Showing papers by "Pacific Northwest National Laboratory published in 2021"
TL;DR: Compared with PINNs, B-PINNs obtain more accurate predictions in scenarios with large noise due to their capability of avoiding overfitting and dropout employed in PINNs can hardly provide accurate predictions with reasonable uncertainty.
410 citations
TL;DR: A general framework for hp-variational physics-informed neural networks (hp-VPINNs) based on the nonlinear approximation of shallow and deep neural networks and hp-refinement via domain decomposition and projection onto space of high-order polynomials is formulated.
253 citations
TL;DR: A new theory quantifying product formulas' errors puts these algorithms on a rigorous foundation, showcasing their superiority over other methods.
Abstract: Product formulas offer a powerful, simple approach to quantum simulation. A new theory quantifying their errors puts these algorithms on a rigorous foundation, showcasing their superiority over other methods.
247 citations
TL;DR: A comprehensive overview of recent advances in the P1P energy system and an insightful discussion of the challenges that need to be addressed in order to establish P2P sharing as a viable energy management option in today’s electricity market are focused on.
236 citations
TL;DR: This article identified key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation, as well as potential targets for EGFR-, TP53-, and RB1-altered tumors.
211 citations
208 citations
TL;DR: Li et al. as mentioned in this paper investigated the degradation mechanisms of Li 0.6Mn0.2Co 0.2O2 pouch cells and present fundamental linkages among Li thickness, electrolyte depletion and the structure evolution of solid-electrolyte interphase layers.
Abstract: The rechargeable lithium metal battery has attracted wide attention as a next-generation energy storage technology. However, simultaneously achieving high cell-level energy density and long cycle life in realistic batteries is still a great challenge. Here we investigate the degradation mechanisms of Li || LiNi0.6Mn0.2Co0.2O2 pouch cells and present fundamental linkages among Li thickness, electrolyte depletion and the structure evolution of solid–electrolyte interphase layers. Different cell failure processes are discovered when tuning the anode to cathode capacity ratio in compatible electrolytes. An optimal anode to cathode capacity ratio of 1:1 emerges because it balances well the rates of Li consumption, electrolyte depletion and solid–electrolyte interphase construction, thus decelerating the increase of cell polarization and extending cycle life. Contrary to conventional wisdom, long cycle life is observed by using ultra-thin Li (20 µm) in balanced cells. A prototype 350 Wh kg−1 pouch cell (2.0 Ah) achieves over 600 long stable cycles with 76% capacity retention without a sudden cell death. The development of Li metal batteries requires understanding of cell-level electrochemical processes. Here the authors investigate the interplay between electrode thickness, electrolyte depletion and solid–electrolyte interphase in practical pouch cells and demonstrate the construction of high-energy long-cycle Li metal batteries.
198 citations
TL;DR: This paper reviews the application of machine learning techniques in building load prediction under the organization and logic of the machine learning, which is to perform tasks T using Performance measure P and based on learning from Experience E.
197 citations
177 citations
University of Maryland, College Park1, Ford Motor Company2, University of Colorado Boulder3, Lawrence Berkeley National Laboratory4, Oak Ridge National Laboratory5, Argonne National Laboratory6, University of California, Los Angeles7, Applied Materials8, Michigan Technological University9, Pacific Northwest National Laboratory10, Iowa State University11, Georgia Institute of Technology12, University of California, San Diego13, University of Michigan14, General Motors15
TL;DR: In this paper, Albertus, P; Anandan, V; Ban, C; Balsara, N; Belharouak, I; Buettner-Garrett, J; Chen, Z; Daniel, C, Doeff, M; Dudney, NJ; Dunn, B; Harris, SJ; Herle, S; Herbert, E; Kalnaus, S, Libera, JA; Lu, D; Martin, S., McCloskey, BD; McDowell, MT; Meng, YS; Nanda, J, Sak
Abstract: Author(s): Albertus, P; Anandan, V; Ban, C; Balsara, N; Belharouak, I; Buettner-Garrett, J; Chen, Z; Daniel, C; Doeff, M; Dudney, NJ; Dunn, B; Harris, SJ; Herle, S; Herbert, E; Kalnaus, S; Libera, JA; Lu, D; Martin, S; McCloskey, BD; McDowell, MT; Meng, YS; Nanda, J; Sakamoto, J; Self, EC; Tepavcevic, S; Wachsman, E; Wang, C; Westover, AS; Xiao, J; Yersak, T
170 citations
National Institutes of Health1, University of California, Riverside2, Purdue University3, Pacific Northwest National Laboratory4, Rensselaer Polytechnic Institute5, State University of New York System6, University of Michigan7, Brown University8, University of Pennsylvania9, University of California, Santa Barbara10, Stanford University11
TL;DR: This review identifies areas in the biomedical sciences where machine learning and multiscale modeling can mutually benefit from one another and identifies applications and opportunities, raise open questions, and address potential challenges and limitations.
