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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Ku-band electron linac for battery-powered hand-portable 2-MeV X-ray generator

X-ray generators, producing radiation in MeV range, are a critical tool for radiography, non-destructive testing and security applications. Field operation of such source requires them to be hand-portable, autonomous and allow parameter adjustability. RF linear accelerators can serve as a flexible, reliable, and robust radiation generator alternative to dangerous radioisotopes and bulky betatrons that are currently used for field radiography if their size, weight, cost, and imaging performance are matched to these sources. Here, in this paper, we present the design and test results of a 2 MeV Ku-band electron linac for a hand-portable X-ray generator system for field radiography being developed by RadiaBeam. The dramatic scale of miniaturization and cost-reduction is achieved thanks to the implementation of innovative technologies such as air-cooled Ku-band air-traffic control magnetrons, a split accelerating structure fabrication technique, and solid-state Marx modulators. This paper presents the design of the first prototype of the accelerator, its operation from Li-Ion batteries, as well as high-power and beam measurements.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

The significance of biomass densification in biological-based biorefineries: A critical review

Replacing fossil fuels with renewable biofuels derived from lignocellulosic biomass is an important aspect of addressing environmental challenges and developing a sustainable industrial society. Densification overcomes the problems of low bulk density and poor flowability of biomass and has been commercialized for producing solid biofuels, but the overall impact of densification on biological-based biorefineries that primarily target liquid fuels (e.g., ethanol) is still under investigation. Herein, this review provides a thorough summary of the application of densified biomass in biological-based biorefineries. First, the effects of densification parameters as well as variables of biomass materials on the densified products’ quality are reviewed, and different commonly used densification technologies are also discussed and compared. Then, the discussion focuses on the physiochemical modifications of biomass caused by densification that may influence further pretreatment and/or enzymatic hydrolysis in biorefineries. Industrial pelleting has been generally shown to exhibit positive/neutral effects on the enzymatic hydrolysis of multiple biomass feedstocks after pretreatments, indicating the viability of using pellets as starting feedstocks in biorefineries. Densification causes structural disruption of biomass, which may facilitate further biochemical conversions. Integrating biomass densification in the feedstock supply chain is feasible for large-scale biorefineries to overcome the techno-economic barriers and become profitable. Suggestions are presented for the efficiency enhancement and cost reduction in densification-based biorefineries. To enable wider applications, it is now the time to employ more demo and full-scale activities in different regions of the world pushing the research and innovation of densification integrated within biorefining.

09 BIOMASS FUELS↗
DOE OSTI2024

Material characterization of seven photovoltaic backsheets using seven accelerated test conditions

A variety of polymeric backsheet materials can be found in fielded photovoltaic (PV) modules, mostly based on fluoropolymer and polyethylene terephthalate (PET) materials. Cost reduction and sustainability considerations drive the recent development of alternative backsheet materials and designs [1]. In some fielded PV installations, polymeric materials are susceptible to environmental degradation in the form of backsheet cracking. To prevent backsheet degradation that can result in a module failure, thorough laboratory reliability testing is needed. In this report we studied the durability of seven commercial and experimental PV backsheets through accelerated stress testing using seven photolytic, hygrometric, and custom tests with the goal to understand if novel fluoropolymer-free backsheets are sufficiently environmentally durable to be commercialized. We divided the mechanisms observed during aging into two categories: core degradation and surface degradation. Although core degradation due to hydrolysis was observed in all commercial PET-, and polyamide (PA)-based backsheets aged with 85 degrees C/85% relative humidity, this test is unlikely to be field relevant. Photo-oxidative reactions on the exposed surface during UV weathering affected all seven backsheets regardless of the outer layer polymer material and additives. This degradation was limited to the outermost micrometers of the surface, except for backsheets containing PA-12, which resulted in surface cracking. A custom test combining UV with water spray caused the most severe backsheet degradation, including surface erosion and loss of insulating properties in polyolefin (PO)- and PA-based backsheets. This highlights the importance of combined accelerated stress testing to screen for complex backsheet degradation mechanisms. We also showed that, with material and design optimization, coextruded experimental PO-based backsheets have the potential to be a durable alternative to commercial PET- and fluoropolymer-based PV backsheets.

