ABSTRACT
The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials and chemical data. Since the first release of the OPTIMADE specification (v1.0), the API has undergone significant development, leading to the v1.2 release, and has underpinned multiple scientific studies. In this work, we highlight the latest features of the API format, accompanying software tools, and provide an update on the implementation of OPTIMADE in contributing materials databases. We end by providing several use cases that demonstrate the utility of the OPTIMADE API in materials research that continue to drive its ongoing development.
ABSTRACT
Monolayer protected metal clusters comprise a rich class of molecular systems and are promising candidate materials for a variety of applications. While a growing number of protected nanoclusters have been synthesized and characterized in crystalline forms, their dynamical behavior in solution, including prenucleation cluster formation, is not well understood due to limitations both in characterization and first-principles modeling techniques. Recent advancements in machine-learned interatomic potentials are rapidly enabling the study of complex interactions such as dynamical behavior and reactivity on the nanoscale. Here, we develop an Au-S-C-H atomic cluster expansion (ACE) interatomic potential for efficient and accurate molecular dynamics simulations of thiolate-protected gold nanoclusters (Aun(SCH3)m). Trained on more than 30,000 density functional theory calculations of gold nanoclusters, the interatomic potential exhibits ab initio level accuracy in energies and forces and replicates nanocluster dynamics including thermal vibration and chiral inversion. Long dynamics simulations (up to 0.1 µs time scale) reveal a mechanism explaining the thermal instability of neutral Au25(SR)18 clusters. Specifically, we observe multiple stages of isomerization of the Au25(SR)18 cluster, including a chiral isomer. Additionally, we simulate coalescence of two Au25(SR)18 clusters and observe series of clusters where the formation mechanisms are critically mediated by ligand exchange in the form of [Au-S]n rings.
ABSTRACT
During Li-ion battery operation, (electro)chemical side reactions occur within the cell that can promote or degrade performance. These complex reactions produce byproducts in the solid, liquid, and gas phases. Studying byproducts in these three phases can help optimize battery lifetimes. To relate the measured gas-phase byproducts to species dissolved in the liquid-phase, equilibrium proprieties such as the Henry's law constants are required. The present work implements a pressure decay experiment to determine the thermodynamic equilibrium concentrations between the gas and liquid phases for ethylene (C2H4) and carbon dioxide (CO2), which are two gases commonly produced in Li-ion batteries, with an electrolyte of 1.2 M LiPF6 in 3:7 wt/wt ethylene carbonate/ethyl methyl carbonate and 3 wt % fluoroethylene carbonate (15:25:57:3 wt % total composition). The experimentally measured pressure decay curve is fit to an analytical dissolution model and extrapolated to predict the final pressure at equilibrium. The relationship between the partial pressures and concentration of dissolved gas in electrolyte at equilibrium is then used to determine Henry's law constants of 2.0 × 104 kPa for C2H4 and k CO2 = 1.1 × 104 kPa for CO2. These values are compared to Henry's law constants predicted from density functional theory and show good agreement within a factor of 3.
ABSTRACT
Rechargeable multivalent-ion batteries are attractive alternatives to Li-ion batteries to mitigate their issues with metal resources and metal anodes. However, many challenges remain before they can be practically used due to the low solid-state mobility of multivalent ions. In this study, a promising material identified by high-throughput computational screening is investigated, ε-VOPO4, as a Mg cathode. The experimental and computational evaluation of ε-VOPO4 suggests that it may provide an energy density of >200 Wh kg-1 based on the average voltage of a complete cycle, significantly more than that of well-known Chevrel compounds. Furthermore, this study finds that Mg-ion diffusion can be enhanced by co-intercalation of Li or Na, pointing at interesting correlation dynamics of slow and fast ions.
