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Ceder, Gerbrand

Publications and source records attributed to Ceder, Gerbrand.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Design Strategies of Spinel Oxide Frameworks Enabling Reversible Mg-Ion Intercalation

In this study, reversible Mg 2+ intercalation in metal oxides frameworks is a key enabler for an operational Mg ion battery with high energy density needed for the next generation of energy storage technologies. While functional Mg-ion batteries have been achieved in structures with soft anions (e.g., S 2- and Se 2- ), they do not meet energy density requirements to compete with the current rechargeable lithium-ion batteries due to their low insertion potentials, emphasizing the necessity of finding an oxide-based cathode that operates at high potentials. A leading hypothesis to explain the limited availability of oxide Mg-ion cathodes is the belief that Mg 2+ has sluggish diffusion kinetics in oxides due to strong electrostatic interactions between the Mg 2+ ions and oxide anions in the lattice. From this assessment, it can be hypothesized that such rate limiting kinetic shortcomings can be mitigated by tailoring an oxide framework through creating less stable Mg 2+ - O 2- coordination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

An autonomous laboratory for the accelerated synthesis of novel materials

To close the gap between the rates of computational screening and experimental realization of novel materials, 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.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Atomic-scale probing of short-range order and its impact on electrochemical properties in cation-disordered oxide cathodes

Abstract Chemical short-range-order has been widely noticed to dictate the electrochemical properties of Li-excess cation-disordered rocksalt oxides, a class of cathode based on earth abundant elements for next-generation high-energy-density batteries. Existence of short-range-order is normally evidenced by a diffused intensity pattern in reciprocal space, however, derivation of local atomic arrangements of short-range-order in real space is hardly possible. Here, by a combination of aberration-corrected scanning transmission electron microscopy, electron diffraction, and cluster-expansion Monte Carlo simulations, we reveal the short-range-order is a convolution of three basic types: tetrahedron, octahedron, and cube. We discover that short-range-order directly correlates with Li percolation channels, which correspondingly affects Li transport behavior. We further demonstrate that short-range-order can be effectively manipulated by anion doping or post-synthesis thermal treatment, creating new avenues for tailoring the electrochemical properties. Our results provide fundamental insights for decoding the complex relationship between local chemical ordering and properties of crystalline compounds.

25 ENERGY STORAGE↗
DOE OSTI2023

Elucidating Structural Transition Dynamics in the Magnesium Cathode MgCr 2 O 4

Multivalent batteries, e.g., those based on magnesium (Mg), are promising candidates for next-generation energy storage due to their high volumetric energy densities and low cost. However, the corresponding ion migration and structural transition mechanisms are often linked and difficult to observe directly. Here, in this paper, we report the direct investigation of atomic transport pathways of cations in spinel magnesium chromate (MgCr 2 O 4 ) by using aberration-corrected scanning transmission electron microscopy (STEM). Cr atoms are directly observed to reversibly occupy the otherwise vacant octahedrally coordinated interstitial sites, passing through tetrahedral sites normally occupied by Mg. Furthermore, imaging and electron energy loss spectroscopy show that electron irradiation induces the formation of Mg and O vacancies, facilitating the migration of Cr and leading to an irreversible phase transition. These results demonstrate the ability of STEM to capture the pathway of deleterious point defects that can result in undesirable phase transitions.

25 ENERGY STORAGE↗
DOE OSTI2023

Modeling Intercalation Chemistry with Multiredox Reactions by Sparse Lattice Models in Disordered Rocksalt Cathodes

Modern battery materials can contain many elements with substantial site disorder, and their configurational state has been shown to be critical for their performance. The intercalation voltage profile is a critical parameter to evaluate the performance of energy storage. The application of commonly used cluster expansion techniques to model the intercalation thermodynamics of such systems ab initio is challenged by the combinatorial increase in configurational degrees of freedom as the number of species grows. Such challenges necessitate the efficient generation of lattice models without overfitting and proper sampling of the configurational space under the requirement of charge balance in ionic systems. In this work, we introduce a combined approach that addresses these challenges by (1) constructing a robust cluster expansion Hamiltonian using the sparse regression technique, including -norm regularization and structural hierarchy; and (2) implementing semigrand-canonical Monte Carlo to sample charge-balanced ionic configurations using the table-exchange method and an ensemble average approach. These techniques are applied to a disordered rocksalt oxyfluoride (LMNOF) that is part of a family of promising earth-abundant cathode materials. The simulated voltage profile is found to be in good agreement with experimental data and particularly provides a clear demonstration of the and oxygen contributions to the redox potential as a function of content.

