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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Update on the United States Advanced Ultra-Supercritical Program with Full Scale Component Fabrication to Develop Utility Scale Power Plants with 760°C Steam Temperature

Following the successful completion of a 15-year effort to develop and test materials that would allow coal-fired power plants to be operated at advanced ultra-supercritical (A-USC) steam conditions, a United States-based consortium is presently engaged in Phase 2 of a project which includes an advanced manufacturing effort to complete US-based supply chain development for full commercial scale (800-850 MWe) A-USC components made of nickel-based alloys, components operating at up to 760°C. The project, funded under U.S. Department of Energy Award No. DE-FE0025064, falls under the US DOE overall goal to Develop cost-effective, reliable technologies to improve the efficiency of new and existing coal-fired power plants. A-USC steam cycles have the potential to improve cycle efficiency, reduce fuel costs, and reduce greenhouse gas emissions. Current development and demonstration efforts are focused on enabling the construction of A-USC plants, operating with steam temperatures as high as 1400°F (760°C) and steam pressures up to 5000 psi (35 MPa), which can potentially increase cycle efficiencies to 47% HHV (higher heating value), or approximately 50% LHV (lower heating value), and reduce CO 2 emissions by roughly 25%, compared to today’s U.S. fleet. A-USC technology provides a lower-cost method to reduce CO 2 emissions, compared to CO 2 capture technologies, while retaining a viable coal option for owners of coal generation assets. Among the specific goals of Phase 2 of the ComTest Project are to: validate that components made from advanced nickel-based alloys can operate and perform under A-USC conditions accelerate the development of a U.S.-based supply chain for the full complement of A-USC components close the remaining gaps and reduce the risks for manufacturing components from advanced materials for commercial demonstration fabricate full-scale versions of selected key components made of nickel-based alloys validate a qualified U.S. supply chain, to provide greater cost certainty for components obtain American Society of Mechanical Engineers (ASME) code approval for new materials, components and processes Additional benefit: Manufacturing technology will be applicable to other advanced fossil energy high temperature cycles, and can support increased flexibility of existing power plants The ComTest project is managed by Energy Industries of Ohio, and technically directed by the Electric Power Research Institute, Inc., with General Electric designing the A-USC components. As stated earlier, the current phase of the effort is primarily funded by the U.S. Department of Energy, through the National Energy Technology Laboratory. This presentation outlines the motivation for the project, explains the project’s structure and schedule, and provides some of the technical details on the design of the ComTest components.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Nuclear waste reduction: Exploring new pathways one step at a time

In my home country of Venezuela, nuclear energy is not a topic that attracts much attention. The government briefly oversaw some nuclear energy programs during the 1950s, but currently there are no active nuclear power facilities in the country. In fact, the Venezuelan government signed and ratified the treaty of the prohibition of nuclear weapons in 2021, which states that Venezuela has never owned, possessed or controlled nuclear weapons or programs of any kind. When I moved to the United States, however, nuclear energy became an extremely relevant topic. In the 1940s, the U.S. government established and oversaw the Manhattan Project to build atomic bombs for use in World War II. After the war, the government encouraged scientists to use this information on nuclear reactions to develop nuclear energy for peaceful civilian purposes instead.1 During these early days of nuclear research, there were no formal regulatory standards for nuclear waste management. Policies usually were self-regulated and often created based on existing policies of disposal for non-nuclear waste.2 As a result, there were instances of nuclear waste leaching into the environment and affecting local communities. So, much research has been conducted since then to characterize and store nuclear waste safely and securely.3 I first became interested in nuclear energy during my undergraduate studies when I worked on a project involving ligand synthesis to help extract actinides from nuclear waste. I then studied electrochemistry in molten salt systems for nuclear energy applications during my Ph.D. As I approached graduation, I started looking into national laboratories that have programs involving nuclear energy and waste management. At Idaho National Laboratory (INL), the focus is more on applied processes and how nuclear energy can be innovated to realize next-generation reactor design and technologies. This focus led me to apply for a Seaborg distinguished postdoctoral position at INL, for which I was chosen based on my proposal of a way to improve nuclear waste recycling. To understand my proposal, we must familiarize ourselves with the makeup of nuclear waste. After uranium dioxide is used as nuclear fuel in a reactor, the fuel matrix is then characterized by various fission products, including rare earth elements, alkali and alkaline earths, and actinides. Some of these fission products can potentially be recovered through pyroprocessing, 4 which involves the electrochemical dissolution of the used nuclear fuel in a molten chloride salt mixture at high temperatures. Though some of the fission products can be easily recovered—for example, uranium is reduced onto an inert cathode by applied potentials—numerous other fission products such as rare earth elements are difficult to recover due to their multivalent oxidation states and side reactions.5 To improve the recovery efficiency of rare earth elements specifically, I proposed investigating the fundamental interactions between rare earth elements in the molten chloride salt and their metallic form (Figure 1). The kinetic pathways and the chemical reactions of these elements, which will be elucidated through spectro-electrochemistry at high temperatures, will give insights on how the recovery efficiency can be improved. Although my research focuses on fundamental science, it will benefit the applied process by generating new scientific knowledge and closing the gap for efficient recycling of the waste: one step at a time.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

