Showing papers by "Argonne National Laboratory published in 2021"

Strong tough hydrogels via the synergy of freeze-casting and salting out

Abstract: Natural load-bearing materials such as tendons have a high water content of about 70 per cent but are still strong and tough, even when used for over one million cycles per year, owing to the hierarchical assembly of anisotropic structures across multiple length scales1. Synthetic hydrogels have been created using methods such as electro-spinning2, extrusion3, compositing4,5, freeze-casting6,7, self-assembly8 and mechanical stretching9,10 for improved mechanical performance. However, in contrast to tendons, many hydrogels with the same high water content do not show high strength, toughness or fatigue resistance. Here we present a strategy to produce a multi-length-scale hierarchical hydrogel architecture using a freezing-assisted salting-out treatment. The produced poly(vinyl alcohol) hydrogels are highly anisotropic, comprising micrometre-scale honeycomb-like pore walls, which in turn comprise interconnected nanofibril meshes. These hydrogels have a water content of 70–95 per cent and properties that compare favourably to those of other tough hydrogels and even natural tendons; for example, an ultimate stress of 23.5 ± 2.7 megapascals, strain levels of 2,900 ± 450 per cent, toughness of 210 ± 13 megajoules per cubic metre, fracture energy of 170 ± 8 kilojoules per square metre and a fatigue threshold of 10.5 ± 1.3 kilojoules per square metre. The presented strategy is generalizable to other polymers, and could expand the applicability of structural hydrogels to conditions involving more demanding mechanical loading. A strategy that combines freeze-casting and salting-out treatments produces strong, tough, stretchable and fatigue-resistant poly(vinyl alcohol) hydrogels.

A genomic catalog of Earth’s microbiomes

Abstract: The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this approach to >10,000 metagenomes collected from diverse habitats covering all of Earth’s continents and oceans, including metagenomes from human and animal hosts, engineered environments, and natural and agricultural soils, to capture extant microbial, metabolic and functional potential. This comprehensive catalog includes 52,515 metagenome-assembled genomes representing 12,556 novel candidate species-level operational taxonomic units spanning 135 phyla. The catalog expands the known phylogenetic diversity of bacteria and archaea by 44% and is broadly available for streamlined comparative analyses, interactive exploration, metabolic modeling and bulk download. We demonstrate the utility of this collection for understanding secondary-metabolite biosynthetic potential and for resolving thousands of new host linkages to uncultivated viruses. This resource underscores the value of genome-centric approaches for revealing genomic properties of uncultivated microorganisms that affect ecosystem processes.

Planck 2018 results - VI. Cosmological parameters (Corrigendum)

Abstract: Author(s): Aghanim, N; Akrami, Y; Ashdown, M; Aumont, J; Baccigalupi, C; Ballardini, M; Banday, AJ; Barreiro, RB; Bartolo, N; Basak, S; Battye, R; Benabed, K; Bernard, JP; Bersanelli, M; Bielewicz, P; Bock, JJ; Bond, JR; Borrill, J; Bouchet, FR; Boulanger, F; Bucher, M; Burigana, C; Butler, RC; Calabrese, E; Cardoso, JF; Carron, J; Challinor, A; Chiang, HC; Chluba, J; Colombo, LPL; Combet, C; Contreras, D; Crill, BP; Cuttaia, F; De Bernardis, P; De Zotti, G; Delabrouille, J; Delouis, JM; DI Valentino, E; DIego, JM; Dore, O; Douspis, M; Ducout, A; Dupac, X; Dusini, S; Efstathiou, G; Elsner, F; Enslin, TA; Eriksen, HK; Fantaye, Y; Farhang, M; Fergusson, J; Fernandez-Cobos, R; Finelli, F; Forastieri, F; Frailis, M; Fraisse, AA; Franceschi, E; Frolov, A; Galeotta, S; Galli, S; Ganga, K; Genova-Santos, RT; Gerbino, M; Ghosh, T; Gonzalez-Nuevo, J; Gorski, KM; Gratton, S; Gruppuso, A; Gudmundsson, JE; Hamann, J; Handley, W; Hansen, FK; Herranz, D; Hildebrandt, SR; Hivon, E; Huang, Z; Jaffe, AH; Jones, WC; Karakci, A; Keihanen, E; Keskitalo, R; Kiiveri, K; Kim, J; Kisner, TS | Abstract: In the original version, the bounds given in Eqs. (87a) and (87b) on the contribution to the early-time optical depth, (15,30), contained a numerical error in deriving the 95th percentile from the Monte Carlo samples. The corrected 95% upper bounds are: τ(15,30) l 0:018 (lowE, flat τ(15, 30), FlexKnot), (1) τ(15, 30) l 0:023 (lowE, flat knot, FlexKnot): (2) These bounds are a factor of 3 larger than the originally reported results. Consequently, the new bounds do not significantly improve upon previous results from Planck data presented in Millea a Bouchet (2018) as was stated, but are instead comparable. Equations (1) and (2) give results that are now similar to those of Heinrich a Hu (2021), who used the same Planck 2018 data to derive a 95% upper bound of 0.020 using the principal component analysis (PCA) model and uniform priors on the PCA mode amplitudes.

