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At least 1,081 records · Page 60

Constrained optimization framework for interface-aware sub-scale dynamics discrete closure model for multimaterial cells in Lagrangian cell-centered hydrodynamics

In this paper, we present the new discrete optimization-based interface-aware sub-scale dynamics (IA-SSD) closure model for multimaterial cells for Lagrangian cell-centered hydrodynamics. For the multimaterial cell, the kinematic and thermodynamic properties (e.g., velocity, density, pressure and internal energy) will typically vary between the materials. The discrete closure model is responsible for an accurate update of the thermodynamic states of the individual material components in the multimaterial cell, and for determining the nodal forces that move the vertices of the cell. The IA-SSD closure model consists of two stages — a bulk stage followed by a sub-scale stage. During the bulk stage, the total change in the volume of the cell, total force applied to the cell, and total work done on the cell are distributed between the materials to update their volume, velocity and total energy. This distribution is performed using volume fractions of the materials. During the second stage, sub-scale interactions of the materials inside the multimaterial cell are taken into account. At this stage, information about the topology of the materials inside the multimaterial cell is used, allowing the orientations of internal interfaces to be included in the model. Each material interacts in a pair-wise fashion with the materials with which it has a common boundary. The interactions are based on the solution of the acoustic Riemann problem between each pair of materials and are limited using physically justified constraints: positivity of volume, positivity of internal energy, and controlled rate of pressure relaxation. To determine the values of the limiter coefficients, a constrained-optimization framework is employed using a quadratic objective function with linear constraints. It is a first-of-its kind application of constrained optimization to develop discrete closure models in a more rigorous fashion. The pair-wise interaction between materials is essentially one dimensional in the direction that is normal to interface. Finally, for this reason, we demonstrate in this paper the performance of our new model on one dimensional numerical examples.

97 MATHEMATICS AND COMPUTING↗

Computational Fermi Level Engineering and Doping-Type Conversion of Mg:Ga 2 O 3 via Three-Step Synthesis Process

Gallium oxide (Ga 2 O 3 ) is being actively explored for electronics that can operate at high power, temperature, and frequency as well as for deep-ultraviolet optoelectronics and other applications due to its ultra-wide bandgap (UWBG) and low projected fabrication cost of large-size and high-quality crystals. Efficient n-type doping of monoclinic beta-phase of Ga 2 O 3 has been achieved, but p-type doping faces fundamental obstacles due to compensation, deep acceptor levels, and the polaron transport mechanism of free holes. However, aside from the challenges of achieving p-type conductivity, plenty of opportunity exists to engineer the position of the Fermi level for improved design of Ga 2 O 3 -based devices. We use first-principles defect theory and defect equilibrium calculations to simulate a three-step growth-annealing-quench synthesis protocol for hydrogen-assisted Mg doping in ß-Ga 2 O 3 . The simulations take into account the gas phase equilibrium between H 2 , O 2 , and H 2 O, which determines the H chemical potential. We predict Ga 2 O 3 doping-type conversion to a net p-type regime after growth under reducing conditions in the presence of H2 followed by O-rich annealing, which is a similar process to Mg acceptor activation by H removal in GaN. For equilibrium annealing with re-equilibration of compensating O vacancies, there is an optimal temperature that maximizes the Ga 2 O 3 net acceptor density for a given Mg doping level; the acceptor density is further increased in the non-equilibrium annealing scenario without re-equilibration. After quenching to operating temperature, the Ga 2 O 3 Fermi level drops below mid-gap down to about 1.5 eV above the valence band maximum, creating a significant number of uncompensated neutral Mg Ga 0 acceptors. The resulting free hole concentration in Ga 2 O 3 is very low even at elevated operating temperature (~10 8 cm -3 at 400°C) due to the deep energy level of these Mg acceptors, and hole conductivity is further impeded by the polaron hopping mechanism. However, the Fermi-level reduction and suppression of free electron density in this doping-type converted (NA>ND) Ga 2 O 3 material are important for improved designs of Ga 2 O 3 electronic devices. These results illustrate the power of computational predictions not only for new materials but also for their synthesis science.