Abstract: Machine learning is increasingly recognized as a promising technology in the biological, biomedical, and behavioral sciences. There can be no argument that this technique is incredibly successful in image recognition with immediate applications in diagnostics including electrophysiology, radiology, or pathology, where we have access to massive amounts of annotated data. However, machine learning often performs poorly in prognosis, especially when dealing with sparse data. This is a field where classical physics-based simulation seems to remain irreplaceable. In this review, we identify areas in the biomedical sciences where machine learning and multiscale modeling can mutually benefit from one another: Machine learning can integrate physics-based knowledge in the form of governing equations, boundary conditions, or constraints to manage ill-posted problems and robustly handle sparse and noisy data; multiscale modeling can integrate machine learning to create surrogate models, identify system dynamics and parameters, analyze sensitivities, and quantify uncertainty to bridge the scales and understand the emergence of function. With a view towards applications in the life sciences, we discuss the state of the art of combining machine learning and multiscale modeling, identify applications and opportunities, raise open questions, and address potential challenges and limitations. We anticipate that it will stimulate discussion within the community of computational mechanics and reach out to other disciplines including mathematics, statistics, computer science, artificial intelligence, biomedicine, systems biology, and precision medicine to join forces towards creating robust and efficient models for biological systems.
TL;DR: Recent progress in understanding the degradation of low-PGM and PGM-free catalysts in fuel cell MEAs and materials-based solutions to address these issues are reviewed and the key factors that degrade the MEA performance are highlighted.
Abstract: Fuel cells as an attractive clean energy technology have recently regained popularity in academia, government, and industry. In a mainstream proton exchange membrane (PEM) fuel cell, platinum-group-metal (PGM)-based catalysts account for ≈50% of the projected total cost for large-scale production. To lower the cost, two materials-based strategies have been pursued: 1) to decrease PGM catalyst usage (so-called low-PGM catalysts), and 2) to develop alternative PGM-free catalysts. Grand stability challenges exist when PGM catalyst loading is decreased in a membrane electrode assembly (MEA)-the power generation unit of a PEM fuel cell-or when PGM-free catalysts are integrated into an MEA. More importantly, there is a significant knowledge gap between materials innovation and device integration. For example, high-performance electrocatalysts usually demonstrate undesired quick degradation in MEAs. This issue significantly limits the development of PEM fuel cells. Herein, recent progress in understanding the degradation of low-PGM and PGM-free catalysts in fuel cell MEAs and materials-based solutions to address these issues are reviewed. The key factors that degrade the MEA performance are highlighted. Innovative, emerging material concepts and development of low-PGM and PGM-free catalysts are discussed.
TL;DR: In this paper, Allen et al. used in situ observations of microplastic deposition combined with an atmospheric transport model and optimal estimation techniques to test hypotheses of the most likely sources of atmospheric plastic.
