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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Thermal management challenges in lithium-ion batteries: understanding heat generation mechanisms

This paper investigates heat generation in commercial 18 650 lithium-ion battery cells and the thermal management challenges from their high energy density and electrochemical processes. Thermal effects can degrade performance, accelerate aging, and increase thermal runaway risk. Using isothermal calorimetry and EIS, the study emphasizes optimizing thermal behavior to improve battery efficiency, safety, and durability.

25 ENERGY STORAGE↗
DOE OSTI2025

Photoswitching dynamics of a guanidine anion receptor

Photoswitchable molecules involving large-scale structural changes such as E/Z photoisomerization offer remarkable opportunities for light-stimulated catch-and-release chemical separations. While the feasibility of this photochemically driven mechanism has been demonstrated in pioneering studies, the electronic excited-state relaxation processes and concomitant structural changes of such a functional photoswitcher remain largely unexplored. Here, we investigate an exceptional photoswitchable molecule, 2-pyridyl-diiminoguanidinium (2PyDIG), which exhibits strong and selective anion binding, along with an extraordinary capability for light-induced release of a guest ion. Through time-resolved fluorescence measurements and multireference and time-dependent density functional theory calculations, we reveal the dynamics underlying electronic excited state relaxation and photoisomerization central to photoswitching. A very rapid and dominant decay component was found that is consistent with radiationless de-excitation from S 1 to S 0 through conical intersections. This process competes effectively with the slower photoisomerization process taking place in 94 ps. We further identified the underlying causes through theoretical calculations and potential routes towards improved photoisomerization efficiencies.

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

An unwanted guest in the electrochemical oxidation of high-voltage Li-ion battery electrolytes: the life of highly reactive protons

Lithium-ion batteries (LIBs) are central to the urgent societal need to decarbonize both transportation and energy storage on the grid. Unfortunately, despite their attractive energy/power density, as well as high coulombic and energy efficiencies, further improvement of this technology – especially their durability – is desperately needed. To support these efforts, our study focuses on fundamental understanding of the decomposition pathways for LIB electrolytes at the cathode–electrolyte interface (CEI), as the nature of these reactions directly controls the extent to which cell capacity and voltage decays in these systems. In this study, we employ electrochemical methods, coupled with product analysis using NMR spectroscopy and mass spectrometry, to determine the decomposition mechanisms in both model and technologically relevant electrolytes. Remarkably, we discovered the electrochemical formation of protons with high chemical activity, comparable to known superacids, at potentials relevant to practical Li-ion batteries. Their reactivity toward every individual component of the CEI provides a unified thermochemical origin for a myriad of side reactions that are commonly associated with the electrochemical reaction. In particular, electrochemically generated protons react with intact EC molecules to form CO 2 and other short and long chain ethers. They also undergo an acid–base reaction with LiPF 6 , to form the weaker acid HF, and with the cathode active material, leaching transition metals into the electrolyte. Collectively, the results of this study all point to the urgent need to either mitigate this proton formation or introduce benign harvesting additives via new electrolyte design strategies.

Ilic, Stefan [Argonne National Laboratory (ANL), A↗
DOE OSTI2025

Elucidating the impact of fiber source on polypropylene/hemp composite performance for the automotive industry

Given their high strength-to-weight ratio, there is an ever-increasing volume of plastics being used in the automotive industry as plastics aid in the charge to lightweight vehicles for improved fuel efficiency. However, these plastics are often landfilled at their end-of-life, which has given rise to the demand for sustainable materials and waste management alternatives compared to purely synthetic systems. Natural fiber composites have been explored as a viable material option to reduce the environmental impact of plastic use in automobiles while simultaneously ensuring the part performance is not sacrificed. Herein, we explored the use of hemp/polypropylene (PP) composites in which US-sourced hemp is compared to internationally sourced and industrially available hemp. There appears to be a minimal impact on the composite properties regardless of fiber sourcing, and the addition of a natural filler to the PP matrix results in up to a 367% increase in Young's modulus, 126% increase in heat deflection temperature, and comparable water uptake performance. It should be noted that the natural filler addition does increase density by up to 13% due to the higher density of natural fibers compared to the low-density PP matrix. A modified rule of mixtures calculation revealed that the composite materials produced in this study demonstrated good agreement with analytical modeling. Finally, a screening analysis was performed exploring the transportation of hemp fibers, and the results build a strong case for regionalized manufacturing of automotive parts.

