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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Modelling single atom catalysts for water splitting and fuel cells: A tutorial review

Here, in this tutorial review, we report the state-of-the-art of the modeling approaches of Single Atom Catalysts (SAC) for water splitting and fuel cells reactions. The discussion applies for Hydrogen Evolution Reaction (HER), Oxygen Reduction Reaction (OER), Hydrogen Oxidation Reaction (HOR), and Oxygen Reduction Reaction (ORR). The main scope of this work is to underline the relevant aspects of SACs modelling. On the one hand, the review could help computational chemists aiming to start the study of SACs. On the other hand, experimentalists could find the critical analysis of DFT results of interest to understand better the strengths and weaknesses of simulations, and how to interpret computational results. After an introductory section of SACs, we start by briefly presenting the state-of-the-art methodologies. Then, we analyze the critical aspects for a reliable prediction of the electronic properties, and we discuss the robustness of the structural models and ways to validate them. Furthermore, we discuss the main approaches to predict catalytic activity and selectivity, which is the final goal of the computational catalysis. We conclude this review with a critical analysis of the current challenges in the field, and the main limitations of the modeling approaches that are described.

25 ENERGY STORAGE↗
DOE OSTI2020

Tutorial review on structure – dendrite growth relations in metal battery anode supports

This tutorial review explains the emerging understanding of the surface and bulk chemistry – electrochemical performance relations in anode supports (aka secondary current collectors, substrates, templates, hosts) for lithium, sodium and potassium metal batteries (LMBs, SMBs or NMBs, and KMBs or PMBs). In relation to each section, the possible future research directions that may yield both new insight and improved cycling behavior are explored. Representative case studies from Li, Na and K metal anode literature are discussed. The tutorial starts with an overview of the solid electrolyte interphase (SEI), covering both the “classic” understanding of the SEI structure and the “modern” insights obtained by site-specific cryogenic stage TEM analysis. Next, the multiple roles of supports in promoting cycling stability are detailed. Without an optimized support architecture, the metal–electrolyte interface becomes geometrically unstable at a lower current density and cycle number. Taking into consideration the available literature on LMBs, SMBs and KMBs, it is concluded that effective architectures are geometrically complex and electrochemically lithiophilic, sodiophilic or potassiophilic, so as to promote conformal electrochemical wetting of the metal during plating/stripping. One way that philicity is achieved is through support oxygen surface chemistry, which yields a reversibly reactive metal–support interface. Examples of this include the well-known oxygen–carbon moieties in reduced graphene oxide (rGO), as well as classic ion battery reversible conversion reaction oxides such as SnO 2 . Unreactive surfaces lead to dewetted island growth of the metal, which is a precursor to dendrites, and possibly to non-uniform dissolution. Surveying the literature on various Li, Na and K metal supports, it is concluded that the key bulk thermodynamic property that will predict electrochemical wetting behavior is the enthalpy of infinite solution (Δ sol H ∞ ) of the metal (solute) into the support (solvent). Large and negative Δ sol H ∞ promotes uniform metal wetting on the support surface, corresponding to relatively low plating overpotential. Positive Δ sol H ∞ promotes dewetted islands and a relatively high overpotential. This simple rule explains a broad range of studies on Li, Na and K metal – support interactions, including the previously reported correlation between mutual solubility and wetting.

25 ENERGY STORAGE↗
DOE OSTI2024

A tutorial review of machine learning-based model predictive control methods

Abstract This tutorial review provides a comprehensive overview of machine learning (ML)-based model predictive control (MPC) methods, covering both theoretical and practical aspects. It provides a theoretical analysis of closed-loop stability based on the generalization error of ML models and addresses practical challenges such as data scarcity, data quality, the curse of dimensionality, model uncertainty, computational efficiency, and safety from both modeling and control perspectives. The application of these methods is demonstrated using a nonlinear chemical process example, with open-source code available on GitHub. The paper concludes with a discussion on future research directions in ML-based MPC.