Abstract: Plastic pollution is one of the most pressing environmental and social issues of the 21st century. Recent work has highlighted the atmosphere’s role in transporting microplastics to remote locations [S. Allen et al., Nat. Geosci. 12, 339 (2019) and J. Brahney, M. Hallerud, E. Heim, M. Hahnenberger, S. Sukumaran, Science 368, 1257–1260 (2020)]. Here, we use in situ observations of microplastic deposition combined with an atmospheric transport model and optimal estimation techniques to test hypotheses of the most likely sources of atmospheric plastic. Results suggest that atmospheric microplastics in the western United States are primarily derived from secondary re-emission sources including roads (84%), the ocean (11%), and agricultural soil dust (5%). Using our best estimate of plastic sources and modeled transport pathways, most continents were net importers of plastics from the marine environment, underscoring the cumulative role of legacy pollution in the atmospheric burden of plastic. This effort uses high-resolution spatial and temporal deposition data along with several hypothesized emission sources to constrain atmospheric plastic. Akin to global biogeochemical cycles, plastics now spiral around the globe with distinct atmospheric, oceanic, cryospheric, and terrestrial residence times. Though advancements have been made in the manufacture of biodegradable polymers, our data suggest that extant nonbiodegradable polymers will continue to cycle through the earth’s systems. Due to limited observations and understanding of the source processes, there remain large uncertainties in the transport, deposition, and source attribution of microplastics. Thus, we prioritize future research directions for understanding the plastic cycle.
TL;DR: In this paper, the authors present a comprehensive review of the redox reactivity of four types of Fe(II) species, including aqueous Fe, Fe complexed with ligands, minerals bearing structural Fe, and sorbed Fe on mineral oxide surfaces.
Abstract: Iron (Fe) is the fourth most abundant element in the earth's crust and plays important roles in both biological and chemical processes. The redox reactivity of various Fe(II) forms has gained increasing attention over recent decades in the areas of (bio) geochemistry, environmental chemistry and engineering, and material sciences. The goal of this paper is to review these recent advances and the current state of knowledge of Fe(II) redox chemistry in the environment. Specifically, this comprehensive review focuses on the redox reactivity of four types of Fe(II) species including aqueous Fe(II), Fe(II) complexed with ligands, minerals bearing structural Fe(II), and sorbed Fe(II) on mineral oxide surfaces. The formation pathways, factors governing the reactivity, insights into potential mechanisms, reactivity comparison, and characterization techniques are discussed with reference to the most recent breakthroughs in this field where possible. We also cover the roles of these Fe(II) species in environmental applications of zerovalent iron, microbial processes, biogeochemical cycling of carbon and nutrients, and their abiotic oxidation related processes in natural and engineered systems.
TL;DR: In this article, the authors acknowledge support from the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) of Japan, the Japan Society for the Promotion of Science (JSPS), and the Tau-Lepton Physics Research Center of Nagoya University.
Abstract: We acknowledge support from the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) of Japan, the Japan Society for the Promotion of Science (JSPS), and the Tau-Lepton Physics Research Center of Nagoya University; the Australian Research Council including Grants No. DP180102629, No. DP170102389, No. DP170102204, No. DP150103061, No. FT130100303; Austrian Science Fund (FWF); the National Natural Science Foundation of China under Contracts No. 11435013, No. 11475187, No. 11521505, No. 11575017, No. 11675166, No. 11705209; Key Research Program of Frontier Sciences, Chinese Academy of Sciences (CAS), Grant No. QYZDJ-SSWSLH011; the CAS Center for Excellence in Particle Physics (CCEPP); the Shanghai Pujiang Program under Grant No. 18PJ1401000; the Ministry of Education, Youth and Sports of the Czech Republic under Contract No. LTT17020; the Carl Zeiss Foundation, the Deutsche Forschungsgemeinschaft, the Excellence Cluster Universe, and the VolkswagenStiftung; the Department of Science and Technology of India; the Istituto Nazionale di Fisica Nucleare of Italy; National Research Foundation (NRF) of Korea Grants No. 2016R1D1A1B01010135, No. 2016R1D1A1B02012900, No. 2018R1A2B3003643, No. 2018R1A6A1A06024970, No. 2018R1D1A1B07047294, No. 2019K1A3A7A09033840, No. 2019R1I1A3A01058933; Radiation Science Research Institute, Foreign Large-size Research Facility Application Supporting project, the Global Science Experimental Data Hub Center of the Korea Institute of Science and Technology Information, and KREONET/GLORIAD the Polish Ministry of Science and Higher Education and the National Science Center; the Ministry of Science and Higher Education of the Russian Federation, Agreement No. 14.W03.31.0026; University of Tabuk research Grants No. S-1440-0321, No. S-0256-1438, and No. S-0280-1439 (Saudi Arabia); the Slovenian Research Agency; Ikerbasque, Basque Foundation for Science, Spain; the Swiss National Science Foundation; the Ministry of Education and the Ministry of Science and Technology of Taiwan; and the U.S. Department of Energy and the National Science Foundation.