36 MATERIALS SCIENCE↗

Optimizing Li‐Excess Cation‐Disordered Rocksalt Cathode Design Through Partial Li Deficiency

Li-excess disordered rocksalts (DRXs) are emerging as promising cathode materials for Li-ion batteries due to their ability to use earth-abundant transition metals. In this work, a new strategy based on partial Li deficiency engineering is introduced to optimize the overall electrochemical performance of DRX cathodes. Specifically, by using Mn-based DRX as a proof-of-concept, it is demonstrated that the introduction of cation vacancies during synthesis (e.g., Li 1.3-x Mn 2+ 0.4-x Mn 3+ x Nb 0.3 O 1.6 F 0.4 , x = 0, 0.2, and 0.4) improves both the discharge capacity and rate performance due to the more favored short-range order in the presence of Mn3+. Density functional theory calculations and Monte Carlo simulations, in combination with spectroscopic tools, reveal that introducing 10% vacancies (Li 1.1 Mn 2+ 0.2 Mn 3+ 0.2 Nb 0.3 O 1.6 F 0.4 ) enables both Mn 2+ /Mn 3+ redox and excellent Li percolation. However, a more aggressive vacancy doping (e.g., 20% vacancies in Li 0.9 Mn 3+ 0.4 Nb 0.3 O 1.6 F 0.4 ) impairs performance because it induces phase separation between an Mn-rich and a Li-rich phase.

25 ENERGY STORAGE↗

Target Selection and Validation of DESI Quasars

The Dark Energy Spectroscopic Instrument (DESI) survey will measure large-scale structures using quasars as direct tracers of dark matter in the redshift range 0.9 < z < 2.1 and using Lyα forests in quasar spectra at z > 2.1. We present several methods to select candidate quasars for DESI, using input photometric imaging in three optical bands (g, r, z) from the DESI Legacy Imaging Surveys and two infrared bands (W1, W2) from the Wide-field Infrared Survey Explorer. These methods were extensively tested during the Survey Validation of DESI. In this paper, we report on the results obtained with the different methods and present the selection we optimized for the DESI main survey. The final quasar target selection is based on a random forest algorithm and selects quasars in the magnitude range of 16.5 < r < 23. Visual selection of ultra-deep observations indicates that the main selection consists of 71% quasars, 16% galaxies, 6% stars, and 7% inconclusive spectra. Using the spectra based on this selection, we build an automated quasar catalog that achieves a fraction of true QSOs higher than 99% for a nominal effective exposure time of ~1000 s. With a 310 deg -2 target density, the main selection allows DESI to select more than 200 deg -2 quasars (including 60 deg -2 quasars with z > 2.1), exceeding the project requirements by 20%. The redshift distribution of the selected quasars is in excellent agreement with quasar luminosity function predictions.

79 ASTRONOMY AND ASTROPHYSICS↗

Toward a QUBO-Based Density Matrix Electronic Structure Method

Density matrix electronic structure theory is used in many quantum chemistry methods to “alleviate” the computational cost that arises from directly using wave functions. Although density matrix based methods are computationally more efficient than wave function based methods, significant computational effort is involved. Because the Schrödinger equation needs to be solved as an eigenvalue problem, the time-to-solution scales cubically with the system size in mean-field type approaches such as Hartree–Fock and density functional theory and is solved as many times in order to reach charge or field self-consistency. We hereby propose and study a method to compute the density matrix by using a quadratic unconstrained binary optimization (QUBO) solver. This method could be useful to solve the problem with quantum computers and, more specifically, quantum annealers. Our proposed approach is based on a direct construction of the density matrix using a QUBO eigensolver. We explore the main parameters of the algorithm focusing on precision and efficiency. We show that, while direct construction of the density matrix using a QUBO formulation is possible, the efficiency and precision have room for improvement. Moreover, calculations performed with quantum annealing on D-Wave’s new Advantage quantum computer are compared with results obtained with classical simulated annealing, further highlighting some problems of the proposed method. Finally, we also suggest alternative methods that could lead to a more efficient QUBO-based density matrix construction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modular Undersea Compressed Air Energy Storage (UCAES) System