ABSTRACT
Multivalent-ion battery technologies are increasingly attractive options for meeting diverse energy storage needs. Calcium ion batteries (CIB) are particularly appealing candidates for their earthly abundance, high theoretical volumetric energy density, and relative safety advantages. At present, only a few Ca-ion electrolyte systems are reported to reversibly plate at room temperature: for example, aluminates and borates, including Ca[TPFA]2, where [TPFA]- = [Al(OC(CF3)3)4]- and Ca[B(hfip)4]2, [B(hfip)4]2- = [B(OCH(CF3)2)4]-. Analyzing the structure of these salts reveals a common theme: the prevalent use of a weakly coordinating anion (WCA) consisting of a tetracoordinate aluminum/boron (Al/B) center with fluorinated alkoxides. Leveraging the concept of theory-aided design, we report an innovative, one-pot synthesis of two new calcium-ion electrolyte salts (Ca[Al(tftb)4]2, Ca[Al(hftb)4]2) and two reported salts (Ca[Al(hfip)4]2 and Ca[TPFA]2) where hfip = (-OCH(CF3)2), tftb = (-OC(CF3)(Me)2), hftb = (-OC(CF3)2(Me)), [TPFA]- = [Al(OC(CF3)3)4]-. We also reveal the dependence of Coulombic efficiency on their inherent propensity for cation-anion coordination.
ABSTRACT
Identifying next-generation batteries with multivalent ions, such as Ca2+ is an active area of research to meet the increasing demand for large-scale, renewable energy storage solutions. Despite the promise of higher energy densities with multivalent batteries, one of their main challenges is addressing the sluggish kinetics in cathodes that arise from stronger electrostatic interactions between the multivalent ion and host lattice. In this paper, zircons are theoretically and experimentally evaluated as Ca cathodes. A migration barrier as low as 113 meV is computationally found in YVO4, which is the lowest Ca2+ barrier reported to date. Low barriers are confirmed across 18 zircon compositions, which are related to the low coordination change and reduced interstitial site preference of Ca2+ along the diffusion pathway. Among the four materials (BiVO4, YVO4, EuCrO4, and YCrO4) that were synthesized, characterized, and electrochemically cycled, the highest initial capacity of 81 mA h/g and the most reversible capacity of 65 mA h/g were achieved in YVO4 and BiVO4, respectively. Despite the facile migration of multivalent ions in zircons, density functional theory predictions of the unstable, discharged structures at higher Ca2+ concentrations (Cax>0.25ABO4), the low dimensionality of the migration pathway, and the defect analysis of the B site atom can rationalize the limited intercalation observed upon electrochemical cycling.
ABSTRACT
All solid-state batteries (SSBs) are considered the most promising path to enabling higher energy-density portable energy, while concurrently improving safety as compared to current liquid electrolyte solutions. However, the desire for high energy necessitates the choice of high-voltage cathodes, such as nickel-rich layered oxides, where degradation phenomena related to oxygen loss and structural densification at the cathode surface are known to significantly compromise the cycle and thermal stability. In this work, we show, for the first time, that even in an SSB, and when protected by an intact amorphous coating, the LiNi0.5Mn0.3Co0.2O2 (NMC532) surface transforms from a layered structure into a rocksalt-like structure after electrochemical cycling. The transformation of the surface structure of the Li3B11O18 (LBO)-coated NMC532 cathode in a thiophosphate-based solid-state cell is characterized by high-resolution complementary electron microscopy techniques and electron energy loss spectroscopy. Ab initio molecular dynamics corroborate facile transport of O2- in the LBO coating and in other typical coating materials. This work identifies that oxygen loss remains a formidable challenge and barrier to long-cycle life high-energy storage, even in SSBs with durable, amorphous cathode coatings, and directs attention to considering oxygen permeability as an important new design criteria for coating materials.
ABSTRACT
Bismuth ferrite (BiFeO3) is a multiferroic material that exhibits both ferroelectricity and canted antiferromagnetism at room temperature, making it a unique candidate in the development of electric-field controllable magnetic devices. The magnetic moments in BiFeO3 are arranged into a spin cycloid, resulting in unique magnetic properties which are tied to the ferroelectric order. Previous understanding of this coupling has relied on average, mesoscale measurements. Using nitrogen vacancy-based diamond magnetometry, we observe the magnetic spin cycloid structure of BiFeO3 in real space. This structure is magnetoelectrically coupled through symmetry to the ferroelectric polarization and this relationship is maintained through electric field switching. Through a combination of in-plane and out-of-plane electrical switching, coupled with ab initio studies, we have discovered that the epitaxy from the substrate imposes a magnetoelastic anisotropy on the spin cycloid, which establishes preferred cycloid propagation directions. The energy landscape of the cycloid is shaped by both the ferroelectric degree of freedom and strain-induced anisotropy, restricting the spin spiral propagation vector to changes to specific switching events.
