemistry and elucidate reaction mechanisms. Thorough characterization on the extent of siloxane surface coverage is provided using FTIR and XPS. As a result, TEM is used to demonstrate SiQD size and integrity after surface chemistry and product isolation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Bridging length scales in hard materials with ultra-small angle X-ray scattering – a critical review

Owing to their exceptional properties, hard materials such as advanced ceramics, metals and composites have enormous economic and societal value, with applications across numerous industries. Understanding their microstructural characteristics is crucial for enhancing their performance, materials development and unleashing their potential for future innovative applications. However, their microstructures are unambiguously hierarchical and typically span several length scales, from sub-ångstrom to micrometres, posing demanding challenges for their characterization, especially for in situ characterization which is critical to understanding the kinetic processes controlling microstructure formation. This review provides a comprehensive description of the rapidly developing technique of ultra-small angle X-ray scattering (USAXS), a nondestructive method for probing the nano-to-micrometre scale features of hard materials. USAXS and its complementary techniques, when developed for and applied to hard materials, offer valuable insights into their porosity, grain size, phase composition and inhomogeneities. We discuss the fundamental principles, instrumentation, advantages, challenges and global status of USAXS for hard materials. Using selected examples, we demonstrate the potential of this technique for unveiling the microstructural characteristics of hard materials and its relevance to advanced materials development and manufacturing process optimization. We also provide our perspective on the opportunities and challenges for the continued development of USAXS, including multimodal characterization, coherent scattering, time-resolved studies, machine learning and autonomous experiments. Our goal is to stimulate further implementation and exploration of USAXS techniques and inspire their broader adoption across various domains of hard materials science, thereby driving the field toward discoveries and further developments.

36 MATERIALS SCIENCE↗
DOE OSTI2016

SU-F-T-215: An Investigation Of Multi-Scanner CT Hounsfield Unit Calibration for Pencil Beam Scanning Proton Therapy Using 3D Gamma Analysis

Purpose: We compare and investigate the dosimetric impacts on pencil beam scanning (PBS) proton treatment plans generated with CT calibration curves from four different CT scanners and one averaged ‘global’ CT calibration curve. Methods: The four CT scanners are located at three different hospital locations within the same health system. CT density calibration curves were collected from these scanners using the same CT calibration phantom and acquisition parameters. Mass density to HU value tables were then commissioned in a commercial treatment planning system. Five disease sites were chosen for dosimetric comparisons at brain, lung, head and neck, adrenal, and prostate. Three types of PBS plans were generated at each treatment site using SFUD, IMPT, and robustness optimized IMPT techniques. 3D dose differences were investigated using 3D Gamma analysis. Results: The CT calibration curves for all four scanners display very similar shapes. Large HU differences were observed at both the high HU and low HU regions of the curves. Large dose differences were generally observed at the distal edges of the beams and they are beam angle dependent. Out of the five treatment sites, lung plans exhibits the most overall range uncertainties and prostate plans have the greatest dose discrepancy. There are no significant differences between the SFUD, IMPT, and the RO-IMPT methods. 3D gamma analysis with 3%, 3 mm criteria showed all plans with greater than 95% passing rate. Two of the scanners with close HU values have negligible dose difference except for lung. Conclusion: Our study shows that there are more than 5% dosimetric differences between different CT calibration curves. PBS treatment plans generated with SFUD, IMPT, and the robustness optimized IMPT has similar sensitivity to the CT density uncertainty. More patient data and tighter gamma criteria based on structure location and size will be used for further investigation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

AI Driven Optimization of Public Transit

This project explores the application of AI-driven methods to optimize public transit operations for the Chattanooga Area Regional Transportation Authority (CARTA). By leveraging data analytics, machine learning, and predictive modeling, the initiative seeks to enhance system efficiency, improve rider experience, and support sustainability goals. This research, supported by the National Science Foundation and the U.S. Department of Energy, integrates real-time transit data with advanced computational tools to inform decision-making, optimize routes, and balance operational demands. The work exemplifies a forward-looking model for mid-sized cities aiming to modernize mobility systems through intelligent technology integration.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

A Statistical Analysis of the Economic Drivers of Battery Energy Storage in Commercial Buildings: Preprint

There is significant interest in using battery energy storage systems (BESS) to reduce peak demand charges, and therefore the life cycle cost of electricity, in commercial buildings. This paper explores the drivers of economic viability of BESS in commercial buildings through statistical analysis. A sample population of buildings was generated, a techno-economic optimization model was used to size and dispatch the BESS, and the resulting optimal BESS sizes were analyzed for relevant predictor variables. Explanatory regression analyses were used to demonstrate that peak demand charges are the most significant predictor of an economically viable battery, and that the shape of the load profile is the most significant predictor of the size of the battery.