Hubbard, Amber M. [Oak Ridge National Laboratory (↗
DOE OSTI2020

Short-term load demand forecasting through rich features based on recurrent neural networks

With the emerging penetration of renewables and dynamic loads, the understanding of grid edge loading conditions becomes increasingly substantial. Load modelling researches commonly consist of explicitly expressed load models and non-explicitly expressed techniques, of which artificial intelligence approaches turn out to be the major path. This paper reveals the artificial intelligence-based load modelling technique to enhance the knowledge of current and future load information considering geographical and weather dependencies. This paper presents a recurrent neural network based sequence to sequence (Seq2Seq) model to forecast the short-term power loads. Also, a feature attention mechanism, which is along channel and time directions, is developed to improve the efficiency of feature learning. The experiments over three publicly available datasets demonstrate the accuracy and effectiveness of the proposed model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Continuum electromagnetic gyrokinetic simulations of turbulence in the tokamak scrape-off layer and laboratory devices

Here, we present algorithms and results from Gkeyll, a full-f continuum, electromagnetic gyrokinetic code, designed to study turbulence in the edge region of fusion devices. The edge is computationally very challenging, requiring robust algorithms that can handle large-amplitude fluctuations and stable interactions with plasma sheaths. We present an energy-conserving high-order discontinuous Galerkin scheme that solves gyrokinetic equations in Hamiltonian form. Efficiency is improved by a careful choice of basis functions and automatically generated computation kernels. Previous verification tests were performed in the straight-field-line large plasma device [Shi et al., J. Plasma Phys. 83, 905830304 (2017)] and the Texas Helimak, a simple magnetized torus [Bernard et al., Phys. Plasmas 26, 042301 (2019)], including the effect of end-plate biasing on turbulence. Results for the scrape-off layer for NSTX parameters with a model helical magnetic geometry with bad curvature have been obtained [Shi et al., Phys. Plasmas 26, 012307 (2019)]. In this paper, we present algorithms for the two formulations of electromagnetic gyrokinetics: the Hamiltonian and the symplectic. We describe each formulation and show results of benchmark tests. Although our scheme works for the Hamiltonian formulation, the presence of spurious numerical modes for high-β and large $k^2_⊥ρ^2_s$ regimes shows that the symplectic formulation is more robust. We then review our recent algorithm for the symplectic formulation [Mandell et al., J. Plasma Phys. 86, 905860109 (2020)], along with example application of this new capability. Maintaining positivity of the distribution function can be challenging, and we describe a new and novel exponential recovery based algorithm to address this.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Preparation, analysis, and application of coated glass targets for the Wendelstein 7-X laser blow-off system

Coated glass targets are a key component of the Wendelstein 7-X laser blow-off system that is used for impurity transport studies. The preparation and analysis of these glass targets as well as their performance is examined in this paper. The glass targets have a high laser damage threshold and are coated via physical vapor deposition with μm thick films. In addition, nm-thin layers of Ti are used as an interface layer for improved ablation efficiency and reduced coating stress. Hence, the metallic or ceramic coating has a lateral homogeneity within 2% and contaminants less than 5%, being optimal for laser ablation processing. With this method, a short (few ms) and well defined pulse of impurities with about 1017 particles can be injected close to the last closed flux surface of Wendelstein 7-X. In particular, a significant amount of atoms with a velocity of about 1 km/s enters the plasma within 1 ms. The atoms are followed by a negligible concentration of slower clusters and macro-particles. This qualifies the use of the targets and applied laser settings for impurity transport studies with the laser blow-off system in Wendelstein 7-X.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Singlet fission