JUSTIFI: Software for Improving Performance Objectives via Energy Efficiency

With growing energy supply concerns and rising costs, energy efficiency is a critical component of industrial energy resilience and competitiveness by directly reducing energy operating costs. Energy efficiency projects in manufacturing also yield valuable benefits to other key metrics, such as improved quality, reduced maintenance costs, improved safety, decreased pollution, and enhanced productivity. However, it is difficult to receive approval for energy efficiency projects, so implementation rates are low, even when meeting capital project payback period criteria. The inclusion and quantification of non-energy benefits (NEBs) in the decision-making process for energy efficiency projects can improve the overall financial payback period while demonstrating a positive impact on the firm's key performance metrics and business strategy. Despite their significant financial and strategic value, NEBs are rarely factored into decision-making due to lack of tools to effectively identify and quantify them. Therefore, a comprehensive and integrative approach is needed for the rapidly evolving energy landscape. To address these challenges, through funding from U.S. Department of Energy, our new assessment methodology integrates common continuous improvement six sigma concepts, such as the DMAIC process, and a protocol of guiding questions, into energy efficiency assessments to identify NEBs. We have also developed open-source software, JUSTIFI, to guide users through this process, data collection, and quantification. It is designed to be used concurrently with DOE energy system analysis software suite, MEASUR. Our methodology and tools inform energy assessors, firm engineering, decision makers, and workforce seeking to increase energy resilience and to maximize benefits aligned with performance metrics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

JUSTIFI: Software for Improving Performance Objectives via Energy Efficiency

With growing energy supply concerns and rising costs, energy efficiency is a critical component of industrial energy resilience and competitiveness by directly reducing energy operating costs. Energy efficiency projects in manufacturing also yield valuable benefits to other key metrics, such as improved quality, reduced maintenance costs, improved safety, decreased pollution, and enhanced productivity. However, it is difficult to receive approval for energy efficiency projects, so implementation rates are low, even when meeting capital project payback period criteria. The inclusion and quantification of non-energy benefits (NEBs) in the decision-making process for energy efficiency projects can improve the overall financial payback period while demonstrating a positive impact on the firm's key performance metrics and business strategy. Despite their significant financial and strategic value, NEBs are rarely factored into decision-making due to lack of tools to effectively identify and quantify them. Therefore, a comprehensive and integrative approach is needed for the rapidly evolving energy landscape. To address these challenges, through funding from U.S. Department of Energy, our new assessment methodology integrates common continuous improvement six sigma concepts, such as the DMAIC process, and a protocol of guiding questions, into energy efficiency assessments to identify NEBs. We have also developed open-source software, JUSTIFI, to guide users through this process, data collection, and quantification. It is designed to be used concurrently with DOE energy system analysis software suite, MEASUR. Our methodology and tools inform energy assessors, firm engineering, decision makers, and workforce seeking to increase energy resilience and to maximize benefits aligned with performance metrics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Crop diversification improves water-use efficiency and regional water sustainability

As global water scarcity intensifies, identifying agricultural practices that enhance sustainable water management is critical. Temporal crop diversification-rotating multiple species over time-has been proposed to improve soil health and water retention based on field-scale experiments. However, widespread adoption remains limited on farms, in part due to unverified benefits at larger scales. Here, we assess the influence of crop diversification on agricultural water-use efficiency (WUE, ratio of gross primary productivity to evapotranspiration) along a spectrum of monoculture to complex species rotations in California. Leveraging new high-resolution remote sensing datasets, we show that crop diversification is a key driver of agricultural WUE, and increasing the number of species planted in the previous 6 years from two to four increases WUE by ∼20% after accounting for differences between crops. Our results provide spatially explicit, large-scale quantification of crop diversification’s improvements to WUE, with direct implications for climate adaptation. More broadly, our framework offers a tool to evaluate other sustainable practices and guide policy and farm-scale decision-making.