14 SOLAR ENERGY↗
DOE OSTI2025

Hierarchical analysis of US electric vehicle subsidies for carbon emission mitigation

Electric vehicle (EV) adoptions are promoted with subsidies to reduce greenhouse gas emissions from ground transportation. In this paper, a hierarchical analysis is presented on the potential of greenhouse gas emission mitigation via the electric vehicle subsidy policy at state level in the US, through research of environmental and economic fundamentals of electric vehicle operations, energy consumptions, battery degradation and service life. It has been found that restructuring the federal subsidies to promote EV adoption can significantly reduce greenhouse gas emissions across the US. The reduction costs of greenhouse gas emissions vary between $\$1167.44$/ton in Vermont to $\$6880.13$/ton in Wyoming. A case study reveals that 15.24 % more greenhouse gas emissions can be reduced with a tiered federal subsidy structure. The restructuring of subsidies will also encourage the adoption of clean energies in the grid fuel mix and drive technological advancements to extend the battery lifetime in the future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Truck platooning in the U.S. national road network: A system-level modeling approach

Truck platooning enables a group of trucks to move close together, which helps reduce truck fuel use and increase effective road capacity. In this paper, a system-level equilibrium model is developed to characterize spontaneous truck platooning with coexistence of non-platooning vehicles in a network, by explicitly accounting for the interlocking relationship among platoon formation time, truck fuel saving, and increase in effective road capacity. To equilibrate the relationships, an algorithm is proposed which involves a diagonalization approach and a bush based algorithm to solve decomposed subproblems. The condition of proportionality is imposed to obtain unique traffic flows for each class of vehicles on road links. In addition, a spatially constrained multivariate clustering technique is employed to construct origin/destination zones that are smaller than the coarse Freight Analysis Framework (FAF) zones, while maintaining reasonable computational burden for network traffic assignment. Model implementation in the U.S. shows that platooning could lead to 7.9% fuel saving among platoonable trucks in 2025 and a comparable increase in effective capacity of platoonable road links, which would account for 60% of rural interstate roads. The fuel saving and road capacity improvement translate into an annual cost reduction of $\$$868 million for the U.S. intercity trucking sector and reduced road infrastructure investment needs worth $\$$4.8 billion. Extensive sensitivity analysis further reveals that fuel saving of platoonable trucks increases with platoon size but decreases with inter-truck distance in a platoon. Fuel saving potential suggests that priority should be given to rural rather than urban roads in deploying platooning technologies. As we expected, greater market penetration of platooning technologies means higher fuel saving and greater increase in effective road capacity.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Hybrid Grid-Renewable Strategies for Green Steel Production under Electricity Market Uncertainty

Volatility in grid spot prices is expected to rise with climate change-driven demand pressures and the intermittency of renewable generation. This volatility poses financial risks for green hydrogen-based steel production. The Direct Reduced Iron− Electric Arc Furnace (H 2 -DRI-EAF) is a promising pathway to decarbonize steel, which accounts for ∼8% of global GHG emissions. This study assesses how increased grid spot price volatility influences the optimal sizing and operation of H2-DRIEAF plants under three operational scenarios: grid-connected, fully behind-the-meter (islanded), and mixed-mode (semi-islanded). Our analysis identifies the semi-islanded configuration as the most cost-effective solution, achieving a Levelized Cost of Steel (LCOS) 10−35% lower than sourcing energy solely from the grid. Modeling also shows hydrogen storage or selective electricity purchases at high prices (>$1000/MWh) generally outperform battery storage, except under extreme volatility. Additionally, the study explores cost reduction strategies to strengthen the economic viability and sustainability of green steel production.