Singlet fission (SF) is a process whereby a photo-excited singlet exciton spontaneously splits into lower energy triplet excitons. This process has been known to occur in select organic materials for over 50 years but in the past was viewed as a curiosity and not as a problem worthy of focused attention. Over the past decade, this viewpoint has changed as the promising use of SF to improve photovoltaic efficiency has spurred vast activity, which has revealed the richness of the phenomenon. Currently, our understanding of the role played by various bright and dark states and their couplings to vibrations and to each other and by chemical composition and packing, among other factors, has enabled a large increase in the number of viable SF systems as well as a far deeper understanding of the process itself. These advances have allowed for the demonstration of proof-of-concept increases in the solar cell efficiency via the use of SF materials in simple tandem cells and as sensitizers in conjunction with conventional photovoltaics. Indeed, concepts surrounding the field have now invaded other fields, with a prominent example being the use of photon upconversion associated with triplet–triplet fusion (the inverse process to SF) in organic chemistry and photocatalysis. The 23 research articles in this special topic showcase recent cutting-edge advances in the field and highlight the diverse new directions being explored in the field of SF.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

In situ TEM measurement of electrical properties of individual BaTiO 3 nanocubes

We report on the measurement of the electrical properties of individual pristine and doped BaTiO 3 nanocubes by using in situ transmission electron microscopy with a two-electrode configuration. The dimensions of the nanocubes tested are between 10 and 20 nm, which rendered their in situ electrical characterization challenging. We characterized 4%Cr and 5%La (atomic percentage) doped BaTiO 3 nanocubes and compared them with the properties of pristine BaTiO3 nanocubes synthesized by the same solvothermal method. We found that the resistance of all three types of nanocubes when displayed in log-scale shows a nearly linear dependence on the applied electric field (R2 ≥ 0.95) over a wide range of electric fields (50–900 kV/cm). Compared with pristine BaTiO 3 nanocubes, the resistance of both 4%Cr and 5%La doped nanocubes showed reduced variation rates with respect to the electric field, with 5%La doping, demonstrating a better reduction in the variation rate. By developing techniques capable of evaluating the properties of individual BaTiO 3 nanocubes, we expect that our work to open the door to the use of BaTiO 3 nanomaterials in the design of future multilayer ceramic capacitors with improved volumetric efficiency and ferroelectrics-enabled nanodevices with advanced functionality.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Light extraction in tandem organic light emitting diodes

Since the invention of organic light emitting diodes (OLEDs), great research efforts have been dedicated to improving their efficiency and lifetime. For high-brightness applications, tandem OLED structures have advantages because of the lower current densities required to achieve high brightness. With the successful development of highly efficient charge generation layers, high brightness tandem OLEDs are used in displays and lighting. However, the major challenge for tandem OLEDs is the low light extraction efficiency, because about 50% of the light is trapped inside the device as waveguide modes. In this Perspective, we first review the recent works done on light extraction, analyze different waveguide mode extraction structures, and then identify the key factors determining the extraction efficiencies in tandem OLEDs.

42 ENGINEERING↗
DOE OSTI2022

Defect tolerance in halide perovskites: A first-principles perspective

In recent years, the impressive photovoltaic performance of halide perovskites has been commonly attributed to their defect tolerance. This attribution is seemingly intuitive and has been widely promoted in the field, though it has not been rigorously assessed. In this Perspective, we critically discuss the proposition of defect tolerance in halide perovskites based on first-principles calculations. We show that halide perovskites actually do suffer from defect-assisted nonradiative recombination, i.e., they are not defect tolerant. The nonradiative recombination rates in halide perovskites are comparable to or even greater than those in more conventional semiconductors. We note that to obtain accurate defect properties in halide perovskites, the level of theory and computational details are highly important, which was previously not sufficiently recognized. A distinctive feature of halide perovskites is that they can be grown with moderate defect densities using low-cost deposition techniques. But, similar to the case of conventional semiconductors, defect engineering is still key to improving the efficiency of perovskite solar cells.

14 SOLAR ENERGY↗
DOE OSTI2022

Quantification of electron correlation for approximate quantum calculations

State-of-the-art many-body wave function techniques rely on heuristics to achieve high accuracy at an attainable computational cost to solve the many-body Schrödinger equation. By far, the most common property used to assess accuracy has been the total energy; however, total energies do not give a complete picture of electron correlation. In this work, we assess the von Neumann entropy of the one-particle reduced density matrix (1-RDM) to compare selected configuration interaction (CI), coupled cluster, variational Monte Carlo, and fixed-node diffusion Monte Carlo for benchmark hydrogen chains. A new algorithm, the circle reject method, is presented, which improves the efficiency of evaluating the von Neumann entropy using quantum Monte Carlo by several orders of magnitude. The von Neumann entropy of the 1-RDM and the eigenvalues of the 1-RDM are shown to distinguish between the dynamic correlation introduced by the Jastrow and the static correlation introduced by determinants with large weights, confirming some of the lore in the field concerning the difference between the selected CI and Slater–Jastrow wave functions.