TL;DR: In this paper, a universal strategy is proposed to overcome the anode instability issues by rationally designing alloyed materials, using Zn-M alloys as model systems (M = Mn and other transition metals).
Abstract: Metal anode instability, including dendrite growth, metal corrosion, and hetero-ions interference, occurring at the electrolyte/electrode interface of aqueous batteries, are among the most critical issues hindering their widespread use in energy storage. Herein, a universal strategy is proposed to overcome the anode instability issues by rationally designing alloyed materials, using Zn-M alloys as model systems (M = Mn and other transition metals). An in-situ optical visualization coupled with finite element analysis is utilized to mimic actual electrochemical environments analogous to the actual aqueous batteries and analyze the complex electrochemical behaviors. The Zn-Mn alloy anodes achieved stability over thousands of cycles even under harsh electrochemical conditions, including testing in seawater-based aqueous electrolytes and using a high current density of 80 mA cm−2. The proposed design strategy and the in-situ visualization protocol for the observation of dendrite growth set up a new milestone in developing durable electrodes for aqueous batteries and beyond. Metal anode instability due to several intrinsic factors limits their widespread use in energy storage. Here, the authors report a 3D alloy anode via a universal alloy electrodeposition approach to overcome the anode instability issues and demonstrate a seawater-based aqueous battery.
Lawrence Berkeley National Laboratory1, National University of Singapore2, Stanford University3, National Ecological Observatory Network4, University of Wisconsin-Madison5, Oak Ridge National Laboratory6, McMaster University7, University of Nebraska–Lincoln8, University of California, Berkeley9, Agricultural Research Service10, University of British Columbia11, University of Colorado Boulder12, Ohio State University13, University of Florida14, University of Guelph15, University of Kansas16, Michigan State University17, Pacific Northwest National Laboratory18, United States Department of Agriculture19, University of New Mexico20, National Research Council21, Marine Biological Laboratory22, University of Alberta23, Virginia Commonwealth University24, University of Minnesota25, Université de Montréal26, Dalhousie University27, Carleton University28, Shinshu University29, Japan Agency for Marine-Earth Science and Technology30, Northern Arizona University31, Oregon State University32, Yale University33, Washington State University34, Harvard University35, Texas A&M University36, Indiana University37, Florida International University38, San Diego State University39, California State University, East Bay40, Wayne State University41, University of Sydney42, Wilfrid Laurier University43, University of Alabama44, Environment Canada45, United States Geological Survey46, Argonne National Laboratory47, Osaka Prefecture University48, University of Delaware49, University of Missouri50, University of Sheffield51
TL;DR: In this article, the authors evaluate the representativeness of flux footprints and evaluate potential biases as a consequence of the footprint-to-target-area mismatch, which can be used as a guide to identify site-periods suitable for specific applications.
Pacific Northwest National Laboratory1, Lawrence Berkeley National Laboratory2, Trinity College, Dublin3, Argonne National Laboratory4, Oak Ridge National Laboratory5, Ernst Ruska Centre6, Sandia National Laboratories7, National Institute of Standards and Technology8, University of Minnesota9, Virginia Tech10, Johns Hopkins University11
TL;DR: The open, highly integrated and data-driven microscopy architecture needed to realize transformative discoveries in the coming decade is discussed.
Abstract: Electron microscopy touches on nearly every aspect of modern life, underpinning materials development for quantum computing, energy and medicine. We discuss the open, highly integrated and data-driven microscopy architecture needed to realize transformative discoveries in the coming decade.