Batteries↗
DOE OSTI2021

Toward the Minimal Floating Operation Count Cholesky Decomposition of Electron Repulsion Integrals

As quantum chemistry calculations deal with molecular systems of increasing size, the memory requirement to store electron-repulsion integrals (ERIs) greatly outpaces the physical memory available in computing hardware. Here, the Cholesky decomposition of ERIs provides a convenient yet accurate technique to reduce the storage requirement of integrals. Recent developments of a two-step algorithm have drastically reduced the memory operation (MOP) count, leaving the floating operation (FLOP) count as the last frontier of cost reduction in the Cholesky ERI algorithm. In this report, we introduce a dynamic integral tracking, reusing, and compression/elimination protocol embedded in the two-step Cholesky ERI method. Benchmark studies suggest that this technique becomes particularly advantageous when the basis set consists of many computationally expensive high-angular-momentum basis functions. With this dynamic ERI improvement, the Cholesky ERI approach proves to be a highly efficient algorithm with minimal FLOP and MOP count.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Exploring Parameter Redundancy in the Unitary Coupled-Cluster Ansätze for Hybrid Variational Quantum Computing

One of the commonly used chemical-inspired approaches in variational quantum computing is the unitary coupled-cluster (UCC) ansatze. Despite being a systematic way of approaching the exact limit, the number of parameters in the standard UCC ansatze exhibits unfavorable scaling with respect to the system size, hindering its practical use on near-term quantum devices. Efforts have been taken to propose some variants of UCC ansatze with better scaling. In this paper we explore the parameter redundancy in the preparation of unitary coupled-cluster singles and doubles (UCCSD) ansatze employing spin-adapted formulation, small amplitude filtration, and entropy-based orbital selection approaches. Numerical results of using our approach on some small molecules have exhibited a significant cost reduction in the number of parameters to be optimized and in the time to convergence compared with conventional UCCSD-VQE simulations. Further, we also discuss the potential application of some machine learning techniques in further exploring the parameter redundancy, providing a possible direction for future studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Conversion of Waste PET Plastic to Aramid Fiber

A three-step synthesis was used to convert waste polyethylene terephthalate (PET) into the high value polymer, poly-para-phenylene terephthalamide (PPTA), used in the production of high strength aramid fiber, such as Kevlar. Improvements to the polymerization reaction by addition of calcium chloride to the solvent, N-methyl-2-pyrrolidone (NMP), and rigorous anhydrous conditions enabled the production of a PET-derived PPTA with a 4.15 dL/g inherent viscosity in sulfuric acid that is amenable to fiber spinning. PPTA fibers were spun using a wet spinning apparatus under varied process parameters to assess their impact on fiber surface morphology, diameter, and the mechanical properties of the fibers. Select fibers were subjected to a post-spinning heat treatment at 150 °C , which improved the tensile strength and modulus by 100% and 30%, respectively, relative to the as-spun fibers. Techno-economic and life cycle analyses were conducted to evaluate the economic feasibility and the life-cycle greenhouse gases (GHG) emissions of the approach. In conclusion, the results suggest the potential for up to a 30% cost reduction, and comparable GHG emissions against conventional petroleum-based processes.

Lifecycle Analysis↗
DOE OSTI2023

Trajectory sampling and finite-size effects in first-principles stopping power calculations

Abstract Real-time time-dependent density functional theory (TDDFT) is presently the most accurate available method for computing electronic stopping powers from first principles. However, obtaining application-relevant results often involves either costly averages over multiple calculations or ad hoc selection of a representative ion trajectory. We consider a broadly applicable, quantitative metric for evaluating and optimizing trajectories in this context. This methodology enables rigorous analysis of the failure modes of various common trajectory choices in crystalline materials. Although randomly selecting trajectories is common practice in stopping power calculations in solids, we show that nearly 30% of random trajectories in an FCC aluminum crystal will not representatively sample the material over the time and length scales feasibly simulated with TDDFT, and unrepresentative choices incur errors of up to 60%. We also show that finite-size effects depend on ion trajectory via “ouroboros” effects beyond the prevailing plasmon-based interpretation, and we propose a cost-reducing scheme to obtain converged results even when expensive core-electron contributions preclude large supercells. This work helps to mitigate poorly controlled approximations in first-principles stopping power calculations, allowing 1–2 order of magnitude cost reductions for obtaining representatively averaged and converged results.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Historical and Future Learning for the New Era of Multi-Terawatt Photovoltaics