25 ENERGY STORAGE↗
DOE OSTI2017

The Simulation of Precipitation Evolutions and Mechanical Properties in Friction Stir Welding with Post-Weld Heat Treatments

A finite element model of friction stir welding capable of re-meshing is used to simulate the temperature variations. Re-meshing of the finite element model is used to maintain a fine mesh resolving the gradients of the solution. The Kampmann–Wagner numerical model for precipitation is then used to study the relation between friction stir welds with post-weld heat treatment (PWHT) and the changes in mechanical properties. Results indicate that the PWHT holding time and PWHT holding temperature need to be optimally designed to obtain FSW with better mechanical properties. Higher precipitate number with lower precipitate sizes gives higher strength in the stirring zone after PWHT. The coarsening of precipitates in HAZ are the main reason to hinder the improvement of mechanical property when PWHT is used.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A new elliptical-beam method based on time-domain thermoreflectance (TDTR) to measure the in-plane anisotropic thermal conductivity and its comparison with the beam-offset method

Materials lacking in-plane symmetry are ubiquitous in a wide range of applications such as electronics, thermoelectrics, and high-temperature superconductors, in all of which the thermal properties of the materials play a critical part. Yet, very few experimental techniques can be used to measure in-plane anisotropic thermal conductivity. A beam-offset method based on time-domain thermoreflectance (TDTR) was previously proposed to measure in-plane anisotropic thermal conductivity. However, a detailed analysis of the beam-offset method is still lacking. Our analysis shows that uncertainties can be large if the laser spot size or the modulation frequency is not properly chosen. In this report we propose an differing approach based on TDTR to measure in-plane anisotropic thermal conductivity using a highly elliptical pump (heating) beam. The highly elliptical pump beam induces a quasi-one-dimensional temperature profile on the sample surface that has a fast decay along the short axis of the pump beam. The detected TDTR signal is exclusively sensitive to the in-plane thermal conductivity along the short axis of the elliptical beam. By conducting TDTR measurements as a function of delay time with the rotation of the elliptical pump beam to different orientations, the in-plane thermal conductivity tensor of the sample can be determined. In this work, we first conduct detailed signal sensitivity analyses for both techniques and provide guidelines in determining the optimal experimental conditions. We then compare the two techniques under their optimal experimental conditions by measuring the in-plane thermal conductivity tensor of a ZnO [11-20] sample. The accuracy and limitations of both methods are discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Reducing the computational burden of a microgrid energy management system

As renewable technology advances and decreases in cost, microgrids are becoming an appealing means of distributed generation both for isolated communities and integrated with existing electrical grid systems. Due to their small size, however, microgrids may have financial limitations which preclude them from using commercial software to optimize control of their assets. Open-source optimization solvers are a viable alternative, but increase computation time. This work expands on a rolling horizon optimization framework for economic dispatch within an existing residential microgrid located in Hoover, Alabama. The microgrid has an open-source solver requirement and a need for quick solution time on a rolling horizon as opposed to a day-ahead commitment. We present a method of reducing integer variables by relaxation which completes two goals: reduction in computation time for real-time operations, and reduction in daily operational cost for the microgrid. Seasonal data for load and photovoltaic (PV) power was also collected from the microgrid to facilitate simulation testing. Computation time was successfully reduced using multiple variations of the relaxation method, while obtaining solution quality with operational cost similar to or better than the original model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Effect of porous transport layer properties on the anode electrode in anion exchange membrane electrolyzers

Anion exchange membrane water electrolyzers (AEMELs) have recently received significant attention due to their potential advantages over existing commercial water electrolysis technologies. However, AEM electrolyzers have not yet met performance and durability targets. One of the critical components in achieving high AEMEL performance is the porous transport layer (PTL) which serves many critical functions in the oxygen evolution reaction (OER) electrode. In this study, several OER PTL attributes were investigated, including: material of construction, fabrication method, feature size, porosity/density, and thickness. It was found that higher porosity helped facilitate multiphase (O 2 , H 2 O, etc.) transport; however, as the porosity increased, the catalyst layer adhesion to the PTL decreased, the contact resistance with the bipolar plate increased and the cell operating voltage increased. It was found that nickel-based PTLs allowed for lower operating voltages than similarly-structured stainless steel PTLs. Improved operating voltages were achieved with both fiber felts and sintered structures by porosity optimization. Furthermore, an increase in thickness did not affect transient voltage response, however, it had a negative effect on performance stability. As a result, the experimental findings presented here provide important insights for development of PTL materials and structures for efficient and low-cost water electrolysis.