A high-energy and long-cycling lithium-sulfur pouch cell via a macroporous catalytic cathode with double-end binding sites.

Abstract: Lithium–sulfur batteries are attractive alternatives to lithium-ion batteries because of their high theoretical specific energy and natural abundance of sulfur. However, the practical specific energy and cycle life of Li–S pouch cells are significantly limited by the use of thin sulfur electrodes, flooded electrolytes and Li metal degradation. Here we propose a cathode design concept to achieve good Li–S pouch cell performances. The cathode is composed of uniformly embedded ZnS nanoparticles and Co–N–C single-atom catalyst to form double-end binding sites inside a highly oriented macroporous host, which can effectively immobilize and catalytically convert polysulfide intermediates during cycling, thus eliminating the shuttle effect and lithium metal corrosion. The ordered macropores enhance ionic transport under high sulfur loading by forming sufficient triple-phase boundaries between catalyst, conductive support and electrolyte. This design prevents the formation of inactive sulfur (dead sulfur). Our cathode structure shows improved performances in a pouch cell configuration under high sulfur loading and lean electrolyte operation. A 1-A-h-level pouch cell with only 100% lithium excess can deliver a cell specific energy of >300 W h kg−1 with a Coulombic efficiency >95% for 80 cycles. The shuttling effect in Li–S batteries can be drastically suppressed by using a single-atom Co catalyst and polar ZnS nanoparticles embedded in a macroporous conductive matrix as a cathode. Using this strategy, Li–S pouch cells show stable cycling and high energy performances.

New roads and challenges for fuel cells in heavy-duty transportation

Abstract: The recent release of hydrogen economy roadmaps for several major countries emphasizes the need for accelerated worldwide investment in research and development activities for hydrogen production, storage, infrastructure and utilization in transportation, industry and the electrical grid. Due to the high gravimetric energy density of hydrogen, the focus of technologies that utilize this fuel has recently shifted from light-duty automotive to heavy-duty vehicle applications. Decades of development of cost-effective and durable polymer electrolyte membrane fuel cells must now be leveraged to meet the increased efficiency and durability requirements of the heavy-duty vehicle market. This Review summarizes the latest market outlooks and targets for truck, bus, locomotive and marine applications. Required changes to the fuel-cell system and operating conditions for meeting Class 8 long-haul truck targets are presented. The necessary improvements in fuel-cell materials and integration are also discussed against the benchmark of current passenger fuel-cell electric vehicles. Fuel cells are increasingly being considered for powertrains of heavy-duty transportation. Cullen et al. survey the technical challenges of fuel cells at both the system and materials level for transportation application and outline the roadmap for future development.

Chemical vapour deposition of Fe-N-C oxygen reduction catalysts with full utilization of dense Fe-N4 sites.

Abstract: Replacing scarce and expensive platinum (Pt) with metal–nitrogen–carbon (M–N–C) catalysts for the oxygen reduction reaction in proton exchange membrane fuel cells has largely been impeded by the low oxygen reduction reaction activity of M–N–C due to low active site density and site utilization. Herein, we overcome these limits by implementing chemical vapour deposition to synthesize Fe–N–C by flowing iron chloride vapour over a Zn–N–C substrate at 750 °C, leading to high-temperature trans-metalation of Zn–N4 sites into Fe–N4 sites. Characterization by multiple techniques shows that all Fe–N4 sites formed via this approach are gas-phase and electrochemically accessible. As a result, the Fe–N–C catalyst has an active site density of 1.92 × 1020 sites per gram with 100% site utilization. This catalyst delivers an unprecedented oxygen reduction reaction activity of 33 mA cm−2 at 0.90 V (iR-corrected; i, current; R, resistance) in a H2–O2 proton exchange membrane fuel cell at 1.0 bar and 80 °C. Replacing platinum with metal–nitrogen–carbon catalysts for the oxygen reduction reaction in proton exchange membrane fuel cells has been impeded by low activity. These limitations have now been overcome by the trans-metalation of Zn–N4 sites into Fe–N4 sites.

