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DOE OSTI2018

Computational Design of Active Site Structures with Improved Transition-State Scaling for Ammonia Synthesis

Here, the Haber–Bosch process for the reduction of atmospheric nitrogen to ammonia is one of the most optimized heterogeneous catalytic reactions, but there are aspects of the industrial process that remain less than ideal. It has been shown that the activity of metal catalysts is limited by a Brønsted–Evans–Polanyi (BEP) scaling relationship between the reaction and transition-state energies for N 2 dissociation, leading to a negligible production rate at ambient conditions and a modest rate under harsh conditions. In this study, we use density functional theory (DFT) calculations in conjunction with mean-field microkinetic modeling to study the rate of NH 3 synthesis on model active sites that require the singly coordinated dissociative adsorption of N atoms onto transition metal atoms. Our results demonstrate that this ”on-top” binding of nitrogen exhibits significantly improved scaling behavior, which can be rationalized in terms of transition-state geometries and leads to considerably higher predicted activity. While synthesis of these model systems is likely challenging, the stabilization of such an active site could enable thermochemical ammonia synthesis under more benign conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

The role of the CeO 2 /BiVO 4 interface in optimized Fe–Ce oxide coatings for solar fuels photoanodes

Solar fuel generators entail a high degree of materials integration, and efficient photoelectrocatalysis of the constituent reactions hinges upon the establishment of highly functional interfaces. Our recent application of high throughput experimentation to interface discovery for solar fuels photoanodes has revealed several surprising and promising mixed-metal oxide coatings for BiVO 4 . Furthermore, when using sputter deposition of composition and thickness gradients on a uniform BiVO 4 film, we systematically explore photoanodic performance as a function of the composition and loading of Fe–Ce oxide coatings. This combinatorial materials integration study not only enhances the performance of this new class of materials but also identifies CeO 2 as a critical ingredient that merits detailed study. A heteroepitaxial CeO 2 (001)/BiVO4(010) interface is identified in which Bi and V remain fully coordinated to O such that no surface states are formed. Ab initio calculations of the integrated materials and inspection of the electronic structure reveals mechanisms by which CeO 2 facilitates charge transport while mitigating deleterious recombination. Our results support the observations that addition of Ce to BiVO 4 coatings greatly enhances photoelectrocatalytic activity, providing an important strategy for developing a scalable solar fuels technology.

14 SOLAR ENERGY↗

DOE OSTI2019

The effects of active site and support on hydrogen elimination over transition-metal-functionalized yttria-decorated metal–organic frameworks

Hydrogen elimination from a metal alkyl complex and its reverse reaction are critical elementary steps in many catalytic cycles. In understanding such catalytic cycles, it is important to learn about the effect of the active site as well as effects beyond the active site, especially support effects. Here we employ density-functional-theory-based computational screening of transition-metal-functionalized yttria-decorated NU-1000 metal–organic frameworks to study the effect of metal sites and supports on the hydrogen elimination reactions. In this work, we consider six transition metals. The screening shows that a Nb-based catalyst has the lowest free energy of activation for both α-H elimination and β-H elimination, but for the latter we must also consider the free energy of release of the alkene. By the Sabatier principle, the optimal catalyst for β-H elimination is the one that interacts with molecules with intermediate strength for easy reactant activation as well as easy product desorption. By employing a volcano plot to find the optimum compromise, we identified V-functionalized, yttria-decorated NU-1000 as the most active catalyst among the trial candidates for the β-H elimination reaction. The analysis also reveals a support-specific charge transfer process in which the yttria and carboxylate linkers enable electron transfer between the transition-metal site and organic linkers of the NU-1000 simultaneously with a coordinated change of spin at the metal site and in the linker groups. Based on our analyses, we hypothesize that the observed charge transfer enables certain functional groups, such as propyl, to interact more strongly with the support and stabilize the catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Retracted Article: Distributed energy management for networked microgrids in a three-phase unbalanced distribution network