This project has been devoted to the design, optimization, and cost analysis of a unique power plant with integral energy storage. The proposed facility combines a novel underwater compressed air energy storage (UCAES) system with a customized gas turbine generator, providing exceptional power management and overall efficiency. Unlike conventional CAES, opportunities for underwater storage are plentiful and proximal to the power grid. The UCAES system provides coastal and island communities a practical means for managing the volatility of large-scale wind and solar power resources. The result is higher renewable energy absorption and improved electrical reliability with reduced fossil fuel consumption. The UCAES power plant is composed of three major subsystems: The underwater air containment system (ACS), the air transport pipe (ATP), and the land-based power conversion system (PCS). The underwater ACS is made up of modular concrete shell units, structurally optimized for minimal material usage while employing conventional production methods and equipment. Each shell is designed to receive and control loose fill or gravel, serving as the ballast. The static nature of the final structures make them an asset to marine habitats and includes features intended to permit safe and cost-effective deployment. The ATP Connects the ACS modules to each other and to the on-land power conversion system and utilizes high density polyethylene (HDPE) pipe for low cost and long life. The PCS Houses the turbine-generator ‘expander modules’, with peak capacity of 12.3 MWe each, engineered from existing gas turbine equipment and includes electrically driven commercial 3-stage intercooled centrifugal compressors, each nominally drawing 6.6 MWe when matching the turbine flow requirements. The subsystems listed above are designed with the intent to serve as building-blocks to achieve a peak power output rating in the 40 to 120 MWe range, with 0.25 to 4 hours of energy storage capacity. The modular facility with integral energy storage provides some remarkable transient maneuvers and load-following features unachievable by competing technologies. The system can operate as a dispatchable power plant with a fuel-to-electric efficiency over 41%; substantially better that the average existing Hawaiian peak power generation assets. Optimal efficiency can be maintained while load-following due to modular PCS design and is operable with a range of liquid or gaseous fuels while meeting the most stringent California (CARB) emission standards. The system can operate as a peaking energy plant in discharge mode. Power ramp-up equivalent to 215% of continuous load rating within 1 second accomplished by simply turning off the electric compressor(s). Contrarily, the system can offer energy absorption during periods of grid surplus generation. The electric compressors may be sequenced on to absorb power within seconds. More moderate transitions are easily achieved with standard compressor control functions. The system offers unique features as compared to energy storage systems. ‘Round-trip efficiency’, as calculated by industry standard methods, is in the 90% range. The PCS equipment has a mean-time between overhauls of 80,000 hours, with maintenance costs of less than $0.005/kW-hr of electricity delivered. The underwater ACS structures and piping employ materials and designs specified to achieve a 75 year life. With the underwater containment modules qualified as a marine habitat, there would be no decommissioning costs. In conjunction with the engineering work invested in the design of the UCAES power plant, Brayton Energy has employed a team of manufacturing specialists, marine construction engineers, and power industry experts to create a comprehensive economic model that captures the many site-related variables and configuration options. The cost results and methodology have been validated by suppliers, engineers, and deployment specialists through a detailed case study on Hawaii. While creation of the parametric cost model was based on inputs specific to Hawaii, the proposed construction and deployment steps were chosen to be general enough to allow extrapolation across locations world-wide. Analysis of the proposed system shows it to be a viable option and addresses the principal challenges described by the Department of Energy by offering competitive costs, validated safety and reliability, consideration of the regulatory environment, and utilization of industry accepted practices and equipment. The UCAES system is recommended for immediate consideration in Hawaii. Estimation of time to complete planning, design, and construction of the facility is anticipated to take 3 to 5 years. Other coastal and island communities world-wide should realize similar benefits; as the results presented in this report are considered generally transferable to other locations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