Chemistry↗
DOE OSTI2023

Machine learning guided optimal composition selection of niobium alloys for high temperature applications

Nickel- and cobalt-based superalloys are commonly used as turbine materials for high-temperature applications. However, their maximum operating temperature is limited to about 1100 °C. Therefore, to improve turbine efficiency, current research is focused on designing materials that can withstand higher temperatures. Niobium-based alloys can be considered as promising candidates because of their exceptional properties at elevated temperatures. The conventional approach to alloy design relies on phase diagrams and structure–property data of limited alloys and extrapolates this information into unexplored compositional space. In this work, we harness machine learning and provide an efficient design strategy for finding promising niobium-based alloy compositions with high yield and ultimate tensile strength. Unlike standard composition-based features, we use domain knowledge-based custom features and achieve higher prediction accuracy. We apply Bayesian optimization to screen out novel Nb-based quaternary and quinary alloy compositions and find these compositions have superior predicted strength over a range of temperatures. We develop a detailed design flow and include Python programming code, which could be helpful for accelerating alloy design in a limited alloy data regime.

Mohanty, Trupti (ORCID:0000000342701430)↗
DOE OSTI2023

Strain effects on Auger–Meitner recombination in silicon

We study the effects of compressive and tensile biaxial strain on direct and phonon-assisted Auger–Meitner recombination (AMR) in silicon using first-principles calculations. We find that the application of strain has a non-trivial effect on the AMR rate. For most AMR processes, the application of strain increases the AMR rate. However, the recombination rate for the AMR process involving two holes and one electron is suppressed by 38% under tensile strain. We further analyze the specific phonon contributions that mediate the phonon-assisted AMR mechanism, demonstrating the increased anisotropy under strain. In conclusion, our results indicate that the application of tensile strain increases the lifetime of minority electron carriers in p-type silicon and can be leveraged to improve the efficiency of silicon devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Artificial-intelligence-driven shot reduction in quantum measurement

Variational Quantum Eigensolver (VQE) provides a powerful solution for approximating molecular ground state energies by combining quantum circuits and classical computers. However, estimating probabilistic outcomes on quantum hardware requires repeated measurements (shots), incurring significant costs as accuracy increases. Optimizing shot allocation is thus critical for improving the efficiency of VQE. Current strategies rely heavily on hand-crafted heuristics requiring extensive expert knowledge. This paper proposes a reinforcement learning (RL)-based approach that automatically learns shot assignment policies to minimize total measurement shots while achieving convergence to the minimum of the energy expectation in VQE. The RL agent assigns measurement shots across VQE optimization iterations based on the progress of the optimization. This approach reduces VQE's dependence on static heuristics and human expertise. When the RL-enabled VQE is applied to a small molecule, a shot reduction policy is learned. The policy demonstrates transferability across systems and compatibility with other wavefunction Ansätze. In addition to these specific findings, this work highlights the potential of RL for automatically discovering efficient and scalable quantum optimization strategies.

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

Electronic structure theory with molecular point group symmetries on quantum annealers