Owing to increased penetration of three-phase and single-phase microgrids, distributed energy resources (DERs), and responsive loads, the maintenance of a three-phase balance by distribution networks is a significant challenge. Existing literature on distributed energy management for networked microgrids generally neglects the distribution network or employs a simplified phase balanced distribution network; thus, these evaluations are not applicable. Further, the underlying mutual coupling between the different phases of distribution feeders results in a more challenging situation. Here, to solve this issue, this study sought to propose distributed energy management based on a three-phase unbalanced distribution network. Various three-phase or single-phase microgrids, utility-owned DERs, and responsive loads were coordinated through iteratively adjusted price signals. Based on the price signals received, the microgrid controllers (MCs) and distribution management system (DMS) updated the schedules of the DERs and responsive loads under their jurisdiction separately. The price signals were then updated according to the generation-load mismatch at each node and distributed to the corresponding MCs and DMS for the next iteration. The iteration continued until a sufficiently small generation-load mismatch was achieved at all nodes, that is, a balanced generation and load at all nodes under the agreed price signals. Considering a three-phase unbalanced distribution network, the price signals were determined per phase per node. Overall, the proposed distributed energy management coordinates microgrids, utility-owned DERs, responsive loads with guaranteed network constraints, and preserves the privacy of microgrid customers. This distributed energy management method was further demonstrated through various case studies on a three-phase networked microgrid test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Evaluating the Impact of Managed EV Charging for Reliable Operation of Bulk Power Systems with High Non-Dispatchable Generation

The growth of electric vehicles (EVs) and variable-generation (VG) sources introduces new challenges for power-system operations. This study introduces a modeling framework and evaluates five EV charging strategies under projected 2040 grid conditions in the Evergy service territory with high non-dispatchable generation. Using realistic EV behavior and generation models, their impacts on system peak demand, ramp rate, and reserve capacity are evaluated. Results show that only the peak-avoidance strategy effectively reduces system peak demand, while decentralized strategies-particularly cost based dynamic charging-can exacerbate peaks due to synchronized user behavior. However, ramp-rate minimization strategy significantly reduce the stress on dispatchable generation achieving the lowest maximum absolute ramp rate (MARR) (56.81 MW) and lowest reserve requirement (2.39 GW). In contrast, unmanaged and TOU random strategies increase the stress on dispatchable generation sources with increased MARR and reserve requirements. These findings highlight the importance of coordinated, system-aware managed charging strategies to ensure reliable and affordable grid operation in the presence of EVs and VG sources.

14 - SOLAR ENERGY↗

DOE OSTI2017

Postsynthetic Functionalization of Mg-MOF-74 with Tetraethylenepentamine: Structural Characterization and Enhanced CO 2 Adsorption

Postsynthetic functionalization of magnesium 2,5-dihydroxyterephthalate (Mg-MOF-74) with tetraethylenepentamine (TEPA) resulted in improved CO 2 adsorption performance under dry and humid conditions. XPS, elemental analysis, and neutron powder diffraction studies indicated that TEPA was incorporated throughout the MOF particle, although it coordinated preferentially with the unsaturated metal sites located in the immediate proximity to the surface. Neutron and X-ray powder diffraction analyses showed that the MOF structure was preserved after amine incorporation, with slight changes in the lattice parameters. The adsorption capacity of the functionalized amino-Mg-MOF-74 (TEPA-MOF) for CO 2 was as high as 26.9 wt % versus 23.4 wt % for the original MOF due to the extra binding sites provided by the multiunit amines. Here, the degree of functionalization with the amines was found to be important in enhancing CO 2 adsorption, as the optimal surface coverage improved performance and stability under both pure CO 2 and CO 2 /H 2 O coadsorption, and with partially saturated surface coverage, optimal CO 2 capacity could be achieved under both wet and dry conditions by a synergistic binding of CO 2 to the amines as well as metal centers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Chicken fat for catalysis: a scaffold is as important for molecular complexes for energy transformations as it is for enzymes in catalytic function

Metalloenzymes are remarkably active, specific, and efficient catalysts.Mimicking the active sites with organometallic complexes based on crystal structures has been a focus for many synthetic chemists. These surrogates have provided significant mechanistic insight into both the molecular complexes as well as the enzymes, however, one of the principle findings has been that just reproducing the active site is not adequate in reproducing the catalytic function. Specifically, the scaffold surrounding the active site plays a critical role in many aspects of catalysis, from positioning reactants optimally to positioning functional groups for reaction to creating the ideal environment for catalysis. Each of these can be controlled with both static positioning as well as small and large dynamics that can activate or control a specific part of the reaction. In this review, we will discuss the effect of organic/peptidic scaffolds, along with medium as an extension of the scaffold, and their varying impacts on catalytic reactivity.