climate-resilient agriculture↗
DOE OSTI2021

Energy-efficient sorption-based gas clothes dryer systems

Standard electric resistance and fuel-driven dehydration technologies exhibit a maximum coefficient of performance of well below 1 mainly due to enthalpy losses associated with the air leaving the dehydration system. To improve energy efficiency, condensing dryer systems condense the moisture captured from a product in a closed-loop air circulation cycle. Existing condensing dehydration systems including heat pump dryers, however, need to significantly cool the air to achieve dehumidification. The added cooling and subsequent heating to return the air to a desired drying temperature consume substantial energy and thus reduce drying performance. Here, an innovative sorption-based gas dehydration system is proposed to overcome barriers deteriorating energy efficiency in existing gas, electric, or heat pump dryer systems. Decoupling latent and sensible loads, the system employs a liquid-desiccant solution to directly capture air humidity, thereby allowing circulation of the air in a closed loop to achieve high drying energy efficiency. In other words, the system captures waste latent heat from the moisture produced during the dehydration process and reuses it to improve energy efficiency. This study focuses on a comprehensive quasi-steady-state thermodynamic modeling of the proposed sorption-based dehydration concept employed for a gas clothes dryer application to predict transient response and overall drying performance (i.e., time and energy metrics). The analysis indicates the proposed sorption-based gas clothes dryer system can deliver a specific moisture extraction rate of 1.71 kg of water per kWh (i.e., a combined energy factor of 3.167 kg (6.98 lbm) of dry cloth per kWh) with a drying time of 44 min. This is a 112% energy improvement compared with state-of-the-art gas clothes dryers exhibiting a combined energy factor of 1.50 kg (3.3 lbm) of dry cloth per kWh. The technology pursued here can potentially be employed as a platform for many fuel-driven equipment to take advantage of available waste thermal energy in the environment instead of simply burning a fuel.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Hybrid Analytics Solution for Power Plant Operations

Expert Microsystems, Inc., MapEx Software Inc. and XMPLR Energy LLC have teamed to submit a proposal to the US Department of Energy’s Office of Fossil Energy to improve the efficiency, reliability and flexibility of existing coal-based power plants. The project, titled Hybrid Analytics Solution to Improve Coal Power Plant Operations (the “Hybrid Analytics” project), will develop, demonstrate and commercialize a novel approach that integrates two proven real-time monitoring techniques. The Hybrid Analytics approach integrates into a single, integrated solution: a) an established, advanced data-driven analytics solution that includes artificial intelligence, advanced pattern recognition and machine-learning techniques and b) a well-proven, first principle thermal heat balance model solution. The future role of coal plants will depend on the ability to cycle and follow loads to meet marginal power demands, accommodate renewables and support the grid. Essential to success in this new role is a plant’s ability to maintain high reliability, efficiency and flexibility. However, these changing operational demands put significant stresses on power plant components that directly impact the ability to deliver these requirements. In the past, plants have independently monitored performance using physics-based solutions (heat rate, boiler losses, etc.) and reliability using data-driven analytics (advanced pattern recognition). The Hybrid Analytics solution integrates both approaches to enhance fault detection, provide automated diagnostics and estimates of remaining time to act, and provide critical, enhanced and accurate real-time information to coal plant operators. As a result, coal plants can improve efficiency, reliability, and flexibility and can cost-effectively maintain their key role in the power delivery system.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Characterization of Heat Transfer in a Trapped-Vortex Combustor Designed for High-Temperature Material Testing

Next generation gas turbines will reduce carbon emissions by improving their cycle efficiencies and implementing hydrogen as a low-carbon fuel. The combined-cycle efficiency can be improved by increasing the combustor outlet temperature and decreasing the cooling air required for hot-section parts. Ultra-high temperature ceramic matrix composites (CMC) can survive increasingly extreme environments due to their strong mechanical properties at expected conditions. The introduction of CMCs in high-hydrogen flame environments requires testing at realistic conditions that mimic the thermochemical and fluid mechanic states in gas-turbine combustors. In this work, we describe a new experiment that has been designed to test high-temperature materials in a combustor-relevant environment. Its trapped-vortex combustor chamber design allows for high levels of fuel flexibility and wide flame stability limits. Testing of monolithic silicon carbide (SiC) samples in this environment was done to characterize the heat transfer to material samples over a wide range of operating conditions, including variations in fuel composition and thermal power. Heat flux measurements were verified in non-reacting and reacting environments after which they were benchmarked with previous literature to verify the operation of the facility with heated air. Testing in combustor-relevant conditions shows high levels of heat flux to the material samples in the combustor, particularly downstream of the anchored flame.