Quantum computation has the potential to revolutionize quantum chemistry through major speedups in computation times and an exponential reduction in computational resources. Here, we combine the symmetry-adapted Jordan–Wigner encoding based on the full Boolean symmetry group $\mathbb{Z}$$^{k}_{2}$ with our new implementation of the Xia–Bian–Kais (XBK) method for improving the efficiency of electronic structure theory calculations on quantum annealers, particularly by reducing the number of qubits needed to achieve the same accuracy. By providing a more extensive symmetry-adapted encoding (SAE) than previous work, we are able to simulate molecules larger than those previously reported that have been studied using methods developed for quantum annealers and without using an active space. We calculated the potential energy surfaces of H 2 , LiH, He 2 , H 2 O, O 2 , N 2 , Li 2 , F 2 , CO, BH 3 , NH 3 , and CH 4 , with the largest molecule in the STO-6G basis set requiring 16 qubits with our SAE, and compared them with full configuration interaction results. The application of SAE to the XBK method provides an exponential reduction in the size of the Hilbert space and scales well with the size of the problem. It does not introduce significant additional errors for even or large values of a key variational parameter that determines the number of ancilla qubits used in the XBK method’s Hamiltonian embedding, or for certain molecules such as He 2 and H 2 O. Here, we provide an explanation for this behavior and a recommendation on the usage of our method. In addition, we briefly discuss the potential of extracting electronic excited states from our method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Minimal implicit-solvent coarse-grained simulation of Pluronic block copolymers with ionic liquids

Pluronic block copolymers, composed of poly(ethylene oxide) (PEO) and poly(propylene oxide) (PPO) in a triblock structure (PEO–PPO–PEO), are well known for their amphiphilic character and ability to self‐assemble into micelles in aqueous solution. The addition of ionic liquids (ILs) can further modulate the core–shell structures of these copolymers, influencing their stability, critical micellization temperature, and size. However, fully atomistic simulations often become prohibitively expensive due to the size and complexity of these systems. In this work, coarse‐grained simulations using a minimal implicit‐solvent model were performed to examine how two classes of ILs, namely, 1‐alkyl‐3‐methylimidazolium ([C n C 1 im]) and 1‐alkyl‐3‐methylpyrrolidinium ([C n C 1 pyrr]), change the micellization of Pluronic block copolymers in aqueous solution. The effects of IL concentration and alkyl group length were investigated, and the model greatly improved the efficiency of simulating large‐scale micelle systems. Furthermore, the numerical simulations are qualitatively compared with experimental investigations. Our results show that adding ILs expands the micelle core by embedding IL tails among the PPO blocks, thereby increasing overall micelle size. Less polar ILs generally induce more pronounced micellar growth. However, the effect of IL tail length on conformation and micellar packing is non‐monotonic. Up to moderate chain lengths (around C8–C10), the IL tails can extend sufficiently to increase local separation within the micelle; at longer tail lengths, enhanced hydrophobic clustering and steric hindrance cause the tails to bend or fold, capping further expansion. In addition, although block copolymer chains tend to pack more closely in the presence of longer‐tailed ILs, the random coil size of an individual polymer chain does not necessarily shrink. Meanwhile, these insights provide a deeper understanding of how Pluronic/IL systems interact, informing applications in drug delivery, cosmetics, food, and environmental engineering. Finally, our minimal implicit‐solvent model can be applied to larger systems and longer timescales, substantially reducing computational cost while reproducing key structural trends observed experimentally.

Atomistic simulations↗
DOE OSTI2026

Filament extension atomizers: A study of integration potential into spray dryers for high-viscosity and non-Newtonian fluids

Filament extension atomizers (FEAs) are an emerging class of spray nozzles designed to atomize high-viscosity and non-Newtonian fluids that are challenging for conventional pressure or two-fluid nozzles. In this study, we investigate the influence of roller geometry, surface velocity, roller material, and fluid rheology on the atomization performance of FEA systems using concentrated whey protein suspensions (50–70 wt. %). Extensional and shear rheology experiments, along with high-speed imaging and particle image velocimetry, reveal that filament breakup dynamics are governed by competition between inertial, capillary, and viscoelastic stresses. High roller rotational velocity leads to narrower spray cones, contradicting rheology experiments and suggests a significant inertial contribution to filament breakup. Smaller rollers operating at the same rotational velocity led to broader spray cones consistent with expectations. An FEA nozzle was integrated into a conventional dryer producing particles in the 100 μm range. Results suggest that FEA technology enables atomization of highly viscous fluids at industrially relevant spray cone angles similar to those generated by pressure nozzles, offering a pathway to improve energy efficiency in spray drying by enabling higher solids loading feedstocks. Furthermore, these insights provide critical guidance for optimizing FEA nozzle designs and process parameters across a range of applications.

Energy efficiency↗