Laureanti, Joseph A.↗

DOE OSTI2021

Power Quality and Stability in a Cluster of Microgrids with Coordinated Power and Energy Management

Distributed Energy Resources (DER) such as photovoltaic (PV) systems and battery energy storage systems (BESS) can be operated collectively as microgrids. Microgrids can be effective in meeting local load requirements as well as in improving the power quality and stability in a modern power distribution system. Multiple microgrids can also be operated in a coordinated manner as a cluster, to improve the resiliency of the power distribution system. In the event of an outage caused by a transmission system failure, the microgrids in a cluster can use their distributed generation capacity and energy storage resources to recover and extend power availability to the critical loads in the system. In this paper, an illustrative cluster of two microgrids based on the IEEE 13-bus model with DERs has been used, to demonstrate the operation of the concept using real-time simulations. Using real-time simulations, capabilities such as switching reconfiguration following faults, identification of optimal DER placement for effective power quality management, and power electronic controller validation have been demonstrated. For the two-microgrid cluster, this paper also presents improvements in load voltage quality and

Chowdhury, Prithwiraj Roy↗

DOE OSTI2024

Optimized Substrate Positioning Enables Switches in the C–H Cleavage Site and Reaction Outcome in the Hydroxylation–Epoxidation Sequence Catalyzed by Hyoscyamine 6β-Hydroxylase

Hyoscyamine 6β-hydroxylase (H6H) is an Fe(II)- and 2-oxoglutarate-dependent (Fe/2OG) oxygenase that catalyzes the last two steps in the biosynthesis of scopolamine, a prolifically administered anti-nausea drug. After its namesake first reaction, H6H couples the newly installed C6-bonded oxygen to C7 to form the epoxide of scopolamine. Oxoiron(IV) (ferryl) intermediates initiate both reactions by cleaving C–H bonds, but it remains unclear how the enzyme switches target site and promotes (C6)O–C7 coupling in preference to C7 hydroxylation in the second step. In one possible epoxidation mechanism, the C6 oxygen would – analogously to mechanisms proposed for the Fe/2OG halogenases and, in the preceding paper, N-acetylnorloline synthase (LolO) – coordinate as alkoxide to the C7–H-cleaving ferryl intermediate to enable alkoxyl coupling to the ensuing C7 radical. Here we provide structural and kinetic evidence that H6H instead exploits the distinct spatial dependencies of competitive C–H-cleavage (C6 vs C7) and C–O-coupling (oxygen rebound vs cyclization) steps to promote the two-step sequence without substrate coordination or repositioning for the epoxidation step. Structural comparisons of ferryl-mimicking vanadyl complexes of wild-type H6H and a variant that preferentially hydroxylates C7 of 6-hydroxyhyoscyamine suggest that only a modest (~ 10°) shift in the Fe–O–H(C7) approach angle is sufficient to change the outcome. Finally, the observation that, in wild-type H6H, 2 H 2 O solvent also increases the C7-hydroxylation:epoxidation ratio by ~ 8-fold implies that the latter outcome requires cleavage of the alcohol O-H bond, which, unlike in the LolO oxacyclization, is not accomplished in advance of C–H cleavage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Geometry-dependent distributed polarizability models for the water molecule

Geometry-dependent distributed polarizability models have been constructed by fits to ab initio calculations at the coupled cluster level of theory with up to noniterative triple excitations in an augmented triple-zeta quality basis set for the water molecule in the field of a point charge. The investigated models include (i) charge-flow polarizabilities between chemically bonded atoms, (ii) isotropic or anisotropic dipolar polarizabilities on oxygen atom or on all atoms, and (iii) combinations of models (i) and (ii). For each model, the polarizability parameters have been optimized to reproduce the induction energy of a water molecule polarized by a point charge successively occupying a grid of points surrounding the molecule. The quality of the models is ascertained by examining their ability to reproduce these induction energies as well as the molecular dipolar and quadrupolar polarizabilities. The geometry dependence of the distributed polarizability models has been explored by changing bond lengths and HOH angle to generate 125 molecular structures (reduced to 75 symmetry-unique ones). For each considered model, the distributed polarizability components have been fitted as a function of the geometry by a Taylor expansion in monomer coordinate displacements up to the sum of powers equal to 4.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Multi-Agent Deep Reinforcement Learning for Realistic Distribution System Voltage Control Using PV Inverters