High-Performance First-Principles Molecular Dynamics for Predictive Theory and Modeling

This project focused on developing high-performance software tools for First-Principles Molecular Dynamics (FPMD) simulations, and applying them in investigations of materials relevant to energy conversion processes. FPMD is an atomistic simulation method that combines a quantum-mechanical description of electronic structure with the statistical description provided by molecular dynamics (MD) simulations. This reliance on fundamental principles allows FPMD simulations to provide a consistent description of structural, dynamical and electronic properties of a material. This is particularly useful in systems for which reliable empirical models are lacking. FPMD simulations are increasingly used as a predictive tool for applications such as batteries, solar energy conversion, light-emitting devices, electro-chemical energy conversion devices and other materials. During the course of the project, several new features were developed and added to the open-source Qbox FPMD code. The code was further optimized for scalable operation of large-scale, Leadership-Class DOE computers. When combined with Many-Body Perturbation Theory (MBPT) calculations, this infrastructure was used to investigate structural and electronic properties of liquid water, ice, aqueous solutions, nanoparticles and solid-liquid interfaces. Computing both ionic trajectories and electronic structure in a consistent manner enabled the simulation of several spectroscopic properties, such as Raman spectra, infrared spectra, and sum-frequency generation spectra. The accuracy of the approximations used allowed for direct comparisons of results with experimental data such as optical spectra, X-ray and neutron diffraction spectra. The software infrastructure developed in this project, as applied to various investigations of solids, liquids and interfaces, demonstrates that FPMD simulations can provide a detailed, atomic-scale picture of structural, vibrational and electronic properties of complex systems relevant to energy conversion devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Enhanced computational efficiency in the direct determination of the two-electron reduced density matrix from the anti-Hermitian contracted Schrödinger equation with application to ground and excited states of conjugated π-systems

Determination of the two-electron reduced density matrix (2-RDM) from the solution of the anti-Hermitian contracted Schrödinger equation (ACSE) yields accurate energies and properties for both ground and excited states. Here, we develop a more efficient method to solving the ACSE that uses second-order information to select a more optimal step towards the solution. Calculations on the ground and excited states of water, hydrogen fluoride, and conjugated π systems show that the improved ACSE algorithm is 10-20 times faster than the previous ACSE algorithm. The ACSE can treat both single- and multi-reference electron correlation with the initial 2-RDM from a complete-active-space self-consistent-field (CASSCF) calculation. Using the improved algorithm, we explore the relationship between truncation of the active space in the CASSCF calculation and the accuracy of the energy and 2-RDM from the ACSE calculation. The accuracy of the ACSE, we find, is less sensitive to the size of the active space than the accuracy of other wavefunction methods, which is useful when large active space calculations are computationally infeasible.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Kinetic phase evolution of spinel cobalt oxide during lithiation

Spinel cobalt oxide has been proposed to undergo a multiple-step reaction during the electrochemical lithiation process. Understanding the kinetics of the lithiation process in this compound is crucial to optimize its performance and cyclability. In this work, we have utilized a low-angle annular dark-field scanning transmission electron microscopy method to visualize the dynamic reaction process in real time and study the reaction kinetics at different rates. We show that the particles undergo a two-step reaction at the single-particle level, which includes an initial intercalation reaction followed by a conversion reaction. At low rates, the conversion reaction starts after the intercalation reaction has fully finished, consistent with the prediction of density functional theoretical calculations. At high rates, the intercalation reaction is overwhelmed by the subsequently nucleated conversion reaction, and the reaction speeds of both the intercalation and conversion reactions are increased. Phase-field simulations show the crucial role of surface diffusion rates of lithium ions in controlling this process. Furthermore, this work provides microscopic insights into the reaction dynamics in non-equilibrium conditions and highlights the effect of lithium diffusion rates on the overall reaction homogeneity as well as the performance.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Direct Laser Impulse (DLI) System Alignment: Requirements Engineering Project

