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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Mirrors for petawatt lasers: Design principles, limitations, and solutions

High intensity and high energy laser facilities place increasing demands on optical components, requiring large surface area optics with exacting specifications. Petawatt lasers are high energy, short-pulse laser systems generally based on chirped-pulse amplification, where an initial low energy short pulse is stretched, amplified, and then recompressed to produce fs to ps high-power laser pulses. In such petawatt lasers, the highest demands are placed on the final optics, including gratings which compress the pulses and mirrors which direct and focus the final high-power beams. The limiting factor in these optical components is generally laser-induced damage. Designing and fabricating these optical components to meet reflection, dispersion, and other requirements while meeting laser-induced damage requirements is the primary challenge discussed in this tutorial. We will introduce the reader to the technical challenges and tradeoffs required to produce mirrors for petawatt lasers and discuss current research directions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

First-principles elucidation of defect-mediated Li transport in hexagonal boron nitride

Hexagonal boron nitride (hBN) is a promising candidate as a protective membrane or separator in Li-ion and Li–S batteries, given its excellent chemical stability, mechanical robustness, and high thermal conductivity. In addition, hBN can be functionalized by introducing defects and dopants, or be directly integrated into other active components of batteries, which further augments its appeal to the field. Here, we use first-principles simulations to evaluate the role of atomic defects in hBN in regulating the Li-ion diffusion mechanism and associated kinetics. Specifically, the following four distinct types of vacancy defects are considered: isolated single B and N vacancies, a B–N vacancy pair, and a B 3 N vacancy cluster. It is found that these defect sites generally favor Li intercalation and out-of-plane diffusion but slow down in-plane Li-ion diffusion due to a strong Li trapping effect at the defect sites. Such a trapping effect is, however, highly local such that it does not necessarily affect the overall Li-ion conductivity in defected hBN layers. The present systematic evaluation of the impact of atomic defects on Li ion migration and accompanied charge analysis of hBN lattice in response to Li-ion diffusion provide a mechanistic understanding of Li-ion transport behavior in defected hBN and highlight the potential of defect engineering to achieve optimal material performance.

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

First-principles prediction of incipient order in arbitrary high-entropy alloys: exemplified in Ti 0.25 CrFeNiAl

High-temperature disordered multi-component alloys, including high-entropy alloys, experience either segregation or partially-ordered phases to reach low-temperature phases. For Ti 0.25 CrFeNiAl x (0 ≤ x ≤ 1), experiments suggest a partially-ordered B2 phase, whereas CALculation of PHAse Diagrams (CALPHAD) predicts a region of L21+B2 coexistence. We employ first-principles KKR-CPA to assess stability of phases with arbitrary order and a KKR-CPA linear-response theory to predict atomic short-range order (SRO) in the disorder phase that reveals the competing long-range ordered (LRO) phases in a given Bravais lattice. The favorable SRO provides a specific concentration-waves (site occupation probabilities and partially-ordered unit cells) and estimated energy gains that can then be assess directly by KKR-CPA formation enthalpies. Our results are in good agreement with experiments and CALPHAD in Al-poor regions (x ≤ 0.75) and with CALPHAD in Al-rich region (1≥ x >0.75). Our first-principles KKR-CPA and SRO-based concentration-wave analysis is shown to be a powerful and fast method to assess competing LRO phases in complex solid-solution alloys, and our results suggests more careful experiments in Al-rich region are needed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Interface property–functionality interplay suppresses bimolecular recombination facilitating above 18% efficiency organic solar cells embracing simplistic fabrication

Efficient exciton-to-charge generation from the introduction of non-fullerene acceptors (NFAs) has been an important breakthrough in organic solar cell (OSC) developments. However, low device fill factors (FFs) following significant free charge carrier recombination loss continue to undermine their marketplace potential. Previous studies have successfully uncovered the importance of donor and acceptor domains in promoting charge transport. However, the functionality of donor/acceptor (D/A) interfaces relevant to free charge recombination remains unclear despite such interfaces being present throughout the material. In this work, the disorder-induced uphill bulk-to-D/A interface transport energy landscape is unveiled to enhance the polaron recombination resistance thereby also mitigating the triplet state formation from back charge transfer. In simple words, increasing the interface disorder while keeping the purer domains highly ordered will impart greater bulk-to-interface differential energy which then serves as a recombination energy barrier. Herein, these are made possible by varying the NFA outer side chains from linear alkyls to bulkier 2D phenylalkyls which influence the donor–acceptor interaction and define the interfacial disorder. Meanwhile, the extent of interface disorder without tradeoff in geminate losses is dependent on electrostatics and nanomorphology driving efficient exciton dissociation. By understanding these interplays, remarkable FFs over 80% and power conversion efficiencies (PCEs) above 18% are revealed to remain accessible even with simple binary component device fabrication without additional components/treatments thereby maintaining the scalability. Consequently, the principles uncovered here will serve as the foundation to reach the optimum potential of binary and simple systems, a prerequisite to ultimately realize the most cost-effective OSC design strategies for practical applications.