Over the last few decades, the deployment of distributed solar photovoltaic (PV) systems has increased consistently. High PV penetration could cause adverse effects on the grid, such as voltage violations. This paper proposes a new distributed soft actor-critic based multi-agent deep reinforcement learning (SAC-MADRL) control solution to minimize the PV real power curtailment while keeping the grid voltage in an acceptable range. New reward functions have been designed to coordinate different agents during the learning process, yielding improved convergence. Comparison results with other control methods on a real feeder in western Colorado U.S. with 80% penetration of PVs demonstrate that the proposed method has better capability of effectively regulating voltage while minimizing the PV real power curtailment.

distribution system↗

DOE OSTI2017

Models for the dynamics of dust-like matter in the self-gravity field: The method of hydrodynamic substitutions

Models for the dynamics of a dust-like medium in the self-gravity field are investigated. Solutions of the corresponding problems are constructed by the method of hydrodynamic substitutions generalizing the Cole–Hopf substitutions. The method is extended to multidimensional ideal and viscous fluid flows with cylindrical and spherical symmetries for which exact solutions are constructed. Solutions for the dynamics of self-gravitating dust with arbitrary initial distributions of both fluid density and velocity are constructed using special coordinate transformations. In particular, the problem of cosmological expansion is considered in terms of Newton’s gravity theory. Models of a one-dimensional viscous dust fluid flow and some problems of gas hydrodynamics are considered. Examples of exact solutions and their brief analysis are provided.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

AI Applications to Physics Experiments at Jefferson Lab

We survey how AI/ML is being deployed across Jefferson Lab's experimental and accelerator programs. In EPSCI, Hydra applies computer vision to automate real-time data-quality monitoring across all four experimental halls, replacing manual inspection of hundreds to thousands of histograms per shift. AIEC (AI Experiment Controls) uses ML to stabilize drift chamber gains and is now part of standard CEBAF production running, while AI Optimized Polarization (AIOP) targets autonomous control of polarized targets and photon beam angular alignment. In CASA, cavity fault classification models identify faulted cavities and trip types from waveform data with ~85% and ~78% agreement to labeled data, respectively, and are deployed in production; a separate effort applies LLMs and hybrid search to make the CEBAF operations logbook AI-ready. QCD-focused work includes transformer- and GAN-based generative models for particle-level event simulation, with distributed GAN training scaling studies on Polaris. Additional efforts span ML-on-FPGA for the EIC and a new Data Science Department coordinating anomaly detection, uncertainty quantification, and HPC-scalable ML lab-wide. Collectively, these projects illustrate AI's growing role in improving efficiency across JLab's nuclear physics mission.