Sichuan University1, Lawrence Berkeley National Laboratory2, Karlsruhe Institute of Technology3, Massachusetts Institute of Technology4, Forschungszentrum Jülich5, University of Münster6, Texas A&M University7, Pacific Northwest National Laboratory8, Environmental Molecular Sciences Laboratory9, German Aerospace Center10, Argonne National Laboratory11, Stanford University12
TL;DR: In this article, the formation of a passivation film (that is, a solid electrolyte interphase) determines ionic diffusion and the structural and morphological evolution of the Li metal electrode upon cycling.
Abstract: Rechargeable Li metal batteries are currently limited by safety concerns, continuous electrolyte decomposition and rapid consumption of Li. These issues are mainly related to reactions occurring at the Li metal–liquid electrolyte interface. The formation of a passivation film (that is, a solid electrolyte interphase) determines ionic diffusion and the structural and morphological evolution of the Li metal electrode upon cycling. In this Review, we discuss spontaneous and operation-induced reactions at the Li metal–electrolyte interface from a corrosion science perspective. We highlight that the instantaneous formation of a thin protective film of corrosion products at the Li surface, which acts as a barrier to further chemical reactions with the electrolyte, precedes film reformation, which occurs during subsequent electrochemical stripping and plating of Li during battery operation. Finally, we discuss solutions to overcoming remaining challenges of Li metal batteries related to Li surface science, electrolyte chemistry, cell engineering and the intrinsic instability of the Li metal–electrolyte interface. Rechargeable Li metal batteries are currently limited by electrolyte decomposition and rapid Li consumption. Li plating and stripping greatly depend on the solid electrolyte interphase formed at the Li metal–liquid electrolyte interface. This Review discusses the reactions occurring at this interface from a corrosion science perspective, highlighting the requirements for an ideal passivation layer.
TL;DR: In this article, the authors elucidate the merits of rechargeable aqueous zinc batteries through side-by-side comparison to Li-ion batteries, examine the challenges and progress made in the pursuit of highly rechargeable alkaline and mild acidic batteries, and finally provide a holistic forward look at the technology.
TL;DR: In this article, the authors used synchrotron-based X-ray diffraction and pair distribution function analysis to identify and differentiate two elusive components, LiH and LiF, in the SEI of lithium metal anodes.
Abstract: A comprehensive understanding of the solid–electrolyte interphase (SEI) composition is crucial to developing high-energy batteries based on lithium metal anodes. A particularly contentious issue concerns the presence of LiH in the SEI. Here we report on the use of synchrotron-based X-ray diffraction and pair distribution function analysis to identify and differentiate two elusive components, LiH and LiF, in the SEI of lithium metal anodes. LiH is identified as a component of the SEI in high abundance, and the possibility of its misidentification as LiF in the literature is discussed. LiF in the SEI is found to have different structural features from LiF in the bulk phase, including a larger lattice parameter and a smaller grain size (<3 nm). These characteristics favour Li+ transport and explain why an ionic insulator, like LiF, has been found to be a favoured component for the SEI. Finally, pair distribution function analysis reveals key amorphous components in the SEI. X-ray diffraction and Rietveld refinement analysis confirm the presence of LiH in the solid–electrolyte interphase of lithium metal anodes.
TL;DR: This review offers an introduction to this discipline in terms that are relatable to metabolic engineers, as well as providing in-depth illustrative examples leveraging omics data and improving production.
TL;DR: In this paper, the authors present national low-emission scenarios to inform low emission development strategies for Australia, Brazil, Canada, China, EU-28, India, Indonesia, Japan, Republic of Korea, Russia and USA.
TL;DR: In this article, the authors highlight important aspects related to high-throughput screening, data analysis, and more which are vital to the success of achieving proteomic and metabolomic profiling at the single cell scale.
TL;DR: In this article, dual-doped nickel selenide nanoporous films (Fe,P-NiSe2 NFs) are designed as bifunctional catalysts for high-efficiency direct seawater electrolysis.