Accurate Determination of the Neutron Skin Thickness of ^{208}Pb through Parity-Violation in Electron Scattering.

Abstract: We report a precision measurement of the parity-violating asymmetry A_{PV} in the elastic scattering of longitudinally polarized electrons from ^{208}Pb. We measure A_{PV}=550±16(stat)±8(syst) parts per billion, leading to an extraction of the neutral weak form factor F_{W}(Q^{2}=0.00616 GeV^{2})=0.368±0.013. Combined with our previous measurement, the extracted neutron skin thickness is R_{n}-R_{p}=0.283±0.071 fm. The result also yields the first significant direct measurement of the interior weak density of ^{208}Pb: ρ_{W}^{0}=-0.0796±0.0036(exp)±0.0013(theo) fm^{-3} leading to the interior baryon density ρ_{b}^{0}=0.1480±0.0036(exp)±0.0013(theo) fm^{-3}. The measurement accurately constrains the density dependence of the symmetry energy of nuclear matter near saturation density, with implications for the size and composition of neutron stars.

Structure of papain-like protease from SARS-CoV-2 and its complexes with non-covalent inhibitors.

Abstract: The pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to expand Papain-like protease (PLpro) is one of two SARS-CoV-2 proteases potentially targetable with antivirals PLpro is an attractive target because it plays an essential role in cleavage and maturation of viral polyproteins, assembly of the replicase-transcriptase complex, and disruption of host responses We report a substantive body of structural, biochemical, and virus replication studies that identify several inhibitors of the SARS-CoV-2 enzyme We determined the high resolution structure of wild-type PLpro, the active site C111S mutant, and their complexes with inhibitors This collection of structures details inhibitors recognition and interactions providing fundamental molecular and mechanistic insight into PLpro All compounds inhibit the peptidase activity of PLpro in vitro, some block SARS-CoV-2 replication in cell culture assays These findings will accelerate structure-based drug design efforts targeting PLpro to identify high-affinity inhibitors of clinical value

Ultra-high-voltage Ni-rich layered cathodes in practical Li metal batteries enabled by a sulfonamide-based electrolyte

Abstract: By increasing the charging voltage, a cell specific energy of >400 W h kg−1 is achievable with LiNi0.8Mn0.1Co0.1O2 in Li metal batteries. However, stable cycling of high-nickel cathodes at ultra-high voltages is extremely challenging. Here we report that a rationally designed sulfonamide-based electrolyte enables stable cycling of commercial LiNi0.8Co0.1Mn0.1O2 with a cut-off voltage up to 4.7 V in Li metal batteries. In contrast to commercial carbonate electrolytes, the electrolyte not only suppresses side reactions, stress-corrosion cracking, transition-metal dissolution and impedance growth on the cathode side, but also enables highly reversible Li metal stripping and plating leading to a compact morphology and low pulverization. Our lithium-metal battery delivers a specific capacity >230 mA h g−1 and an average Coulombic efficiency >99.65% over 100 cycles. Even under harsh testing conditions, the 4.7 V lithium-metal battery can retain >88% capacity for 90 cycles, advancing practical lithium-metal batteries. Charging at high voltages in principle makes batteries energy dense, but this is often achieved at the cost of the cycling stability. Here the authors design a sulfonamide-based electrolyte to enable a Li metal battery with a state-of-the-art cathode at an ultra-high voltage of 4.7 V while maintaining cyclability.