Mei, Xinxin [Thomas Jefferson National Accelerator↗

DOE OSTI2015

Multi-GPU implementation of a VMAT treatment plan optimization algorithm

Purpose: Volumetric modulated arc therapy (VMAT) optimization is a computationally challenging problem due to its large data size, high degrees of freedom, and many hardware constraints. High-performance graphics processing units (GPUs) have been used to speed up the computations. However, GPU’s relatively small memory size cannot handle cases with a large dose-deposition coefficient (DDC) matrix in cases of, e.g., those with a large target size, multiple targets, multiple arcs, and/or small beamlet size. The main purpose of this paper is to report an implementation of a column-generation-based VMAT algorithm, previously developed in the authors’ group, on a multi-GPU platform to solve the memory limitation problem. While the column-generation-based VMAT algorithm has been previously developed, the GPU implementation details have not been reported. Hence, another purpose is to present detailed techniques employed for GPU implementation. The authors also would like to utilize this particular problem as an example problem to study the feasibility of using a multi-GPU platform to solve large-scale problems in medical physics. Methods: The column-generation approach generates VMAT apertures sequentially by solving a pricing problem (PP) and a master problem (MP) iteratively. In the authors’ method, the sparse DDC matrix is first stored on a CPU in coordinate list format (COO). On the GPU side, this matrix is split into four submatrices according to beam angles, which are stored on four GPUs in compressed sparse row format. Computation of beamlet price, the first step in PP, is accomplished using multi-GPUs. A fast inter-GPU data transfer scheme is accomplished using peer-to-peer access. The remaining steps of PP and MP problems are implemented on CPU or a single GPU due to their modest problem scale and computational loads. Barzilai and Borwein algorithm with a subspace step scheme is adopted here to solve the MP problem. A head and neck (H and N) cancer case is then used to validate the authors’ method. The authors also compare their multi-GPU implementation with three different single GPU implementation strategies, i.e., truncating DDC matrix (S1), repeatedly transferring DDC matrix between CPU and GPU (S2), and porting computations involving DDC matrix to CPU (S3), in terms of both plan quality and computational efficiency. Two more H and N patient cases and three prostate cases are used to demonstrate the advantages of the authors’ method. Results: The authors’ multi-GPU implementation can finish the optimization process within ∼1 min for the H and N patient case. S1 leads to an inferior plan quality although its total time was 10 s shorter than the multi-GPU implementation due to the reduced matrix size. S2 and S3 yield the same plan quality as the multi-GPU implementation but take ∼4 and ∼6 min, respectively. High computational efficiency was consistently achieved for the other five patient cases tested, with VMAT plans of clinically acceptable quality obtained within 23–46 s. Conversely, to obtain clinically comparable or acceptable plans for all six of these VMAT cases that the authors have tested in this paper, the optimization time needed in a commercial TPS system on CPU was found to be in an order of several minutes. Conclusions: The results demonstrate that the multi-GPU implementation of the authors’ column-generation-based VMAT optimization can handle the large-scale VMAT optimization problem efficiently without sacrificing plan quality. The authors’ study may serve as an example to shed some light on other large-scale medical physics problems that require multi-GPU techniques.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Producing glucose 6-phosphate from cellulosic biomass: Structural insights into levoglucosan bioconversion

The most abundant carbohydrate product of cellulosic biomass pyrolysis is the anhydrosugar levoglucosan (1,6-anhydro-β-d-glucopyranose), which can be converted to glucose 6-phosphate by levoglucosan kinase (LGK). In addition to the canonical kinase phosphotransfer reaction, the conversion requires cleavage of the 1,6-anhydro ring to allow ATP-dependent phosphorylation of the sugar O6 atom. Using x-ray crystallography, we show that LGK binds two magnesium ions in the active site that are additionally coordinated with the nucleotide and water molecules to result in ideal octahedral coordination. To further verify the metal binding sites, we co-crystallized LGK in the presence of manganese instead of magnesium and solved the structure de novo using the anomalous signal from four manganese atoms in the dimeric structure. The first metal is required for catalysis, whereas our work suggests that the second is either required or significantly promotes the catalytic rate. Although the enzyme binds its sugar substrate in a similar orientation to the structurally related 1,6-anhydro-N-acetylmuramic acid kinase (AnmK), it forms markedly fewer bonding interactions with the substrate. In this orientation, the sugar is in an optimal position to couple phosphorylation with ring cleavage. We also observed a second alternate binding orientation for levoglucosan, and in these structures, ADP was found to bind with lower affinity. These combined observations provide an explanation for the high Km of LGK for levoglucosan. Furthermore, greater knowledge of the factors that contribute to the catalytic efficiency of LGK can be used to improve applications of this enzyme for levoglucosan-derived biofuel production.

09 BIOMASS FUELS↗

DOE OSTI2026

A Survey on the Expanding Scope and Interdisciplinary Opportunities for Processing-in-Memory Techniques