14 SOLAR ENERGY↗
DOE OSTI2022

Revisiting W–ZrC interfaces: A first principles study

We investigate W–ZrC interfaces using first-principles calculations based on the density functional theory. There have been theoretical and experimental studies exploring W–ZrC interfaces, however, the debate regarding the most stable interface continues to persist. In this study, we systematically simulated various W–ZrC interfaces merging W and ZrC surfaces with different orientations. Subsequently, we evaluated their stabilities and explained the corresponding stabilities in terms of the nature of bonding and charge-transfer processes at the interface. We find ZrC(111)–W(110) is the most stable interface with higher adhesive energy than the other interfaces. The additional stability associated with the ZrC(111)–W(110) results from significant interface reconstruction. Three layers of W and ZrC adjacent to the interface are involved in the charge-transfer process leading to stronger ionic bonds in ZrC(111)–W(110) as compared to the other potential candidate: ZrC(100)–W(100). The C and W atoms are found to be displaced from their symmetric position during the reconstruction process at the interface to facilitate stronger bonds with shorter W–C and W–Zr bonds in ZrC(111)–W(110) as compared to ZrC(100)–W(100). This leads to stronger covalent bonds in ZrC(111)–W(110) than that in ZrC(100)–W(100). Therefore, we conclude that the stronger covalent and ionic forces in ZrC(111)–W(110) than those in ZrC(100)–W(100) are responsible for making ZrC(111)–W(110) to be the most stable interface. In conclusion, this study addresses the long-standing question of the most stable W–ZrC interface and derives a number of implications for other W-transition metal carbide interfaces which are potential candidates for improving the mechanical properties of plasma facing materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

First-principles Study of the Tritium Species Diffusion Across Ni-Zircaloy-4 Getter Interface

Tritium is a critical fuel component for experimental nuclear fusion reactors (like tokamaks), typically used in combination with deuterium. In tritium-producing burnable absorber rods (TPBARs), due to its high lithium density, LiAlO2 is used in the form of an annular ceramic pellet enriched with the Li_6 isotope located between the Zircaloy-4 liner and nickel-plated Zircaloy-4 tritium getter. Employing DFT, we explored the tritium diffusion across the pellet and getter.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Leveraging Triphenylphosphine-Containing Polymers to Explore Design Principles for Protein-Mimetic Catalysts

Complex interactions between noncoordinating residues are significant yet commonly overlooked components of macromolecular catalyst function. While these interactions have been demonstrated to impact binding affinities and catalytic rates in metalloenzymes, the roles of similar structural elements in synthetic polymeric catalysts remain underexplored. Using a model Suzuki–Miyuara cross-coupling reaction, we performed a series of systematic studies to probe the interconnected effects of metal–ligand cross-links, electrostatic interactions, and local rigidity in polymer catalysts. To achieve this, a novel bifunctional triphenylphosphine acrylamide (BisTPPAm) monomer was synthesized and evaluated alongside an analogous monofunctional triphenylphosphine acrylamide (TPPAm). In model copolymer catalysts, increased initial reaction rates were observed for copolymers untethered by Pd complexation (BisTPPAm-containing) compared to Pd-cross-linked catalysts (TPPAm-containing). Further, incorporating local rigidity through secondary structure-like and electrostatic interactions revealed nonmonotonic relationships between composition and the reaction rate, demonstrating the potential for tunable behavior through secondary-sphere interactions. Lastly, through rigorous cheminformatics featurization strategies and statistical modeling, we quantitated relationships between chemical descriptors of the substrate and reaction conditions on catalytic performance. Collectively, these results provide insights into relationships among the composition, structure, and function of protein-mimetic catalytic copolymers.