Richins, Porter [Pennsylvania State University , ,↗
DOE OSTI2020

Reducing Exposures to Airborne Particles Through Improved Filtration: A High-Level Modeling Analysis

Indoor airborne particulates are well-known health hazards and filtration is one common method of reducing exposures. Based on our previously developed Regional Shelter Analysis methodology and parameters that characterize the existing US building stock, we perform a high-level assessment of the potential benefits of upgrading existing filters in furnace and in heating, ventilation, and air conditioning systems using off-the-shelf filters. We use three metrics to assess the improvement: Building Transmission Factor (a measure of protection against outdoor airborne particles), Indoor Normalized Time and Space Integrated Air Concentration (a measure of indoor exposure to indoor-origin airborne particles), and Building Exit Fraction (fraction of indoor airborne particles that are released to the outdoor atmosphere). We also discuss the potential reduction in regional exposures due to particles exiting the building and exposing downwind building occupants. Our modeling indicates that while buildings provide their occupants passive protection against airborne particulate hazards, including but not limited to PM 2.5 , PM 10 , and wildfire smoke; improving particle filtration efficiency may further improve this protection. The degree of improvement varies with particle size and building type. Of the building types studied, apartments are predicted to benefit most, with greater than a factor of 2 improvement (≥50% reduction in exposures) for 1 µm particle exposures when using MERV 7 to 12 rated filters. Non-residential buildings were notably less responsive to improved filtration but had the highest Building Exit Fractions with 30% to 40% of indoor airborne particles released to the outdoor atmosphere (apartment buildings only released 6% to 9%). Improvements predicted for single family homes were intermediate between apartments and non-residential buildings. Improvements in the Regional Exposure metric are larger, ranging from a factor of 2.5x to 10x for residences (when using MERV 7 to 12 rated filters) and up to 25x for large apartments with MERV 14 or 15 rated filters. The results of our modeling analysis are broadly consistent with the limited experimental data and modeling results available in the literature.

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

Direct Acceleration of an Electron Beam with a Radially Polarized Long-Wave Infrared Laser

Direct laser acceleration with radially polarized lasers is an intriguing variant of laser-based particle acceleration that has the potential of offering GeV/cm-level energy while avoiding the instabilities and complex beam dynamics associated with plasma wakefield accelerators. A major limiting factor is the difficulty of generating high-power radially polarized beams. In this paper, we propose the use of CO2-based long-wave infrared (LWIR) lasers as a driver for direct laser acceleration, as the polarization insensitivity of the gain medium allows a radially polarized beam to be amplified. Additionally, the larger waist sizes, Rayleigh lengths, and pulse lengths associated with the long wavelength could improve the injection efficiency of the electron beam. By comparing acceleration simulations using a near-infrared laser and an LWIR laser, we show that the injection efficiency is indeed improved by up to an order of magnitude with the longer wavelength. Furthermore, we show that even sub-TW peak powers with an LWIR laser can provide MeV-level energy gains. Thus, radially polarized LWIR lasers show significant promise as a driver of a direct laser-driven demonstration accelerator.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Future Battery Material Demand Analysis Based on U.S. Department of Energy R&D Targets

The U.S. Department of Energy’s Vehicle Technologies Office (VTO) supports research, development, and deployment of efficient, sustainable transportation technologies that will improve energy efficiency and fuel economy, and enable America to use less petroleum. To accelerate the development and adoption of new technologies, VTO has developed specific targets for a wide range of powertrain components, including the energy storage system. In this study, we use Autonomie, Argonne National Laboratory’s (Argonne’s) vehicle system simulation tool to evaluate future energy storage requirements (power, energy, etc.) for different vehicle classes, powertrains, component technologies and timeframes. BatPac, Argonne’s tool dedicated to energy storage pack design and costs, is then used to quantify the materials required for each pack. Market penetrations are then used to estimate the overall material demand worldwide and in the United States, with or without recycling. The results demonstrate that the positive impact of VTO research and development will lead to significant reduction in material compared to business-as-usual due to new anode and cathode designs, along with acceleration in battery cell chemistry penetrations. In terms of material demands, it is observed that lithium demand reaches about 80,000 tons (by a factor of 42–45), nickel demand reaches about 500,000 tons (by a factor of 47–56), manganese demand reaches about 30,000–50,000 tons (by a factor of 20–34), and cobalt demand reaches about 30,000 tons (by a factor of 13–28) in the future by 2050. The individual material demand per unit energy, however, decreases significantly in the future due to advances in VTO research and development activities. The increase in battery material demands is mostly driven by increased electrified vehicle fleet penetration in the markets.