Wu, Zhe [Department of Chemical and Biomolecular E↗
DOE OSTI2021

Epitaxial oxide thin films for oxygen electrocatalysis: A tutorial review

Epitaxial thin films can offer unprecedented definition of an electrocatalyst surface, defining the crystallographic orientation, interaction with a current collector, and providing an atomically flat surface for quantitative spectroscopy yielding mechanistic insight. This review introduces experts in thin films to the important parameters of electrochemical setups, techniques, and methods for quantifying electrocatalytic activity and comparing it across the literature. Examples are drawn from the literature measuring oxygen electrocatalysis on epitaxial oxide thin films. Furthermore, we share best practices in the robust measurement of intrinsic activity of thin films, including methods of electrical contact and assessment of charge transport in situ. We conclude by highlighting recent insights from epitaxial films in understanding oxygen electrocatalysis.

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

Principles and applications of x-ray light sources driven by laser wakefield acceleration

One of the most prominent applications of modern particle accelerators is the generation of radiation. In a synchrotron or an x-ray free electron laser (XFEL), high energy electrons oscillating in periodic magnetic structures emit bright x rays. In spite of their scientific appeal that will remain evident for many decades, one limitation of synchrotrons and XFELs is their typical mile-long size and their cost, which often limits access to the broader scientific community. Here, this tutorial reviews the principles and prospects of using plasmas produced by intense lasers as particle accelerators and x-ray light sources, as well as some of the applications they enable. A plasma is an ionized medium that can sustain electrical fields many orders of magnitude higher than that in conventional radio frequency accelerator structures and can be used to accelerate electrons. When short, intense laser pulses are focused into a gas, it produces electron plasma waves in which electrons can be trapped and accelerated to GeV energies. This process, laser-wakefield acceleration (LWFA), is analogous to a surfer being propelled by an ocean wave. Many radiation sources, from THz to gamma-rays, can be produced by these relativistic electrons. This tutorial reviews several LWFA-driven sources in the keV-MeV photon energy range: betatron radiation, inverse Compton scattering, bremsstrahlung radiation, and undulator/XFEL radiation. X rays from laser plasma accelerators have many emerging applications. They can be used in innovative and flexible x-ray imaging and x-ray absorption spectroscopy configurations, for use in biology, industry, and high-energy density science.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

State preparation and evolution in quantum computing: a perspective from Hamiltonian moments

Quantum algorithms on the noisy intermediate-scale quantum (NISQ) devices are expected to simulate quan- tum systems that are classically intractable to demonstrate quantum advantages. However, the non-negligible gate error on the NISQ devices impedes the conventional quantum algorithms to be implemented. Practical strategies usually exploit hybrid quantum-classical quantum algorithms to demonstrate potentially useful ap- plications of quantum computing in the NISQ era. Among the numerous hybrid quantum-classical algorithms, recent efforts highlight the development of quantum algorithms based upon quantum computed Hamiltonian moments, ?f|Hˆn|f? (n = 1, 2, · · · ), with respect to quantum state |f?. In this tutorial, we will give a brief review of these quantum algorithms with focuses on the typical ways of computing Hamiltonian moments using quantum hardware and improving the accuracy of the estimated state energies based on the quantum computed moments. Furthermore, we will present a tutorial to show how we can measure and compute the Hamiltonian moments of a four-site Heisenberg model, and compute the energy and magnetization of the model utilizing the imaginary time evolution in the real IBM-Q NISQ hardware environment. Along this line, we will further discuss some practical issues associated with these algorithms. We will conclude this tutorial review by overviewing some possible developments and applications in this direction in the near future.

Aulicino, Joseph C.↗
DOE OSTI2020

Harnessing the surface structure to enable high-performance cathode materials for lithium-ion batteries

The ever-increasing demand for high-performance batteries have been driving the fundamental understanding of the crystal/surface structural and electrochemical properties of intercalation cathode materials, among which the olivine-type, spinel and layered lithium transition metal oxide materials have received particular attention in the past decade due to their successful commercialization. While the most current studies focus on the macroscopic and bulk crystal structure of these materials, our previous work suggests that, as a confined region where charge transfer takes place, the interfacial structures of cathode materials largely dictate their electrochemical performances due to the structural symmetry breaking from 3D (bulk) to 2D (surface), which leads to reconstructions under the different chemical/electrochemical conditions. By summarizing works in this subject and offering our perspectives, this tutorial review will reveal for the first time the correlation between surface structure and interface reconstruction at atomic/molecular scales and their direct impact on corresponding electrochemical performances. More importantly, by extending the knowledge obtained from these three well-studied system, we believe that the same principles established could universally apply to other cathode materials that have been the frontiers of new battery chemistries.