Catalysts↗
DOE OSTI2021

A Component-Sizing Methodology for a Hybrid Electric Vehicle Using an Optimization Algorithm

Many leading companies in the automotive industry have been putting tremendous effort into developing new powertrains and technologies to make their products more energy efficient. Evaluating the fuel economy benefit of a new technology in specific powertrain systems is straightforward; and, in an early concept phase, obtaining a projection of energy efficiency benefits from new technologies is extremely useful. However, when carmakers consider new technology or powertrain configurations, they must deal with a trade-off problem involving factors such as energy efficiency and performance, because of the complexities of sizing a vehicle’s powertrain components, which directly affect its energy efficiency and dynamic performance. As powertrains of modern vehicles become more complicated, even more effort is required to design the size of each component. This study presents a component-sizing process based on the forward-looking vehicle simulator “Autonomie” and the optimization algorithm “POUNDERS”; the supervisory control strategy based on Pontryagin’s Minimum Principle (PMP) assures sufficient computational system efficiency. We tested the process by applying it to a single power-split hybrid electric vehicle to determine optimal values of gear ratios and each component size, where we defined the optimization problem as minimizing energy consumption when the vehicle’s dynamic performance is given as a performance constraint. The suggested sizing process will be helpful in determining optimal component sizes for vehicle powertrain to maximize fuel efficiency while dynamic performance is satisfied. Indeed, this process does not require the engineer’s intuition or rules based on heuristics required in the rule-based process.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Phonon screening and dissociation of excitons at finite temperatures from first principles

The properties of excitons, or correlated electron–hole pairs, are of paramount importance to optoelectronic applications of materials. A central component of exciton physics is the electron–hole interaction, which is commonly treated as screened solely by electrons within a material. However, nuclear motion can screen this Coulomb interaction as well, with several recent studies developing model approaches for approximating the phonon screening of excitonic properties. While these model approaches tend to improve agreement with experiment, they rely on several approximations that restrict their applicability to a wide range of materials, and thus far they have neglected the effect of finite temperatures. Here, we develop a fully first-principles, parameter-free approach to compute the temperature-dependent effects of phonon screening within the ab initio GW -Bethe–Salpeter equation framework. We recover previously proposed models of phonon screening as well-defined limits of our general framework, and discuss their validity by comparing them against our first-principles results. We develop an efficient computational workflow and apply it to a diverse set of semiconductors, specifically AlN, CdS, GaN, MgO, and SrTiO 3 . We demonstrate under different physical scenarios how excitons may be screened by multiple polar optical or acoustic phonons, how their binding energies can exhibit strong temperature dependence, and the ultrafast timescales on which they dissociate into free electron–hole pairs.

Science & Technology - Other Topics↗
DOE OSTI2024

Rigidity‐Driven Structural Isomers in the NaCl–Ga 2 S 3 System: Implications for Energy Storage

Alternative energy sources require the search for innovative materials with promising functionalities. Systems with unusual chemical properties represent an insufficiently explored domain, concealing unexpected features. Using diffraction and Raman spectroscopy over a wide temperature range, supported by first‐principles simulations, a rare phenomenon is unveiled: phase‐dependent chemical interactions between binary components in the NaCl–Ga 2 S 3 system. In this unique occurrence, previously intact binary crystalline species transform upon melting into mixed liquid structural isomers, forming bonds with new partners. The chemical combinatorics appears to be fully reversible for stable crystals and liquids. Despite this, rapidly frozen glasses out of thermodynamic equilibrium remain in a metastable isomeric state, offering remarkable properties, particularly a high room‐temperature Na + conductivity, comparable to the best sodium halide superionic conductors and therefore encouraging for sodium solid‐state batteries and energy applications. A rigidity paradigm is responsible for the observed phenomenon, as the extremely constrained Ga 2 S 3 crystal lattice does not survive viscous flow, breaking up at a short‐range level. The removal of rigidity constraints and dense packing leads to a significant increase in empty space, which is the origin of high sodium diffusivity. Broadly, the rigidity‐driven structural isomerism opens up an inspiring path to the discovery of atypical materials.

25 ENERGY STORAGE↗
DOE OSTI2025

High gas-pressure apparatus for nonlinear X-ray propagation and reshaping via stimulated X-ray Raman scattering

Abstract We describe an experimental setup for non-linear interaction and propagation of ultrashort and intense x-ray free-electron laser (XFEL) pulses in a dense gas. It allows one to provide high, but adjustable, target-gas pressures of up to 6 bar within a vacuum environment of 3∙10 − 3 mbar or better. The setup enables investigation of intense x-ray propagation in an optically thick medium with minimal absorption loss of the unfocused beam outside of the target. As an application, we demonstrate the amplification of spectrally-resolved stimulated x-ray Raman scattering (SXRS) in dense neon gas, where the most intense inner part of the beam is almost completely absorbed. As a result, in the inner part of the beam, the SXRS signal exceeds the residual XFEL pulse by a factor of around two. In principle, this reshaping effect allows for a spatial separation of the two spectral components, i.e., the driving pulse and the SXRS signal.