08 HYDROGEN↗
DOE OSTI2024

Accurate numerical simulations of open quantum systems using spectral tensor trains

Decoherence between qubits is a major bottleneck in quantum computations. Decoherence results from intrinsic quantum and thermal fluctuations as well as noise in the external fields that perform the measurement and preparation processes. With prescribed colored noise spectra for intrinsic and extrinsic noise, we present a numerical method, Quantum Accelerated Stochastic Propagator Evaluation (Q-ASPEN), to solve the time-dependent noise-averaged reduced density matrix in the presence of intrinsic and extrinsic noise. Q-ASPEN is arbitrarily accurate and can be applied to provide estimates for the resources needed to error-correct quantum computations. We employ spectral tensor trains, which combine the advantages of tensor networks and pseudospectral methods, as a variational ansatz to the quantum relaxation problem and optimize the ansatz using methods typically used to train neural networks. Here, the spectral tensor trains in Q-ASPEN make accurate calculations with tens of quantum levels feasible. We present benchmarks for Q-ASPEN on the spin-boson model in the presence of intrinsic noise and on a quantum chain of up to 32 sites in the presence of extrinsic noise. In our benchmark, the memory cost of Q-ASPEN scales as a low-order polynomial in the size of the system once the number of system states surpasses the number of basis functions used in the spectral expansion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Advancing quantum simulations of the nuclear shell model with Gray-code–based resource-efficient protocols

Background: Some of the computational limitations in solving the nuclear many-body problem could be overcome by utilizing quantum computers. The nuclear shell-model calculations providing deeper insights into the properties of atomic nuclei are one such case with high demand for resources, as the size of the Hilbert space grows exponentially with the number of particles involved. Quantum algorithms are being developed to overcome these challenges and advance such calculations. Purpose: To develop quantum circuits for the nuclear shell-model, leveraging the capabilities of noisy intermediate-scale quantum (NISQ) devices. Here, we aim to minimize resource requirements (specifically in terms of qubits and gates) and strive to reduce the impact of noise by employing relevant mitigation techniques. Methods: We achieve noise resilience by designing an optimized Ansatz for the variational quantum eigensolver (VQE) based on Givens rotations and incorporating qubit-ADAPT-VQE in combination with variational quantum deflation (VQD) to compute ground and excited states, incorporating the zero-noise extrapolation mitigation technique. Furthermore, the qubit requirements are significantly reduced by mapping the basis states to qubits using Gray-code encoding and generalizing transformations of fermionic operators to efficiently represent many-body states. Results: By employing the resource-efficient protocols, we achieve the ground and excited state energy levels of 38 Ar and 6 Li with better accuracy. These energy levels are presented for noiseless simulations, noisy conditions, and after applying noise mitigation techniques. Results are compared for Jordan-Wigner and Gray-code encoding using VQE, qubit-ADAPT-VQE, and VQD. Conclusions: Our work highlights the potential of resource-efficient protocols to leverage the full potential of NISQ devices in scaling the nuclear shell model calculations, offering a pathway toward more complex quantum simulations in nuclear physics. This approach establishes a framework for studying other nuclear systems with improved quantum resource efficiency, marking a significant advancement in applying quantum computing to realistic nuclear physics applications.

Physics - Nuclear physics and radiation physics↗
DOE OSTI2018

Impact of Heat Dissipation Profiles on Power Electronics Packaging Design

This work focuses on understanding the thermal impacts of using discrete power devices and limitations of applying conventional thermal design methods. Empirically, a thermal system is designed based on selecting a heat sink with the required thermal resistance from the manufacturer datasheet. This method, as an approximate estimation, has been proven effective as a rough design of Si-based power module. However, wide bandgap (WBG) bare dies bring additional thermal design concerns that have been overlooked. The benefits of WBG devices, such as smaller chip sizes and higher power ratings, on the other hand, lead to thermal concentration issues. Detailed analyses and impacts of the thermal concentration are presented in this paper. Finally, a more accurate model involving Finite Element Analysis (FEA) and Genetic Algorithm optimization is also proposed for a more accurate thermal design.

36 MATERIALS SCIENCE↗