25 ENERGY STORAGE↗
DOE OSTI2020

Thermodynamic and kinetic hydricity of transition metal hydrides

The prevalence of transition metal-mediated hydride transfer reactions in chemical synthesis, catalysis, and biology has inspired the development of methods for characterizing the reactivity of transition metal hydride complexes. Thermodynamic hydricity represents the free energy required for heterolytic cleavage of the metal–hydride bond to release a free hydride ion, H - , as determined through equilibrium measurements and thermochemical cycles. Kinetic hydricity represents the rate of hydride transfer from one species to another, as measured through kinetic analysis. This tutorial review describes the common methods for experimental and computational determination of thermodynamic and kinetic hydricity, including advice on best practices and precautions to help avoid pitfalls. The influence of solvation on hydricity is emphasized, including opportunities and challenges arising from comparisons across several different solvents. Connections between thermodynamic and kinetic hydricity are discussed, and opportunities for utilizing these connections to rationally improve catalytic processes involving hydride transfer are highlighted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Understanding, discovery, and synthesis of 2D materials enabled by machine learning

Machine learning (ML) is becoming an effective tool for studying 2D materials. Taking as input computed or experimental materials data, ML algorithms predict the structural, electronic, mechanical, and chemical properties of 2D materials that have yet to be discovered. Such predictions expand investigations on how to synthesize 2D materials and use them in various applications, as well as greatly reduce the time and cost to discover and understand 2D materials. This tutorial review focuses on the understanding, discovery, and synthesis of 2D materials enabled by or benefiting from various ML techniques. Here, we introduce the most recent efforts to adopt ML in various fields of study regarding 2D materials and provide an outlook for future research opportunities. The adoption of ML is anticipated to accelerate and transform the study of 2D materials and their heterostructures.

2D Materials↗
DOE OSTI2021

Compartmentalisation of molecular catalysts for nonorthogonal tandem catalysis

The development of nonorthogonal tandem catalysis enables the use of a combination of arbitrary catalysts to rapidly synthesize complex products in a substainable, efficient, and timely manner. The key is to compartmentalise the molecular catalysts, thereby overcoming inherent incompatibilities between individual catalysts or reaction conditions. This tutorial review analyses the development of the past two decades in the field of nonorthogonal tandem catalysis with an emphasis on compartmentalisation strategies. Here, we highlight design principles of functional materials for compartmentalisation and suggest future directions in the field of nonorthogonal tandem catalysis.

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

From bulk to interface: electrochemical phenomena and mechanism studies in batteries via electrochemical quartz crystal microbalance

Understanding the bulk and interfacial behaviors during the operation of batteries (e.g., Li-ion, Na-ion, Li–O 2 batteries, etc.) is of great significance for the continuing improvement of the performance. Electrochemical quartz crystal microbalance (EQCM) is a powerful tool to this end, as it enables in situ investigation into various phenomena, including ion insertion/deinsertion within electrodes, solid nucleation from the electrolyte, interphasial formation/evolution and solid–liquid coordination. As such, EQCM analysis helps to decipher the underlying mechanisms both in the bulk and at the interface. This tutorial review will present the recent progress in mechanistic studies of batteries achieved by the EQCM technology. Here, the fundamentals and unique capability of EQCM are first discussed and compared with other techniques, and then the combination of EQCM with other in situ techniques is also covered. In addition, the recent studies utilizing EQCM technologies in revealing phenomena and mechanisms of various batteries are reviewed. Perspectives regarding the future application of EQCM in battery studies are given at the end.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