Solar photovoltaics (PV) is entering a new era of multi-terawatt deployment, with 2 TW already in service and more than 75 TW predicted in many scenarios by 2050. This next era has been enabled by over five decades of cumulative advances in PV module cost reduction, performance and reliability. The current scale of deployment also introduces new needs, opportunities and challenges. In this Perspective we frame a path forwards based on learning, broadly defined as a combination of expansion of knowledge and advances through research and development, experience and collaboration. We discuss historical topics where learning has driven PV deployment until now, and emerging areas that are required to sustain high levels of future deployment. We expect progress to continue in terms of module price, performance and reliability, driven by advances in PV cell and module design, the emergence of tandem devices and increased focus on extending module lifetimes. Large-scale deployment also means large-scale sustainability and responsibility. We therefore posit that additional metrics, such as the impact on global CO2 emissions, resource consumption and design for reuse and recycling, will become increasingly important to the PV industry and provide opportunities for further learning.

14 SOLAR ENERGY↗
DOE OSTI2022

Enhancing high-fidelity nonlinear solver with reduced order model

Abstract We propose the use of reduced order modeling (ROM) to reduce the computational cost and improve the convergence rate of nonlinear solvers of full order models (FOM) for solving partial differential equations. In this study, a novel ROM-assisted approach is developed to improve the computational efficiency of FOM nonlinear solvers by using ROM’s prediction as an initial guess. We hypothesize that the nonlinear solver will take fewer steps to the converged solutions with an initial guess that is closer to the real solutions. To evaluate our approach, four physical problems with varying degrees of nonlinearity in flow and mechanics have been tested: Richards’ equation of water flow in heterogeneous porous media, a contact problem in a hyperelastic material, two-phase flow in layered porous media, and fracture propagation in a homogeneous material. Overall, our approach maintains the FOM’s accuracy while speeding up nonlinear solver by 18–73% (through suitable ROM-assisted FOMs). More importantly, the proximity of ROM’s prediction to the solution space leads to the improved convergence of FOMs that would have otherwise diverged with default initial guesses. We demonstrate that the ROM’s accuracy can impact the computational efficiency with more accurate ROM solutions, resulting in a better cost reduction. We also illustrate that this approach could be used in many FOM discretizations (e.g., finite volume, finite element, or a combination of those). Since our ROMs are data-driven and non-intrusive, the proposed procedure can easily lend itself to any nonlinear physics-based problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Considerations for the Global Commercialization of Floating Offshore Wind Energy

Floating offshore wind (FOW) has the potential to unlock access to wind resources in deep water where fixed-bottom turbines are not feasible, enabling coastal regions around the world to meet growing energy demands. Although fixed-bottom offshore wind is commercially mature, FOW, which may be needed for water deeper than 60 m, must progress in multiple ways to reach full commercial viability. In this Perspective, we examine the status of the global FOW industry's commercial development across three key areas - technical innovation, industrialization and cross-cutting value. Technical innovation has enabled FOW turbines to perform as well as fixed-bottom turbines, with the promise of future cost reductions. However, the complex architecture of FOW turbines, combining floating structures with more than 8,000 electrical and mechanical parts in wind turbines, requires industrialization efforts such as standardization and supply-chain integration to enable commercial project deployment. FOW can potentially offer unique benefits, including reduced environmental impacts and strengthened economic development in coastal regions, through substantial regional economic activity. Successful coordination across these three areas could help to position FOW as a major contributor to a competitive, reliable and resilient global energy system.

17 WIND ENERGY↗
DOE OSTI2025

Quantum sensing for emerging energy technologies

The ability to exploit quantum phenomena has enabled sensing technologies with detection limits below the classical limit. Sensors with applications in energy discovery, production, transportation, and consumption can be enhanced through quantum or hybrid quantum-classical sensors. Here, in this Review, we provide an overview of commercial and emerging quantum sensor platforms and their opportunity areas specific to advanced energy technologies. Key examples include: power grid-enhancing-technologies, where quantum magnetometers can detect powerline and transformer faults; electric vehicle-to-grid applications, where chip-scale atomic clocks can enable grid synchronization; and carbon capture and storage, where quantum gravimeters and single-photo LiDAR can detect microscopic leaks. Quantum sensor deployment requires further research into miniaturization and ruggedization for field deployment, cost-reduction, and workforce development. The maturation of clean energy technologies and quantum sensors provide opportunities for synergy, with the integration of quantum sensors into advanced energy technologies maximizing their security, reliability, and efficiency.