ABSTRACT
Nuclear magnetic resonance (NMR) spectroscopy is an important analytical technique in synthetic organic chemistry, but its integration into high-throughput experimentation workflows has been limited by the necessity of manually analyzing the NMR spectra of new chemical entities. Current efforts to automate the analysis of NMR spectra rely on comparisons to databases of reported spectra for known compounds and, therefore, are incompatible with the exploration of new chemical space. By reframing the NMR spectrum of a reaction mixture as a joint probability distribution, we have used Hamiltonian Monte Carlo Markov Chain and density functional theory to fit the predicted NMR spectra to those of crude reaction mixtures. This approach enables the deconvolution and analysis of the spectra of mixtures of compounds without relying on reported spectra. The utility of our approach to analyze crude reaction mixtures is demonstrated with the experimental spectra of reactions that generate a mixture of isomers, such as Wittig olefination and C-H functionalization reactions. The correct identification of compounds in a reaction mixture and their relative concentrations is achieved with a mean absolute error as low as 1%.
Subject(s)
Proton Magnetic Resonance Spectroscopy , Monte Carlo Method , Markov Chains , Density Functional TheoryABSTRACT
Spectator ions have known and emerging roles in aqueous metal-cation chemistry, respectively directing solubility, speciation, and reactivity. Here, we isolate and structurally characterize the last two metastable members of the alkali uranyl triperoxide series, the Rb+ and Cs+ salts (Cs-U1 and Rb-U1). We document their rapid solution polymerization via small-angle X-ray scattering, which is compared to the more stable Li+, Na+ and K+ analogues. To understand the role of the alkalis, we also quantify alkali-hydroxide promoted peroxide deprotonation and decomposition, which generally exhibits increasing reactivity with increasing alkali size. Cs-U1, the most unstable of the uranyl triperoxide monomers, undergoes ambient direct air capture of CO2 in the solid-state, converting to Cs4[UVIO2(CO3)3], evidenced by single-crystal X-ray diffraction, transmission electron microscopy, and Raman spectroscopy. We have attempted to benchmark the evolution of Cs-U1 to uranyl tricarbonate, which involves a transient, unstable hygroscopic solid that contains predominantly pentavalent uranium, quantified by X-ray photoelectron spectroscopy. Powder X-ray diffraction suggests this intermediate state contains a hydrous derivative of CsUVO3, where the parent phase has been computationally predicted, but not yet synthesized.
ABSTRACT
Understanding the mixing behaviour of elements in a multielement material is important to control its structure and property. When the size of a multielement material is decreased to the nanoscale, the miscibility of elements in the nanomaterial often changes from its bulk counterpart. However, there is a lack of comprehensive and quantitative experimental insight into this process. Here we explored how the miscibility of Au and Rh evolves in nanoparticles of sizes varying from 4 to 1 nm and composition changing from 15% Au to 85% Au. We found that the two immiscible elements exhibit a phase-separation-to-alloy transition in nanoparticles with decreased size and become completely miscible in sub-2 nm particles across the entire compositional range. Quantitative electron microscopy analysis and theoretical calculations were used to show that the observed immiscibility-to-miscibility transition is dictated by particle size, composition and possible surface adsorbates present under the synthesis conditions.
ABSTRACT
Extracting structured knowledge from scientific text remains a challenging task for machine learning models. Here, we present a simple approach to joint named entity recognition and relation extraction and demonstrate how pretrained large language models (GPT-3, Llama-2) can be fine-tuned to extract useful records of complex scientific knowledge. We test three representative tasks in materials chemistry: linking dopants and host materials, cataloging metal-organic frameworks, and general composition/phase/morphology/application information extraction. Records are extracted from single sentences or entire paragraphs, and the output can be returned as simple English sentences or a more structured format such as a list of JSON objects. This approach represents a simple, accessible, and highly flexible route to obtaining large databases of structured specialized scientific knowledge extracted from research papers.