Rejuvenating dead lithium supply in lithium metal anodes by iodine redox

Abstract: Inactive lithium (more frequently called dead lithium) in the forms of solid–electrolyte interphase and electrically isolated metallic lithium is principally responsible for the performance decay commonly observed in lithium metal batteries. A fundamental solution of recovering dead lithium is urgently needed to stabilize lithium metal batteries. Here we quantify the solid–electrolyte interphase components, and determine their relation with the formation of electrically isolated dead lithium metal. We present a lithium restoration method based on a series of iodine redox reactions mainly involving I3−/I−. Using a biochar capsule host for iodine, we show that the I3−/I− redox takes place spontaneously, effectively rejuvenating dead lithium to compensate the lithium loss. Through this design, a full-cell using a very limited lithium metal anode exhibits an excellent lifespan of 1,000 cycles with a high Coulombic efficiency of 99.9%. We also demonstrate the design with a commercial cathode in pouch cells. Cycling lithium batteries often results in inactive lithium that no longer participates in redox reactions, leading to performance deterioration. Here the authors use an iodic species to react with inactive lithium, bringing it back to life and thus making batteries last longer.

Gradient-cell–structured high-entropy alloy with exceptional strength and ductility

Abstract: Most multicomponent high-entropy alloys (HEAs) lose ductility with increasing strength, similar to conventional materials. We controllably introduced novel gradient nano-scaled dislocation-cell str...

Cation-disordered rocksalt-type high-entropy cathodes for Li-ion batteries

Abstract: High-entropy (HE) ceramics, by analogy with HE metallic alloys, are an emerging class of solid solutions composed of a large number of species. These materials offer the benefit of large compositional flexibility and can be used in a wide variety of applications, including thermoelectrics, catalysts, superionic conductors and battery electrodes. We show here that the HE concept can lead to very substantial improvements in performance in battery cathodes. Among lithium-ion cathodes, cation-disordered rocksalt (DRX)-type materials are an ideal platform within which to design HE materials because of their demonstrated chemical flexibility. By comparing a group of DRX cathodes containing two, four or six transition metal (TM) species, we show that short-range order systematically decreases, whereas energy density and rate capability systematically increase, as more TM cation species are mixed together, despite the total metal content remaining fixed. A DRX cathode with six TM species achieves 307 mAh g−1 (955 Wh kg−1) at a low rate (20 mA g−1), and retains more than 170 mAh g−1 when cycling at a high rate of 2,000 mA g−1. To facilitate further design in this HE DRX space, we also present a compatibility analysis of 23 different TM ions, and successfully synthesize a phase-pure HE DRX compound containing 12 TM species as a proof of concept. High-entropy ceramics are solid solutions offering compositional flexibility and wide variety of applicability. High-entropy concepts are shown to lead to substantial performance improvement in cation-disordered rocksalt-type cathodes for Li-ion batteries.

A stable low-temperature H2-production catalyst by crowding Pt on α-MoC.

Abstract: The water–gas shift (WGS) reaction is an industrially important source of pure hydrogen (H2) at the expense of carbon monoxide and water1,2. This reaction is of interest for fuel-cell applications, but requires WGS catalysts that are durable and highly active at low temperatures3. Here we demonstrate that the structure (Pt1–Ptn)/α-MoC, where isolated platinum atoms (Pt1) and subnanometre platinum clusters (Ptn) are stabilized on α-molybdenum carbide (α-MoC), catalyses the WGS reaction even at 313 kelvin, with a hydrogen-production pathway involving direct carbon monoxide dissociation identified. We find that it is critical to crowd the α-MoC surface with Pt1 and Ptn species, which prevents oxidation of the support that would cause catalyst deactivation, as seen with gold/α-MoC (ref. 4), and gives our system high stability and a high metal-normalized turnover number of 4,300,000 moles of hydrogen per mole of platinum. We anticipate that the strategy demonstrated here will be pivotal for the design of highly active and stable catalysts for effective activation of important molecules such as water and carbon monoxide for energy production. A stable, low-temperature water–gas shift catalyst is achieved by crowding platinum atoms and clusters on α-molybdenum carbide; the crowding protects the support from oxidation that would cause catalyst deactivation.

Hierarchical crack buffering triples ductility in eutectic herringbone high-entropy alloys

Abstract: In human-made malleable materials, microdamage such as cracking usually limits material lifetime. Some biological composites, such as bone, have hierarchical microstructures that tolerate cracks but cannot withstand high elongation. We demonstrate a directionally solidified eutectic high-entropy alloy (EHEA) that successfully reconciles crack tolerance and high elongation. The solidified alloy has a hierarchically organized herringbone structure that enables bionic-inspired hierarchical crack buffering. This effect guides stable, persistent crystallographic nucleation and growth of multiple microcracks in abundant poor-deformability microstructures. Hierarchical buffering by adjacent dynamic strain-hardened features helps the cracks to avoid catastrophic growth and percolation. Our self-buffering herringbone material yields an ultrahigh uniform tensile elongation (~50%), three times that of conventional nonbuffering EHEAs, without sacrificing strength.