critical metals↗
DOE OSTI2022

Thermodynamic guiding principles of high-capacity phase transformation materials for splitting H 2 O and CO 2 by thermochemical looping

Here, thermochemical looping splitting of water and carbon dioxide (CO 2 ) with greenhouse-gas-free (GHG-free) energy has the potential to help address the Gt-scale GHG emissions challenge. Reaction thermodynamics largely contributes to the main bottlenecks of cost reduction for thermochemical looping water/CO 2 splitting cycle. Here, we analyze thermodynamic driving forces in such cycles with two-phase ternary ferrites as model systems. We find that cation configurational entropy chiefly determines the change of partial molar entropy with oxygen stoichiometry. In addition, our phase diagram analysis accurately predicts the optimal Fe ratio for maximal water/CO 2 splitting capacity in thermal reduction and in chemical reduction based cycles, underlining the significance of phase boundary positions. With chemical reduction, >10% CO 2 conversion and high oxygen exchange capacity can both be achieved. Furthermore, our reduced Gibbs free energy model illustrates critical thermodynamic factors that influence the water/CO 2 splitting capacity. Our research reveals the thermodynamic driving forces underlying the unconventional high-capacity Fe-poor ferrites, further explained via phase diagrams of Fe–Co–O, Fe–Ni–O and Fe–Mg–O. Future materials improvements can be guided by our reduced Gibbs free energy model.

08 HYDROGEN↗
DOE OSTI2020

Parallel high-frequency magnetic sensing with an array of flux transformers and multi-channel optically pumped magnetometer for hand MRI application

Here, we investigate an approach for parallel high-frequency magnetic sensing based on a multi-channel radio frequency (RF) optically pumped magnetometer (OPM) coupled to multiple flux transformers (FTs) with a focus on hand magnetic resonance imaging (MRI) application at ultra-low field (ULF). Multiple RF OPM sensing channels are realized by using a single large-area alkali-metal vapor cell and two laser beams for pumping and probing, shared for all the channels. This design leads to significant cost reduction when multi-channel sensing is desirable, as in the case of ULF MRI. The FT, composed of two connected coils, serves as a transmitter of a target magnetic field to the OPM, while decoupling the OPM from untargeted magnetic fields in the sensing area that can limit the OPM performance. For hand MRI application, theoretical and numerical analysis is performed to determine an optimal geometry for the FT array that could improve signal-to-noise ratio (SNR) and sufficiently reduce crosstalk between FTs. We estimate that the optimized multi-channel FT-OPM sensor can achieve a magnetic field sensitivity of the order of 1 fT / Hz 1 / 2 above 100 kHz, which would be sufficient for 1 mm resolution MRI. In general, the multi-channel capability enables simultaneous magnetic measurements, thus reducing the sensing time and improving the SNR, and we anticipate many applications of the multi-channel FT-OPM sensor beyond the targeted here hand MRI: anatomical parallel ULF MRI of the human brain and other parts of the body, airport security screening, magnetic material imaging, and many others.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Surface chemistry models for GaAs epitaxial growth and hydride cracking using reacting flow simulations

Hydride vapor phase epitaxy (HVPE) is a promising technology that can aid in the cost reduction of III-V materials and devices manufacturing, particularly high-efficiency solar cells for space and terrestrial applications. However, recent demonstrations of ultrafast growth rates (~500 µm/h) via uncracked hydrides are not well described by present models for the growth. Therefore, it is necessary to understand the kinetics of the growth process and its coupling with transport phenomena, so as to enable fast and uniform epitaxial growth. In this work, we derive a kinetic model using experimental data and integrate it into a computational fluid dynamics simulation of an HVPE growth reactor. We also modify an existing hydride cracking model that we validate against numerical simulations and experimental data. Here, we show that the developed growth model and the improved cracking model are able to reproduce experimental growth measurements of GaAs in an existing HVPE system.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS↗