Magunia, Alexander↗
DOE OSTI2021

Differentiable programming for online training of a neural artificial viscosity function within a staggered grid Lagrangian hydrodynamics scheme

Lagrangian methods to solve the inviscid Euler equations produce numerical oscillations near shock waves. A common approach to reducing these oscillations is to add artificial viscosity (AV) to the discrete equations. The AV term acts as a dissipative mechanism that attenuates oscillations by smearing the shock across a finite number of computational cells. However, AV introduces several control parameters that are not determined by the underlying physical model, and hence, in practice are tuned to the characteristics of a given problem. We seek to improve the standard quadratic-linear AV form by replacing it with a learned neural function that reduces oscillations relative to exact solutions of the Euler equations, resulting in a hybrid numerical-neural hydrodynamic solver. Because AV is an artificial construct that exists solely to improve the numerical properties of a hydrodynamic code, there is no offline ‘viscosity data’ against which a neural network can be trained before inserting into a numerical simulation, thus requiring online training. We achieve this via differentiable programming, i.e. end-to-end backpropagation or adjoint solution through both the neural and differential equation code, using automatic differentiation of the hybrid code in the Julia programming language to calculate the necessary loss function gradients. A novel offline pre-training step accelerates training by initializing the neural network to the default numerical AV scheme, which can be learned rapidly by space-filling sampling over the AV input space. We find that online training over early time steps of simulation is sufficient to learn a neural AV function that reduces numerical oscillations in long-term hydrodynamic shock simulations. These results offer an early proof-of-principle that online differentiable training of hybrid numerical schemes with novel neural network components can improve certain performance aspects existing in purely numerical schemes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Distributed Inference with Sparse and Quantized Communication

Here, we consider the problem of distributed inference where agents in a network observe a stream of private signals generated by an unknown state, and aim to uniquely identify this state from a finite set of hypotheses. We focus on scenarios where communication between agents is costly, and takes place over channels with finite bandwidth. To reduce the frequency of communication, we develop a novel event-triggered distributed learning rule that is based on the principle of diffusing low beliefs on each false hypothesis. Building on this principle, we design a trigger condition under which an agent broadcasts only those components of its belief vector that have adequate innovation, to only those neighbors that require such information. We prove that our rule guarantees convergence to the true state exponentially fast almost surely despite sparse communication, and that it has the potential to significantly reduce information flow from uninformative agents to informative agents. Next, to deal with finite-precision communication channels, we propose a distributed learning rule that leverages the idea of adaptive quantization. We show that by sequentially refining the range of the quantizers, every agent can learn the truth exponentially fast almost surely, while using just 1 bit to encode its belief on each hypothesis. For both our proposed algorithms, we rigorously characterize the trade-offs between communication-efficiency and the learning rate.

42 ENGINEERING↗
DOE OSTI2023

Open Water Blade Strain Measurements on a Vertical-Axis Tidal Turbine

Open-water testing of marine renewable energy devices represents a significant milestone and hurdle for research teams and companies that seek to reduce the levelized cost of energy to allow these devices to compete in the open electrical generation market. For open-water testing of tidal energy converters (TECs), accurate measurements of loading characteristics on the blades and other structural components correlated with power performance metrics can be invaluable to further refine design principles and models, allowing continued improvement and cost reductions of new turbine designs. This paper will describe the modifications and additions made to a TEC system to achieve time-correlated blade strain measurements during full turbine operation along with a discussion on the overall impacts the required modifications had on the unmodified turbine.

mechanical loads↗
DOE OSTI2025

Operation at Reduced Atmospheric Pressure and Concept of Reliability Redundancy for Optimized Design of Insulation Systems