Abstract: Hydrogen (H2 ) production from direct seawater electrolysis is an economically appealing yet fundamentally and technically challenging approach to harvest clean energy. The current seawater electrolysis technology is significantly hindered by the poor stability and low selectivity of the oxygen evolution reaction (OER) due to the competition with chlorine evolution reaction in practical application. Herein, iron and phosphor dual-doped nickel selenide nanoporous films (Fe,P-NiSe2 NFs) are rationally designed as bifunctional catalysts for high-efficiency direct seawater electrolysis. The doping of Fe cation increases the selectivity and Faraday efficiency (FE) of the OER. While the doping of P anions improves the electronic conductivity and prevents the dissolution of selenide by forming a passivation layer containing P-O species. The Fe-dopant is identified as the primary active site for the hydrogen evolution reaction, and meanwhile, stimulates the adjacent Ni atoms as active centers for the OER. The experimental analyses and theoretical calculations provide an insightful understanding of the roles of dual-dopants in boosting seawater electrolysis. As a result, a current density of 0.8 A cm-2 is archived at 1.8 V with high OER selectivity and long-term stability for over 200 h, which surpasses the benchmarking platinum-group-metals-free electrolyzers.
German Aerospace Center1, Argonne National Laboratory2, Lawrence Berkeley National Laboratory3, Pacific Northwest National Laboratory4, Forschungszentrum Jülich5, University of Münster6, Massachusetts Institute of Technology7, Texas A&M University8, Karlsruhe Institute of Technology9, Environmental Molecular Sciences Laboratory10, Stanford University11
TL;DR: In this paper, the authors discuss how experimental and theoretical insights can provide possible pathways for reversible cycling of two-dimensional lithium metal and discuss improvements in the understanding of lithium metal nucleation, deposition, and stripping on the nanoscale.
Abstract: Despite the continuous increase in capacity, lithium-ion intercalation batteries are approaching their performance limits. As a result, research is intensifying on next-generation battery technologies. The use of a lithium metal anode promises the highest theoretical energy density and enables use of lithium-free or novel high-energy cathodes. However, the lithium metal anode suffers from poor morphological stability and Coulombic efficiency during cycling, especially in liquid electrolytes. In contrast to solid electrolytes, liquid electrolytes have the advantage of high ionic conductivity and good wetting of the anode, despite the lithium metal volume change during cycling. Rapid capacity fade due to inhomogeneous deposition and dissolution of lithium is the main hindrance to the successful utilization of the lithium metal anode in combination with liquid electrolytes. In this perspective, we discuss how experimental and theoretical insights can provide possible pathways for reversible cycling of two-dimensional lithium metal. Therefore, we discuss improvements in the understanding of lithium metal nucleation, deposition, and stripping on the nanoscale. As the solid–electrolyte interphase (SEI) plays a key role in the lithium morphology, we discuss how the proper SEI design might allow stable cycling. We highlight recent advances in conventional and (localized) highly concentrated electrolytes in view of their respective SEIs. We also discuss artificial interphases and three-dimensional host frameworks, which show prospects of mitigating morphological instabilities and suppressing large shape change on the electrode level.
TL;DR: Of the many potential beyond the Standard Model (BSM) topics DUNE will probe, this paper presents a selection of studies quantifying DUNE’s sensitivities to sterile neutrino mixing, heavy neutral leptons, non-standard interactions, CPT symmetry violation, Lorentz invariance violation, and other new physics topics that complement those at high-energy colliders and significantly extend the present reach.
Abstract: The Deep Underground Neutrino Experiment (DUNE) will be a powerful tool for a variety of physics topics. The high-intensity proton beams provide a large neutrino flux, sampled by a near detector system consisting of a combination of capable precision detectors, and by the massive far detector system located deep underground. This configuration sets up DUNE as a machine for discovery, as it enables opportunities not only to perform precision neutrino measurements that may uncover deviations from the present three-flavor mixing paradigm, but also to discover new particles and unveil new interactions and symmetries beyond those predicted in the Standard Model (SM). Of the many potential beyond the Standard Model (BSM) topics DUNE will probe, this paper presents a selection of studies quantifying DUNE’s sensitivities to sterile neutrino mixing, heavy neutral leptons, non-standard interactions, CPT symmetry violation, Lorentz invariance violation, neutrino trident production, dark matter from both beam induced and cosmogenic sources, baryon number violation, and other new physics topics that complement those at high-energy colliders and significantly extend the present reach.
TL;DR: In this paper, molecular engineering of fluorenone enables the alcohol electro-oxidation needed for reversible ketone hydrogenation and dehydrogenation at room temperature without the use of a catalyst.