The NUBASE2020 evaluation of nuclear physics properties

Abstract: The NUBASE2020 evaluation contains the recommended values of the main nuclear physics properties for all nuclei in their ground and excited, isomeric (T1/2 \begin{document}$\ge$\end{document} 100 ns) states. It encompasses all experimental data published in primary (journal articles) and secondary (mainly laboratory reports and conference proceedings) references, together with the corresponding bibliographical information. In cases where no experimental data were available for a particular nuclide, trends in the behavior of specific properties in neighboring nuclei were examined and estimated values are proposed. Evaluation procedures and policies that were used during the development of this evaluated nuclear data library are presented, together with a detailed table of recommended values and their uncertainties.

Poly(vinyl alcohol) Hydrogels with Broad-Range Tunable Mechanical Properties via the Hofmeister Effect.

Abstract: Hydrogels, exhibiting wide applications in soft robotics, tissue engineering, implantable electronics, etc., often require sophisticately tailoring of the hydrogel mechanical properties to meet specific demands. For examples, soft robotics necessitates tough hydrogels; stem cell culturing demands various tissue-matching modulus; and neuron probes desire dynamically tunable modulus. Herein, a strategy to broadly alter the mechanical properties of hydrogels reversibly via tuning the aggregation states of the polymer chains by ions based on the Hofmeister effect is reported. An ultratough poly(vinyl alcohol) (PVA) hydrogel as an exemplary material (toughness 150 ± 20 MJ m-3 ), which surpasses synthetic polymers like poly(dimethylsiloxane), synthetic rubber, and natural spider silk is fabricated. With various ions, the hydrogel's various mechanical properties are continuously and reversibly in situ modulated over a large window: tensile strength from 50 ± 9 kPa to 15 ± 1 MPa, toughness from 0.0167 ± 0.003 to 150 ± 20 MJ m-3 , elongation from 300 ± 100% to 2100 ± 300%, and modulus from 24 ± 2 to 2500 ± 140 kPa. Importantly, the ions serve as gelation triggers and property modulators only, not necessarily required to remain in the gel, maintaining the high biocompatibility of PVA without excess ions. This strategy, enabling high mechanical performance and broad dynamic tunability, presents a universal platform for broad applications from biomedicine to wearable electronics.

Quantum Computer Systems for Scientific Discovery

Abstract: The great promise of quantum computers comes with the dual challenges of building them and finding their useful applications. We argue that these two challenges should be considered together, by co-designing full-stack quantum computer systems along with their applications in order to hasten their development and potential for scientific discovery. In this context, we identify scientific and community needs, opportunities, a sampling of a few use case studies, and significant challenges for the development of quantum computers for science over the next 2--10 years. This document is written by a community of university, national laboratory, and industrial researchers in the field of Quantum Information Science and Technology, and is based on a summary from a U.S. National Science Foundation workshop on Quantum Computing held on October 21--22, 2019 in Alexandria, VA.

Understanding Co roles towards developing Co-free Ni-rich cathodes for rechargeable batteries

Abstract: Current bottlenecks in cobalt (Co) supply have negatively impacted commercial battery production and inspired the development of cathode materials that are less reliant on Co. However, complete Co elimination is prevented by the lack of fundamental understanding of the impact of Co on cathode capacity and structural stability, as well as the lack of effective substitute components in practice. Here we investigate the roles of Co in purposely designed systems that include both Co-rich and Mn-substituted Co-free cathodes. Our results affirmed that Co plays an undeniable role in fast capacity and/or structural degradation, and found that Co is more destructive than Ni at high potentials, which offers unexpected but encouraging perspectives for Co reduction. Moreover, Mn substitution effectively alleviates the destructive effects of Co and enables a high potential functionality. With these fundamental discoveries, we demonstrated a series of LiNiαMnβXγO2 (X = single or multiple dopants) as a promising candidate for Co-free cathodes. Reduction on cobalt reliance is an urgent requirement in the development of sustainable cathode materials for Li-ion batteries. Here the authors analyse the roles of cobalt and its interplay with other ions in high-nickel layered oxides, and deduce a material formula for promising cobalt-free cathodes.