Electrified transportation is calling for insulation design criteria that is adequate to provide elevated levels of power density, power dynamics and reliability. Increasing voltage levels are expected to cause accelerated intrinsic and extrinsic aging effects which will not be easily predictable at the design stage due to a lack of suitable modeling. Designing reliable insulation systems would require finding solutions able to control accelerated aging due to an unpredictable increase of intrinsic stresses and the onset of extrinsic stresses as partial discharges. This paper proposes the concept of reliability redundancy for the insulation design of aerospace electrical asset components, which is also validated at lower-than-standard atmospheric pressure. The principle is that extrinsic-aging-free design might be achieved upon determining the aging stress or abnormal service stresses distribution and being sure that aging will not generate conditions that can incept extrinsic aging (partial discharges) during operation life. However, such information is never, in practice, fully available to insulation system designers. Hence, especially in critical applications such as electrified aircraft, aerospace, and combat ships a further level of reliability should be added to a partial-discharge-free design, which can consist of the use of corona-resistant materials and/or of life models able to consider the accelerated aging effect of partial discharges (or any other type of extrinsic-accelerated aging factor). Innovative life modeling considering both extrinsic and intrinsic aging stresses, insulating material testing to estimate model parameters, and a metric for quantifying the extent of corona (or partial discharge) resistance can lead to establishing feasibility and limit conditions for optimized or fully reliability-redundant design. It is shown in the paper that if an extrinsic-aging-free design is not feasible, and it is therefore replaced by a redundant design, a further level of reliability redundancy can be provided by effective condition monitoring plans.

Montanari, Gian Carlo↗
DOE OSTI2021

Machine-Learned Manifold-Based Models for Large Eddy Simulation of Turbulent Combustion

Reduced-order manifold combustion models are commonly used to lower the cost of reacting Large Eddy Simulations (LES) and may be derived either from physical principles as in flamelet models or from data-driven methods like Principal Component Analysis (PCA). In either case, neural networks are increasingly used as part of these models to provide a nonlinear mapping between a small set of pre-defined variables that parameterize the manifold and outputs of interest, such as reaction rates. In this work, we propose a new manifold-based modeling approach that combines the definition of the manifold-parameterizing variables (linear combinations of species), the nonlinear mapping to the outputs, and closure of filtered quantities for LES into the structure of a single neural network. This allows the process used to train the neural network to simultaneously optimize both the functional form of the model and the identities of the inputs to the model. The new approach can flexibly incorporate thermochemical data from any combustion system; if trained on data from 1D flames it can be interpreted as an optimized flamelet model, but it can also be used to learn models from data from more complex configurations. This work presents a priori evaluations of the new approach in both contexts. Evaluation using data from 1D premixed flames demonstrates the physical interpretability of the manifold variables generated by the new approach. Evaluation using data from direct numerical simulations of turbulent flames shows improved predictions relative to either flamelet or PCA-based models in a more complex configuration.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Chemical short-range order in derivative Cr–Ta–Ti–V–W high entropy alloys from the first-principles thermodynamic study

The development of high-entropy alloys (HEAs) focuses on exploring compositional regions in multi-component systems with all alloy elements in equal or near-equal atomic concentrations. Initially it was based on the main idea that high mixing configurational entropy contributions to the alloy free energy could promote the formation of a single solid solution phase. By using the ab-initio based Cluster Expansion (CE) Hamiltonian model constructed for the quinary bcc Cr–Ta–Ti–V–W system in combination with Monte Carlo (MC) simulations, we show that the phase stability and chemical short-range order (SRO) of the equiatomic quinary and five sub-quaternary systems, as well as their derivative alloys, can dramatically change the order–disorder transition temperatures (ODTT) as a function of alloy compositions. In particular, it has been found, that the equiatomic quaternary Ta–Ti–V–W and Cr–Ta–Ti–W alloys had the lowest order–disorder transition temperature (500 K) among all the analysed equiatomic compositions. In all investigated alloy systems, the strongest chemical ordering has been observed between Cr and V, which led to the conclusion that decreasing the concentration of either Cr or V might be beneficial in terms of decreasing the ODTT. It also predicts that increasing concentration of Ti significantly decreases the ODTT. Our analysis of chemical SRO as a function of alloy composition allows to understand the microstructure evolution of HEAs as a function of temperature in excellent agreement with available experimental observations. Importantly, our free energy of mixing and SRO calculations predict that the origin of precipitates formed by Cr- and V-rich in the sub-quaternary Cr–Ta–V–W system is driven by the thermodynamics. The modelling results are in an excellent agreement with experimental observation of Cr and V segregation in the W 0.38 Ta 0.36 Cr 0.15 V 0.11 alloy which in turns shows an exceptional radiation resistance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