25 ENERGY STORAGE↗
DOE OSTI2021

Multilevel-in-Space-and-Energy CMFD in VERA

For full-core modeling in the Virtual Environment for Reactor Analysis (VERA), the three-dimensional multigroup eigenvalue neutron transport problem is solved by MPACT. To improve the efficiency of MPACT, advancements have been made in the transport accelerator. Multilevel-in-energy and multilevel-in-space coarse mesh finite difference (CMFD) solvers were developed to improve the efficiency of the CMFD accelerator. In this paper a new multilevel-in-space-and-energy CMFD solver is developed with coarsening in both space and energy on every level. Several different strategies are investigated for coarsening groups in energy. Modified V-cycle and multiple-cycle algorithms are evaluated for solving the multilevel equations. The performance of these solvers is compared for typical full-core reactor physics problems.

42 ENGINEERING↗
DOE OSTI2022

Top Stack Optimization for Cu 2 BaSn(S, Se) 4 Photovoltaic Cell Leads to Improved Device Power Conversion Efficiency beyond 6%

Earth-abundant and air-stable Cu 2 BaSnS 4-x Se x (CBTSSe) and related thin-film absorbers are regarded as prospective options to meet the increasing demand for low-cost solar cell deployment. Devices based on vacuum-deposited CBTSSe absorbers have achieved record power conversion efficiency (PCE) of 5.2 % based on a conventional device structure using CdS buffer and i-ZnO/ITO window layers, with open-circuit voltage (V OC ) posing the major bottleneck for improving solar cell performance. The current study demonstrates a >20 % improvement in V OC (from 0.62 V to 0.75 V) and corresponding enhancement in PCE (from 5.1 % to 6.2 % without anti-reflection coating; to 6.5 % with MgF 2 anti-reflection coating) for solution-deposited CBTSSe solar cells. This performance improvement is realized by introducing an alternative successive ionic layer adsorption and reaction (SILAR)-deposited Zn 1-x Cd x S buffer combined with sputtered Zn 1-x Mg x O/Al-doped ZnO window/top contact layer, which offer lower electron affinities relative to the conventional CdS/i-ZnO/ITO stack and better matching with the low electron affinity of CBTSSe. A combined experimental (temperature- and light intensity-dependent V OC measurements) and device simulation (SCAPS-1D) evaluation points to the importance of addressing relative band offsets for both the buffer and window layers relative to the absorber in mitigating interfacial recombination and optimizing CBTSSe solar cell performance.

25 ENERGY STORAGE↗
DOE OSTI2024

Approach to Startup Inventory for Viable Commercial Power Plant

Summary • FPP realization within the next 10-15 years will require dedicated efforts to improve DIR, burn fraction, fueling efficiency, and/or processing times. • Modest improvements from either the fuel cycle side or plasma physics side should be possible with considered allocation of R&D funding. • Current gaps in particular include blanket extraction at scale, improved efficiency in isotope separation and detritiation, and maximizing DIR efficiency. • Total costs for FPP construction and commissioning depend heavily on site regulation, so decreases in required SI and OI can lead to large decreases in capital outlay. • Some subsystems in the fuel cycle are required from a environmental management perspective but are both energetically expensive and time consuming, particularly water detritiation. • Low inventories but high capital and operational costs mean a centralized water detritiation plant could greatly improve likelihood of deployment of multiple FPPs on the same time scale.