ABSTRACT
Activation barriers of elementary reactions are essential to predict molecular reaction mechanisms and kinetics. However, computing these energy barriers by identifying transition states with electronic structure methods (e.g., density functional theory) can be time-consuming and computationally expensive. In this work, we introduce CoeffNet, an equivariant graph neural network that predicts activation barriers using coefficients of any frontier molecular orbital (such as the highest occupied molecular orbital) of reactant and product complexes as graph node features. We show that using coefficients as features offer several advantages, such as chemical interpretability and physical constraints on the network's behaviour and numerical range. Model outputs are either activation barriers or coefficients of the chosen molecular orbital of the transition state; the latter quantity allows us to interpret the results of the neural network through chemical intuition. We test CoeffNet on a dataset of SN2 reactions as a proof-of-concept and show that the activation barriers are predicted with a mean absolute error of less than 0.025 eV. The highest occupied molecular orbital of the transition state is visualized and the distribution of the orbital densities of the transition states is described for a few prototype SN2 reactions.
ABSTRACT
Elastomers are widely used in textiles, foam, and rubber, yet they are rarely recycled due to the difficulty in deconstructing polymer chains to reusable monomers. Introducing reversible bonds in these materials offers prospects for improving their circularity; however, concomitant bond exchange permits creep, which is undesirable. Here, we show how to architect dynamic covalent polydiketoenamine (PDK) elastomers prepared from polyetheramine and triketone monomers, not only for energy-efficient circularity, but also for outstanding creep resistance at high temperature. By appending polytopic cross-linking functionality at the chain ends of flexible polyetheramines, we reduced creep from >200% to less than 1%, relative to monotopic controls, producing mechanically robust and stable elastomers and carbon-reinforced rubbers that are readily depolymerized to pure monomer in high yield. We also found that the multivalent chain end was essential for ensuring complete PDK deconstruction. Mapping reaction coordinates in energy and space across a range of potential conformations reveals the underpinnings of this behavior, which involves preorganization of the transition state for diketoenamine bond acidolysis when a tertiary amine is also nearby.
ABSTRACT
Recent computational studies have predicted many new ternary nitrides, revealing synthetic opportunities in this underexplored phase space. However, synthesizing new ternary nitrides is difficult, in part because intermediate and product phases often have high cohesive energies that inhibit diffusion. Here, we report the synthesis of two new phases, calcium zirconium nitride (CaZrN2) and calcium hafnium nitride (CaHfN2), by solid state metathesis reactions between Ca3N2 and MCl4 (M = Zr, Hf). Although the reaction nominally proceeds to the target phases in a 1:1 ratio of the precursors via Ca3N2 + MCl4 â CaMN2 + 2 CaCl2, reactions prepared this way result in Ca-poor materials (CaxM2-xN2, x < 1). A small excess of Ca3N2 (ca. 20 mol %) is needed to yield stoichiometric CaMN2, as confirmed by high-resolution synchrotron powder X-ray diffraction. In situ synchrotron X-ray diffraction studies reveal that nominally stoichiometric reactions produce Zr3+ intermediates early in the reaction pathway, and the excess Ca3N2 is needed to reoxidize Zr3+ intermediates back to the Zr4+ oxidation state of CaZrN2. Analysis of computationally derived chemical potential diagrams rationalizes this synthetic approach and its contrast from the synthesis of MgZrN2. These findings additionally highlight the utility of in situ diffraction studies and computational thermochemistry to provide mechanistic guidance for synthesis.
ABSTRACT
Electrolyte decomposition limits the lifetime of commercial lithium-ion batteries (LIBs) and slows the adoption of next-generation energy storage technologies. A fundamental understanding of electrolyte degradation is critical to rationally design stable and energy-dense LIBs. To date, most explanations for electrolyte decomposition at LIB positive electrodes have relied on ethylene carbonate (EC) being chemically oxidized by evolved singlet oxygen (1O2) or electrochemically oxidized. In this work, we apply density functional theory to assess the feasibility of these mechanisms. We find that electrochemical oxidation is unfavorable at any potential reached during normal LIB operation, and we predict that previously reported reactions between the EC and 1O2 are kinetically limited at room temperature. Our calculations suggest an alternative mechanism in which EC reacts with superoxide (O2-) and/or peroxide (O22-) anions. This work provides a new perspective on LIB electrolyte decomposition and motivates further studies to understand the reactivity at positive electrodes.