Machine learning pipeline for battery state-of-health estimation

Abstract: Lithium-ion batteries are ubiquitous in applications ranging from portable electronics to electric vehicles Irrespective of the application, reliable real-time estimation of battery state of health (SOH) by on-board computers is crucial to the safe operation of the battery, ultimately safeguarding asset integrity In this Article, we design and evaluate a machine learning pipeline for estimation of battery capacity fade—a metric of battery health—on 179 cells cycled under various conditions The pipeline estimates battery SOH with an associated confidence interval by using two parametric and two non-parametric algorithms Using segments of charge voltage and current curves, the pipeline engineers 30 features, performs automatic feature selection and calibrates the algorithms When deployed on cells operated under the fast-charging protocol, the best model achieves a root-mean-squared error of 045% This work provides insights into the design of scalable data-driven models for battery SOH estimation, emphasizing the value of confidence bounds around the prediction The pipeline methodology combines experimental data with machine learning modelling and could be applied to other critical components that require real-time estimation of SOH Rechargeable lithium-ion batteries play a crucial role in many modern-day applications, including portable electronics and electric vehicles, but they degrade over time To ensure safe operation, a battery’s ‘state of health’ should be monitored in real time, and this machine learning pipeline, tested on a variety of charging conditions, can provide such an online estimation of battery state of health

Challenges for and Pathways toward Li-Metal-Based All-Solid-State Batteries

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

CsPbBr3 perovskite detectors with 1.4% energy resolution for high-energy γ-rays

Abstract: Halide perovskite semiconductors are poised to revitalize the field of ionizing radiation detection as they have done to solar photovoltaics. We show that all-inorganic perovskite CsPbBr3 devices resolve 137Cs 662-keV γ-rays with 1.4% energy resolution, as well as other X- and γ-rays with energies ranging from tens of keV to over 1 MeV in ambipolar sensing and unipolar hole-only sensing modes with crystal volumes of 6.65 mm3 and 297 mm3, respectively. We report the scale-up of CsPbBr3 ingots to up to 1.5 inches in diameter with an excellent hole mobility–lifetime product of 8 × 10−3 cm2 V−1 and a long hole lifetime of up to 296 μs. CsPbBr3 detectors demonstrate a wide temperature region from ~2 °C to ~70 °C for stable operation. Detectors protected with suitable encapsulants show a uniform response for over 18 months. Consequently, we identify perovskite CsPbBr3 semiconductor as an exceptional candidate for new-generation high-energy γ-ray detection. Energy resolution of high-energy photon detectors is desired for applications ranging from biomedical imaging to homeland security. In this work, perovskite-based γ-ray detection with 1.4% energy resolution is demonstrated.

Oxygen evolution reaction over catalytic single-site Co in a well-defined brookite TiO2 nanorod surface

Abstract: Efficient electrocatalysts for the oxygen evolution reaction (OER) are paramount to the development of electrochemical devices for clean energy and fuel conversion. However, the structural complexity of heterogeneous electrocatalysts makes it a great challenge to elucidate the surface catalytic sites and OER mechanisms. Here, we report that catalytic single-site Co in a well-defined brookite TiO2 nanorod (210) surface (Co-TiO2) presents turnover frequencies that are among the highest for Co-based heterogeneous catalysts reported to date, reaching 6.6 ± 1.2 and 181.4 ± 28 s−1 at 300 and 400 mV overpotentials, respectively. Based on grand canonical quantum mechanics calculations and the single-site Co atomic structure validated by in situ and ex situ spectroscopic probes, we have established a full description of the catalytic reaction kinetics for Co-TiO2 as a function of applied potential, revealing an adsorbate evolution mechanism for the OER. The computationally predicted Tafel slope and turnover frequencies exhibit exceedingly good agreement with experiment. The rational design of efficient water oxidation electrocatalysts is paramount to the development of electrochemical devices. Now, a Co-TiO2 single-site catalyst is presented for alkaline water oxidation with high intrinsic activity, and its mechanism has been studied by grand canonical quantum mechanics calculations and in situ techniques.

Linking void and interphase evolution to electrochemistry in solid-state batteries using operando X-ray tomography.