Processing-in-Memory (PIM) is emerging as a practical path to overcome the limitations of traditional von Neumann architectures. At its core, PIM systems implement computing primitives such as logic operations and multiply-accumulate acceleration through compute-in-memory, near-memory processing, or hybrid designs. The role of memory cells varies widely across technologies, acting as inputs, outputs, or analog accumulators through bit-lines and sense amplifiers. This diversity creates trade-offs in precision, bandwidth, latency, and programmability, making it difficult to build a unified understanding on the progress of the field. In this survey, we organize recent advances of PIM into three areas. First, we discuss the progress on the architectural optimizations of PIM and its integration with both DRAM and emerging non-volatile memories. Second, we examine how PIM is being used to accelerate key computing domains, including generative AI workloads and high-performance kernels, along with new approaches. Third, we highlight the growing adoption of PIM in computational sciences, where it is being applied to solve interdisciplinary problems such as genome analysis, mRNA quantification, mass spectrometry, quantum circuit simulation, wave modeling, and secure computation. Finally, we synthesize the major challenges that continue to slow PIM adoption, including manufacturing constraints, power delivery, thermal reliability, data consistency, runtime and memory-management coordination, and the difficulty of building portable software abstractions without sacrificing commercial viability. This work provides an updated, structured perspective on PIM’s potential across computing and computational sciences and the barriers that must be solved for it to reach its full impact.

Asifuzzaman, Kazi [Oak Ridge National Laboratory (↗

DOE OSTI2025

Metal–Oxide Interface Sites Created Using Atomic Layer Deposition and Tested for CO Oxidation

The performance of catalysts made out of Pt supported on TiO 2 thin films grown on SBA-15 (a silica mesoporous material) by atomic layer deposition (ALD) was characterized systematically by combining in situ infrared absorption spectroscopy (IR) with other techniques including electron microscopy and adsorption−desorption isothermal measurements. The titania films in the resulting high-surface-area catalysts were evenly distributed throughout the inner surface of the SBA-15 mesopores, and their thickness could be controlled at a submonolayer level, with 3 to 4 TiO 2 ALD cycles needed for the complete coverage of the silica sites. The titania films could be deposited either before or after adding the metal (Pt), which was dispersed in the form of small nanoparticles (NPs) approximately 4−6 nm in diameter, in order to exert some control on the density and nature of the Pt/TiO 2 interface sites. One important lesson deriving from this work is that such an order of deposition leads to significantly different catalysts in spite of the fact that most of their structural properties are similar. If the Pt is deposited on the titania films, the resulting metal NPs are slightly smaller than those grown on silica and display CO adsorption sites with lower surface Pt coordination numbers. On the other hand, when TiO 2 is deposited on the Pt/SBA-15 starting material, some titania grows on the metal and partially blocks its surface while also creating new interface sites where CO binds more weakly and displays lower C−O stretching frequencies. In terms of catalytic performance, the results from in situ IR CO site titration and kinetic measurements combined suggest a mechanism where CO first adsorbs on Pt atop sites and then migrates to Pt/TiO 2 interface sites, where oxidation takes place. Both types of sites appear to be similar in all the catalysts tested, but catalytic performance could be optimized by tuning their surface densities. Maximum catalytic activity was obtained when the TiO2 films were deposited first and with TiO 2 coverages of at least half a monolayer, that is, after at least 2 ALD cycles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Rational solvent molecule tuning for high-performance lithium metal battery electrolytes

Electrolyte engineering improved cycling of Li metal batteries and anode-free cells at low current densities; however, high-rate capability and tuning of ionic conduction in electrolytes are desirable yet less-studied. In this study, we design and synthesize a family of fluorinated-1,2-diethoxyethanes as electrolyte solvents. The position and amount of F atoms functionalized on 1,2-diethoxyethane were found to greatly affect electrolyte performance. Partially fluorinated, locally polar –CHF 2 is identified as the optimal group rather than fully fluorinated –CF 3 in common designs. Paired with 1.2 M lithium bis(fluorosulfonyl)imide, these developed single-salt-single-solvent electrolytes simultaneously enable high conductivity, low and stable overpotential, >99.5% Li||Cu half-cell efficiency (up to 99.9%, ±0.1% fluctuation) and fast activation (Li efficiency >99.3% within two cycles). Combined with high-voltage stability, these electrolytes achieve roughly 270 cycles in 50-μm-thin Li||high-loading-NMC811 full batteries and >140 cycles in fast-cycling Cu||microparticle-LiFePO 4 industrial pouch cells under realistic testing conditions. The correlation of Li + –solvent coordination, solvation environments and battery performance is investigated to understand structure–property relationships.

25 ENERGY STORAGE↗