ABSTRACT
The synthesis of complex oxides at low temperatures brings forward aspects of chemistry not typically considered. This study focuses on perovskite LaMnO3, which is of interest for its correlated electronic behavior tied to the oxidation state and thus the spin configuration of manganese. Traditional equilibrium synthesis of these materials typically requires synthesis reaction temperatures in excess of 1000 °C, followed by subsequent annealing steps at lower temperatures and different p(O2) conditions to manipulate the oxygen content postsynthesis (e.g., LaMnO3+x). Double-ion exchange (metathesis) reactions have recently been shown to react at much lower temperatures (500-800 °C), highlighting a fundamental knowledge gap for how solids react at lower temperatures. Here, we revisit the metathesis reaction, LiMnO2 + LaOX, where X is a halide or mixture of halides, using in situ synchrotron X-ray diffraction. These experiments reveal low reaction onset temperatures (ca. 450-480 °C). The lowest reaction temperatures are achieved by a mixture of lanthanum oxyhalide precursors: 2 LiMnO2 + LaOCl + LaOBr. In all cases, the resulting products are the expected alkali halide salt and defective La1-ϵMn1-ϵO3, where ϵ = x/(3 + x). We observe a systematic variation in defect concentration, consistent with a rapid stoichiometric local equilibration of the precursors and the subsequent global thermodynamic equilibration with O2 (g), as revealed by computational thermodynamics. Together, these results reveal how the inclusion of additional elements (e.g., Li and a halide) leads to the local equilibrium, particularly at low reaction temperatures for solid-state chemistry.
ABSTRACT
To close the gap between the rates of computational screening and experimental realization of novel materials1,2, we introduce the A-Lab, an autonomous laboratory for the solid-state synthesis of inorganic powders. This platform uses computations, historical data from the literature, machine learning (ML) and active learning to plan and interpret the outcomes of experiments performed using robotics. Over 17 days of continuous operation, the A-Lab realized 41 novel compounds from a set of 58 targets including a variety of oxides and phosphates that were identified using large-scale ab initio phase-stability data from the Materials Project and Google DeepMind. Synthesis recipes were proposed by natural-language models trained on the literature and optimized using an active-learning approach grounded in thermodynamics. Analysis of the failed syntheses provides direct and actionable suggestions to improve current techniques for materials screening and synthesis design. The high success rate demonstrates the effectiveness of artificial-intelligence-driven platforms for autonomous materials discovery and motivates further integration of computations, historical knowledge and robotics.
ABSTRACT
Oxygen evolution energies were calculated for the {100}, {110}, {111}, and {112} type facets of the rock-salt-structured cation-disordered Li-excess, Mn-rich Li-ion (DRX) cathode Li2MnO2F at the fully lithiated, 25% delithiation, and 50% delithiation states. Our calculations showed that Li2MnO2F remains much more robust to O loss than its nonfluorinated counterparts, as has been shown in experimental work. In particular, the {110} and {112} facets are the most resilient against O loss. Focusing on the {100} type facet, which previous work has shown to be the most likely exposed facet of Li2MnO2F, it was found that higher proportions of Li in an O coordination shell lead to lower O evolution energy (EO) and facilitate O loss. It was also found that at higher states of delithiation, surface fluorine had a weaker effect in increasing EO, meaning the protective effect of F against O loss is more effective at higher lithiation states. Electronic structure chemical bonding analysis revealed weaker bonding interactions between Li and O correlated with lower EO and hence a higher propensity for surface O loss..
ABSTRACT
Synthesis is a major challenge in the discovery of new inorganic materials. Currently, there is limited theoretical guidance for identifying optimal solid-state synthesis procedures. We introduce two selectivity metrics, primary and secondary competition, to assess the favorability of target/impurity phase formation in solid-state reactions. We used these metrics to analyze 3520 solid-state reactions in the literature, ranking existing approaches to popular target materials. Additionally, we implemented these metrics in a data-driven synthesis planning workflow and demonstrated its application in the synthesis of barium titanate (BaTiO3). Using an 18-element chemical reaction network with first-principles thermodynamic data from the Materials Project, we identified 82985 possible BaTiO3 synthesis reactions and selected 9 for experimental testing. Characterization of reaction pathways via synchrotron powder X-ray diffraction reveals that our selectivity metrics correlate with observed target/impurity formation. We discovered two efficient reactions using unconventional precursors (BaS/BaCl2 and Na2TiO3) that produce BaTiO3 faster and with fewer impurities than conventional methods, highlighting the importance of considering complex chemistries with additional elements during precursor selection. Our framework provides a foundation for predictive inorganic synthesis, facilitating the optimization of existing recipes and the discovery of new materials, including those not easily attainable with conventional precursors.