The National Ignition Facility (NIF) is the world’s largest and most energetic laser, and it is comprised of 192 laser beams that must align onto one target for the purpose of learning about Internal Confinement Fusion (ICF) and High Energy Density (HED) physics. A new NIF capability under development is the Direct Laser Impulse (DLI). The DLI capability will provide a test environment where high pulsed laser energy is delivered to a three-dimensional target. Achieving this delivery to target relies on a precision alignment and positioning of the two redirected NIF beams, as shown in Figure 1. When aligned, the two combined beams—with a frequency converted from infrared (IR) to green laser light, at a fluence (energy per unit area) of roughly 20 joules per square centimeter—will be capable of delivering up to 30 kilojoules of direct, unfocused energy to a one cubic foot target. The 40-cm x 40-cm aligned impulse area at the DLI target interaction plane (TIP) is achieved by using a beam path comprised of pickoff and transport mirrors, frequency conversion crystals, optics serving as environmental barriers, and debris shields. A separate aligned diagnostic beam path is also required for impulse to TIP characterization. Final in-situ alignment is required for the two populated diverted NIF beam paths onto the DLI target as well as the diagnostic optical beam path. Existing NIF alignment subsystems do not offer references that meet DLI’s unique demand. The new DLI Red Box, which has been designed to allow for alignment, has been shown to require deviation from the intended configuration and operational use case to obtain adequate functionality. A systems engineering evaluation has identified a solution that meets the stakeholder requirements while optimizing key performance parameters. The solution, referred to in this document as the Red Box “+” Rotated, was determined to be an improved version of the current DLI Red Box. This system offers improved system repeatability and alignment stability while maintaining similar interfaces and decreasing the demand for engineer/operator interaction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Spontaneous dynamical disordering of borophenes in MgB2 and related metal borides

Abstract Layered boron compounds have attracted significant interest in applications from energy storage to electronic materials to device applications, owing in part to a diversity of surface properties tied to specific arrangements of boron atoms. Here we report the energy landscape for surface atomic configurations of MgB 2 by combining first-principles calculations, global optimization, material synthesis and characterization. We demonstrate that contrary to previous assumptions, multiple disordered reconstructions are thermodynamically preferred and kinetically accessible within exposed B surfaces in MgB 2 and other layered metal diborides at low boron chemical potentials. Such a dynamic environment and intrinsic disordering of the B surface atoms present new opportunities to realize a diverse set of 2D boron structures. We validated the predicted surface disorder by characterizing exfoliated boron-terminated MgB 2 nanosheets. We further discuss application-relevant implications, with a particular view towards understanding the impact of boron surface heterogeneity on hydrogen storage performance.

36 MATERIALS SCIENCE↗

Distinct Mechanisms and Hydricities of Cp*Ir-Based CO 2 Hydrogenation Catalysts in Basic Water

Transition metal-catalyzed reversible hydrogenation of CO 2 to formate in aqueous solutions under ambient conditions is an attractive environmentally friendly strategy for the storage and transportation of H 2 in a liquid chemical form. Here, mechanistic details for the CO 2 hydrogenation by a series of pentamethylcyclopentadienyl iridium(III) (Cp*Ir) complexes with picolinamidate ligands are investigated through density functional theory and kinetic isotope effects (KIEs) calculations. Additionally, adopting a speciation approach at a pH of 8.2, CO 2 hydrogenation mechanisms of 37 distinct protonation states and conformers of Cp*Ir type complexes are investigated. This imposes a challenging test for the computational modeling in terms of providing a consistent correlation with experimental kinetics and KIE studies of multiple catalysts instead of a single complex. Overall, H 2 heterolysis to generate an iridium hydride intermediate was demonstrated to be the rate determining step, which proceeds via distinct pathways depending on the stereoelectronic properties of the ligand. A peculiar iridium dihydride route was also uncovered, which could be optimized to accelerate the H 2 heterolysis. We have further computed the thermodynamic and kinetic hydricities of 74 complexes with [Cp*Ir(L)(H)] q ( q = -1, 0, 1 depending on the ligand charge by deprotonation or protonation events) general formula. Hydricity values do not show any noticeable correlation with the thermodynamics (Δ G ) of [Cp*Ir(L)(HCO 2 – )] formation but exhibit linear correlation with the kinetics (Δ G ‡ ) of electrophilic CO 2 attack to iridium hydride species, especially when the charges and local structural effects of the metal hydrides are considered. Insights gained in this study on (i) the factors determining the preferred pathway for the rate-limiting H 2 heterolysis step, (ii) the correlation between thermodynamic hydricity and the kinetics of CO 2 insertion to iridium hydride species, and (iii) mechanistic analysis via combination of free energy profiles and KIE studies for a series of iridium catalysts will provide guidelines for the design of next-generation catalysts for the reversible H 2 storage through CO 2 utilization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigating the Electronic Structure of Prospective Water-Splitting Oxide BaCe 0.25 Mn 0.75 O 3-δ before and after Thermal Reduction