Abstract: Aqueous redox flow batteries with organic active materials offer an environmentally benign, tunable, and safe route to large-scale energy storage. Development has been limited to a small palette of organics that are aqueous soluble and tend to display the necessary redox reversibility within the water stability window. We show how molecular engineering of fluorenone enables the alcohol electro-oxidation needed for reversible ketone hydrogenation and dehydrogenation at room temperature without the use of a catalyst. Flow batteries based on these fluorenone derivative anolytes operate efficiently and exhibit stable long-term cycling at ambient and mildly increased temperatures in a nondemanding environment. These results expand the palette to include reversible ketone to alcohol conversion but also suggest the potential for identifying other atypical organic redox couple candidates.
TL;DR: In this paper, the importance of diluents and their synergetic effects with the conductive salt and the solvating solvent in designing localized high-concentration electrolytes (LHCEs) was investigated.
Abstract: Electrolyte is very critical to the performance of the high-voltage lithium (Li) metal battery (LMB), which is one of the most attractive candidates for the next-generation high-density energy-storage systems. Electrolyte formulation and structure determine the physical properties of the electrolytes and their interfacial chemistries on the electrode surfaces. Localized high-concentration electrolytes (LHCEs) outperform state-of-the-art carbonate electrolytes in many aspects in LMBs due to their unique solvation structures. Types of fluorinated cosolvents used in LHCEs are investigated here in searching for the most suitable diluent for high-concentration electrolytes (HCEs). Nonsolvating solvents (including fluorinated ethers, fluorinated borate, and fluorinated orthoformate) added in HCEs enable the formation of LHCEs with high-concentration solvation structures. However, low-solvating fluorinated carbonate will coordinate with Li+ ions and form a second solvation shell or a pseudo-LHCE which diminishes the benefits of LHCE. In addition, it is evident that the diluent has significant influence on the electrode/electrolyte interphases (EEIs) beyond retaining the high-concentration solvation structures. Diluent molecules surrounding the high-concentration clusters could accelerate or decelerate the anion decomposition through coparticipation of diluent decomposition in the EEI formation. The varied interphase features lead to significantly different battery performance. This study points out the importance of diluents and their synergetic effects with the conductive salt and the solvating solvent in designing LHCEs. These systematic comparisons and fundamental insights into LHCEs using different types of fluorinated solvents can guide further development of advanced electrolytes for high-voltage LMBs.
TL;DR: In this article, a correlated structural and chemical evolution of silicon and the solid-electrolyte interphase (SEI) was revealed in three dimensions by integrating sensitive elemental tomography, an advanced algorithm and cryogenic scanning transmission electron microscopy.
Abstract: The solid–electrolyte interphase (SEI), a layer formed on the electrode surface, is essential for electrochemical reactions in batteries and critically governs the battery stability. Active materials, especially those with extremely high energy density, such as silicon (Si), often inevitably undergo a large volume swing upon ion insertion and extraction, raising a critical question as to how the SEI interactively responds to and evolves with the material and consequently controls the cycling stability of the battery. Here, by integrating sensitive elemental tomography, an advanced algorithm and cryogenic scanning transmission electron microscopy, we unveil, in three dimensions, a correlated structural and chemical evolution of Si and SEI. Corroborated with a chemomechanical model, we demonstrate progressive electrolyte permeation and SEI growth along the percolation channel of the nanovoids due to vacancy injection and condensation during the delithiation process. Consequently, the Si–SEI spatial configuration evolves from the classic ‘core–shell’ structure in the first few cycles to a ‘plum-pudding’ structure following extended cycling, featuring the engulfing of Si domains by the SEI, which leads to the disruption of electron conduction pathways and formation of dead Si, contributing to capacity loss. The spatially coupled interactive evolution model of SEI and active materials, in principle, applies to a broad class of high-capacity electrode materials, leading to a critical insight for remedying the fading of high-capacity electrodes. A correlated structural and chemical evolution of silicon and the solid–electrolyte interphase was unveiled in three dimensions by integrating sensitive elemental tomography, an advanced algorithm and cryogenic scanning transmission electron microscopy.