Abstract: Despite progress in solid-state battery engineering, our understanding of the chemo-mechanical phenomena that govern electrochemical behaviour and stability at solid–solid interfaces remains limited compared to at solid–liquid interfaces. Here, we use operando synchrotron X-ray computed microtomography to investigate the evolution of lithium/solid-state electrolyte interfaces during battery cycling, revealing how the complex interplay among void formation, interphase growth and volumetric changes determines cell behaviour. Void formation during lithium stripping is directly visualized in symmetric cells, and the loss of contact that drives current constriction at the interface between lithium and the solid-state electrolyte (Li10SnP2S12) is quantified and found to be the primary cause of cell failure. The interphase is found to be redox-active upon charge, and global volume changes occur owing to partial molar volume mismatches at either electrode. These results provide insight into how chemo-mechanical phenomena can affect cell performance, thus facilitating the development of solid-state batteries. Understanding electrochemical behaviour and stability at solid–solid interfaces remains challenging. Operando synchrotron X-ray computed microtomography loss reveals that reconfiguration of interfacial contact is critical to explain cell failure during solid-state battery cycling.

Emerging materials intelligence ecosystems propelled by machine learning

Abstract: The age of cognitive computing and artificial intelligence (AI) is just dawning. Inspired by its successes and promises, several AI ecosystems are blossoming, many of them within the domain of materials science and engineering. These materials intelligence ecosystems are being shaped by several independent developments. Machine learning (ML) algorithms and extant materials data are utilized to create surrogate models of materials properties and performance predictions. Materials data repositories, which fuel such surrogate model development, are mushrooming. Automated data and knowledge capture from the literature (to populate data repositories) using natural language processing approaches is being explored. The design of materials that meet target property requirements and of synthesis steps to create target materials appear to be within reach, either by closed-loop active-learning strategies or by inverting the prediction pipeline using advanced generative algorithms. AI and ML concepts are also transforming the computational and physical laboratory infrastructural landscapes used to create materials data in the first place. Surrogate models that can outstrip physics-based simulations (on which they are trained) by several orders of magnitude in speed while preserving accuracy are being actively developed. Automation, autonomy and guided high-throughput techniques are imparting enormous efficiencies and eliminating redundancies in materials synthesis and characterization. The integration of the various parts of the burgeoning ML landscape may lead to materials-savvy digital assistants and to a human–machine partnership that could enable dramatic efficiencies, accelerated discoveries and increased productivity. Here, we review these emergent materials intelligence ecosystems and discuss the imminent challenges and opportunities. The materials research landscape is being transformed by the infusion of approaches based on machine learning. This Review discusses the emerging materials intelligence ecosystems and the potential of human–machine partnerships for fast and efficient virtual materials screening, development and discovery.

Stable, high-performance, dendrite-free, seawater-based aqueous batteries.

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.

Masitinib is a broad coronavirus 3CL inhibitor that blocks replication of SARS-CoV-2.

Abstract: There is an urgent need for antiviral agents that treat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We screened a library of 1900 clinically safe drugs against OC43, a human beta coronavirus that causes the common cold, and evaluated the top hits against SARS-CoV-2. Twenty drugs significantly inhibited replication of both viruses in cultured human cells. Eight of these drugs inhibited the activity of the SARS-CoV-2 main protease, 3CLpro, with the most potent being masitinib, an orally bioavailable tyrosine kinase inhibitor. X-ray crystallography and biochemistry show that masitinib acts as a competitive inhibitor of 3CLpro. Mice infected with SARS-CoV-2 and then treated with masitinib showed >200-fold reduction in viral titers in the lungs and nose, as well as reduced lung inflammation. Masitinib was also effective in vitro against all tested variants of concern (B.1.1.7, B.1.351, and P.1).

Towards data-driven next-generation transmission electron microscopy.

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.

Networked Microgrids for Grid Resilience, Robustness, and Efficiency: A Review

Abstract: Networked microgrids (NMGs) are clusters of microgrids that are physically connected and functionally interoperable The massive and unprecedented deployment of smart grid technologies, new business models, and involvement of new stakeholders enable NMGs to be a conceptual operation paradigm for future distribution systems Much work needs to be done, however, to enable NMGs to achieve seamless coordination, including physical, communication, and functional integration In this paper, we review and summarize the state-of-the-art methodologies for operation and control of NMGs We also specifically discuss the notion of dynamic boundaries for advanced microgrid applications In addition, we introduce the opportunities, challenges, and possible solutions regarding NMGs for improving grid resilience, robustness, and efficiency