BaCe 0.25 Mn 0.75 O 3-δ (BCM), a non-stoichiometric oxide with a layered perovskite-like crystal structure, has recently emerged as a prospective contender for application in renewable energy harvesting by solar thermochemical hydrogen generation. Using solar-thermal energy and a reducing environment, oxygen vacancies can be created in high-temperature BCM, and the reduced crystal so obtained can, in turn, produce H 2 by stripping oxygen from H 2 O. Therefore, a first step toward understanding the working mechanism and optimizing the performance of BCM is a thorough and comparative analysis of the electronic structure of the pristine and the reduced material. In this paper, we probe the electronic structure of BCM using the combined effort of first-principles calculations and experimental O K-edge X-ray absorption spectroscopy (XAS). The computed projected density of states (PDOS) and orbital plots are used to propose a simplified model for orbital mixing between the oxygen and metal atoms. With the help of state-of-the-art simulations, we are able to find the origins of the XAS peaks and categorize them on the basis of contribution from Ce and Mn. For the reduced crystal, the calculations show that the change in electron density resulting from the reduction is strongly localized around the oxygen vacancy. Experimental measurements reveal a marked lowering of the first O K-edge peak in the reduced crystal. Using theoretical analysis, this is shown to result from lifting of spin degeneracy in the absorption peaks as well as from a diminished O 2p contribution to the frontier unoccupied orbitals, in accordance with the tight binding scheme. The simulated results serve as a reference for the extent of spectral change as a function of the percentage of oxygen vacancies in the reduced crystal. Here, our study paves the way for the investigation of the working mechanism of BCM and for computational and experimental efforts aimed at design and discovery of efficient water-splitting oxides.

08 HYDROGEN↗

Interpolative Separable Density Fitting Decomposition for Accelerating Hybrid Density Functional Calculations with Applications to Defects in Silicon

We present a new efficient way to perform hybrid density functional theory (DFT)-based electronic structure calculations. The new method uses an interpolative separable density fitting (ISDF) procedure to construct a set of numerical auxiliary basis vectors and a compact approximation of the matrix consisting of products of occupied orbitals represented in a large basis set such as the planewave basis. Such an approximation allows us to reduce the number of Poisson solves from O ($N$ $^{2}_{ϵ}$) to O ( N ϵ ) when we apply the exchange operator to occupied orbitals in an iterative method for solving the Kohn–Sham equations, where Ne is the number of electrons in the system to be studied. We show that the ISDF procedure can be carried out in O ($N$ $^{3}_{ϵ}$) operations, with a much smaller preconstant compared to methods used in existing approaches. When combined with the recently developed adaptively compressed exchange (ACE) operator formalism, which reduces the number of times the exchange operator needs to be updated, the resulting ACE-ISDF method significantly reduces the computational cost associated with the exchange operator by nearly 2 orders of magnitude compared to existing approaches for a large silicon system with 1000 atoms. We demonstrate that the ACE-ISDF method can produce accurate energies and forces for insulating and metallic systems and that it is possible to obtain converged hybrid functional calculation results for a 1000-atom bulk silicon within 10 min on 2000 computational cores. We also show that ACE-ISDF can scale to 8192 computational cores for a 4096-atom bulk silicon system. We use the ACE-ISDF method to geometrically optimize a 1000-atom silicon system with a vacancy defect using the HSE06 functional and computes its electronic structure. Here, we find that that the computed energy gap from the HSE06 functional is much closer to the experimental value compared to that produced by semilocal functionals in the DFT calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accelerated Selectrion of Optimal Perovskite Alloys for Solar PV using a Combined Quantum and Machine Learning Hierachiral Approach