MALONE, COLLIN↗
DOE OSTI2021

Performance of direct injected propane and gasoline in a high stroke-to-bore ratio SI engine: Pathways to diesel efficiency parity with ultra low soot

This work explores pathways to achieve diesel-like, high-efficiency combustion with stoichiometric 3-way catalyst compatible combustion in a single-cylinder spark ignition (SI) research engine. A unique high stroke-to-bore engine design (1.5:1) with cooled exhaust gas recirculation (EGR) and high compression ratio ( r c ) was used to improve engine efficiency by up to 30% compared with a production turbocharged gasoline direct injection spark ignition engine. Engine experiments were conducted with both 91 RON E10 gasoline and liquified petroleum gas (LPG) (i.e. autogas) and were compared to legacy gasoline data on the production engine. Geometric compression ratio ( r c ) of 13.3:1 was used for both fuels with additional experiments at 16.8:1 for LPG only. Measurements of exhaust soot particle size and number concentrations were made with both fuels. Significant reduction in soot particles across the whole particle size range were achieved with LPG due to the elimination of in-cylinder liquid films. The effects of EGR, late intake valve closing (IVC) and fuel characteristics were investigated through their effects on efficiency, combustion stability and soot production. Results of 47% gross thermal efficiency, and 45% net thermal efficiency at stoichiometric engine operation, at up to 17 bar IMEP and 2000 r/min with 16.8:1 r c were achieved with LPG. Estimated brake efficiency values were compared to a contemporary medium duty diesel engine illustrating the benefits of the chosen path for achieving diesel efficiency parity.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

SGD-Net: Efficient Model-Based Deep Learning with Theoretical Guarantees

Deep unfolding networks have recently gained popularity for solving imaging inverse problems. However, the computational and memory complexity of data-consistency layers within traditional deep unfolding networks scales with the number of measurements, limiting their applicability to large-scale imaging inverse problems. We propose SGD-Net as a new methodology for improving the efficiency of deep unfolding through stochastic approximations of the data-consistency layers. Our theoretical analysis shows that SGD-Net can be trained to approximate batch deep unfolding networks to an arbitrary precision. Our simulations on intensity diffraction tomography and sparse-view computed tomography show that SGD-Net can match the performance of the traditional batch network at a fraction of training and testing complexity.Deep unfolding networks have recently gained popularity for solving imaging inverse problems. However, the computational and memory complexity of data-consistency layers within traditional deep unfolding networks scales with the number of measurements, limiting their applicability to large-scale imaging inverse problems. We propose SGD-Net as a new methodology for improving the efficiency of deep unfolding through stochastic approximations of the data-consistency layers. Our theoretical analysis shows that SGD-Net can be trained to approximate batch deep unfolding networks to an arbitrary precision. Our simulations on intensity diffraction tomography and sparse-view computed tomography show that SGD-Net can match the performance of the traditional batch network at a fraction of training and testing complexity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Multilayered Cu-Carbon Nanotube Composites for Advanced Conductors

Improving the efficiency of electrical components is critical in reducing energy consumption for various industrial and residential applications, ranging from rotating machinery to all electric devices and electric vehicle (EV) components to power grid systems. Substituting Cu wires with reduced resistance conductors that incorporate carbon nanotubes (CNTs) into Cu─ultraconductive Cu (UCC) composites─has recently been considered a promising strategy to improve energy efficiency, power density, and/or performance across various applications. Here, in this study, we created stable material formulations [CNT-containing polyvinylpyrrolidone (PVP) in dimethylformamide (DMF) solution] and utilized commercially viable fabrication approaches (electrospinning and magnetron sputtering) that produced high-performance multilayered tape-based UCC composite architectures. Increasing the CNT volume fraction by sequential layering of the structure with additional Cu-CNT layers showed a nearly stepwise improved performance in electrical and mechanical properties. This study also provides valuable insight into the effectiveness of nitrogen doping in modifying the conductivity of the CNT matrix. Fabricated prototypes demonstrated a >10% increase in current carrying capacity and >10% improvement in mechanical strength compared to those obtained on pure Cu. We believe that the properties demonstrated here, combined with the scalable manufacturing pathway of our approach, pave the way in designing future advanced conductors for diverse energy efficient and high-performance electrical systems and applications.

Carbon nanotubes↗
DOE OSTI2020

Improved Fast Randomized Iteration Approach to Full Configuration Interaction

In this work, we present three modifications to our recently introduced fast randomized iteration method for full configuration interaction (FCI-FRI) and investigate their effects on the method’s performance for Ne, H 2 O, and N 2 . The initiator approximation, originally developed for full configuration interaction quantum Monte Carlo, significantly reduces statistical error in FCI-FRI when few samples are used in compression operations, enabling its application to larger chemical systems. The semistochastic extension, which involves exactly preserving a fixed subset of elements in each compression, improves statistical efficiency in some cases but reduces it in others. We also developed a new approach to sampling excitations that yields consistent improvements in statistical efficiency and reductions in computational cost. We discuss possible strategies based on our findings for improving the performance of stochastic quantum chemistry methods more generally.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