The project aims to: (i) accelerate the discovery of “Missing HP alloys” by combining quantum mechanics and artificial intelligence machine learning approaches, and (ii) analyze the stabilities of candidate alloys, including those that do not pass selection filters (and are thus expected to degrade over time) to decipher the nature of the instabilities to guide the development of durable solar cell materials. Successful candidates will be subjected to validation experiments at NREL's state-of-the-art facilities. The discoveries this effort will provide will be directly testable and implementable and will greatly impact U.S. progress in HP PV as they will provide clear direction and motivation for experimental studies including specific material synthetic targets, device optimization, and device stability protocols. A key advantage of this effort is the feedback and guidance provided by the Industry Collaborative Work Group that we established to coordinate academic and national lab research with industry needs. The proposed work will provide a basis for and direct the development of robust and reliable HP PV. It will also provide a timely, valuable and extensive roadmap to the experimental HP PV community to enable it to focus its efforts on improving and fine-tuning promising HP compositions that this effort predicts will likely be the best performers rather than wandering in the vast chemical space for decades spending enormous resources mostly evaluating unpromising candidate materials.

14 SOLAR ENERGY↗

Electrolyte Design for Fast‐Charging Lithium‐Based Batteries

Fast charging is essential for the widespread adoption of lithium (Li)-ion batteries, but it is fundamentally limited by sluggish interfacial kinetics, Li plating, and electrolyte instability at high current densities. Over the past decade, electrolyte engineering has emerged as a key strategy to address these challenges. This review summarizes the development of fast-charging electrolytes over the past ten years and outlines a design framework. Electrolyte formulations are first deconstructed into their main components—solvents, salts, and functional additives—and representative strategies for tuning solvation structure and interphase chemistry are discussed to suppress Li plating and improve interfacial kinetics. The discussion then extends to advanced electrolyte systems, particularly localized high-concentration electrolytes (LHCEs), and their compatibility with different anode chemistries. Advanced characterization techniques are also summarized and categorized based on destructiveness, spatial and temporal resolution, quantitative analysis, and the chemical species or processes probed across multiple length scales. Recent progress in AI-enabled electrolyte discovery and battery management system (BMS) strategies for optimized fast-charging protocols is further highlighted. Finally, perspectives are presented on translating electrolyte innovations from academic research to practical applications, with emphasis on cell format, realistic operating conditions, and manufacturability.

25 ENERGY STORAGE↗

Multi-reward Reinforcement Learning Based Bond-Order Potential to Study Strain-Assisted Phase Transitions in Phosphorene

Here, we introduce a multi-reward reinforcement learning (RL) approach to train a flexible bond-order potential (BOP) for 2D phosphorene based on ab initio training data sets. Our approach is based on a continuous action space Monte Carlo tree search algorithm that is general and scalable and presents an efficient multiobjective optimization scheme for high-dimensional materials design problems. As a proof-of-concept, we deploy this scheme to parametrize multiple structural and dynamical properties of 2D phosphorene polymorphs. Our RL-trained BOP model adequately captures the structure, energetics, transformation barriers, equation of state, elastic constants, and phonon dispersions of various 2D P polymorphs. We use this model to probe the impact of temperature and strain rate on the phase transition from black (α-P) to blue phosphorene (β-P) through molecular dynamics simulations. A decrease in critical strain for this phase transition with increase in temperature is observed, and the underlying atomistic mechanisms are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