25 ENERGY STORAGE↗
DOE OSTI2023

CHGNet as a pretrained universal neural network potential for charge-informed atomistic modelling

Large-scale simulations with complex electron interactions remain one of the greatest challenges for atomistic modelling. Although classical force fields often fail to describe the coupling between electronic states and ionic rearrangements, the more accurate ab initio molecular dynamics suffers from computational complexity that prevents long-time and large-scale simulations, which are essential to study technologically relevant phenomena. Here we present the Crystal Hamiltonian Graph Neural Network (CHGNet), a graph neural network-based machine-learning interatomic potential (MLIP) that models the universal potential energy surface. CHGNet is pretrained on the energies, forces, stresses and magnetic moments from the Materials Project Trajectory Dataset, which consists of over 10 years of density functional theory calculations of more than 1.5 million inorganic structures. The explicit inclusion of magnetic moments enables CHGNet to learn and accurately represent the orbital occupancy of electrons, enhancing its capability to describe both atomic and electronic degrees of freedom. We demonstrate several applications of CHGNet in solid-state materials, including charge-informed molecular dynamics in Li x MnO 2 , the finite temperature phase diagram for Li x FePO 4 and Li diffusion in garnet conductors. We highlight the significance of charge information for capturing appropriate chemistry and provide insights into ionic systems with additional electronic degrees of freedom that cannot be observed by previous MLIPs.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Design principles for NASICON super-ionic conductors

Na Super Ionic Conductor (NASICON) materials are an important class of solid-state electrolytes owing to their high ionic conductivity and superior chemical and electrochemical stability. In this paper, we combine first-principles calculations, experimental synthesis and testing, and natural language-driven text-mined historical data on NASICON ionic conductivity to achieve clear insights into how chemical composition influences the Na-ion conductivity. These insights, together with a high-throughput first-principles analysis of the compositional space over which NASICONs are expected to be stable, lead to the successful synthesis and electrochemical investigation of several new NASICONs solid-state conductors. Among these, a high ionic conductivity of 1.2 mS cm ₋1 could be achieved at 25 °C. We find that the ionic conductivity increases with average metal size up to a certain value and that the substitution of PO 4 polyanions by SiO 4 also enhances the ionic conductivity. While optimal ionic conductivity is found near a Na content of 3 per formula unit, the exact optimum depends on other compositional variables. Surprisingly, the Na content enhances the ionic conductivity mostly through its effect on the activation barrier, rather than through the carrier concentration. These deconvoluted design criteria may provide guidelines for the design of optimized NASICON conductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Ab initio study of short-range ordering in vanadium-based disordered rocksalt structures

Disordered rocksalt Li-excess (DRX) compounds are attractive new cathode materials for Li-ion batteries as they contain resource-abundant metals and do not require the use of cobalt or nickel. Understanding the delithiation process and cation short-range ordering (SRO) in DRX compounds is essential to improve these promising cathode materials. Herein, we use first-principles calculations along with the cluster-expansion approach to model the disorder in DRX Li 2-x VO 3 , 0 < x < 1. We discuss the SRO of Li in tetrahedral and octahedral sites, and the order in which Li delithiates and V oxidizes with respect to local environments. We reveal that the number of nearest-neighbor V dictates the order of delithiation from octahedral sites and that V is oxidized in a manner that minimizes the electrostatic interactions among V. In conclusion, our results provide valuable insight for tailoring the performance of V-based DRX cathode materials in general by controlling the SRO features that reduce energy density.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Novel Structural Motif To Promote Mg-Ion Mobility: Investigating ABO 4 Zircons as Magnesium Intercalation Cathodes

There is an increasing need for sustainable energy storage solutions as fossil fuels are replaced by renewable energy sources. Multivalent batteries, specifically Mg batteries, are one energy storage technology that researchers continue to develop with hopes to surpass the performance of Li-ion batteries. However, the limited energy density and transport properties of Mg cathodes remain critical challenges preventing the realization of high-performance multivalent batteries. In this work, ABO 4 zircon materials (A = Y, Eu and B = V, Cr) are computationally and experimentally evaluated as Mg intercalation cathodes. Remarkably good Mg-ion transport properties were predicted and Mg-ion intercalation was experimentally verified in sol-gel synthesized zircon YVO 4 , EuVO 4 , and EuCrO 4 . Among them, EuVO 4 exhibited the best electrochemical performance and demonstrated repeated reversible cycling. While we believe that the one-dimensional diffusion channels and redox-active species tetragonal coordination limit the value of many zircons as high-performance cathodes, their unique structural motif of overlapping polyhedra along the diffusion pathway appears instrumental for promoting good Mg-ion mobility. The motif results in a favorable "6-5-4" change in coordination that avoids unfavorable sites with lower coordination along the diffusion pathway and a structural design metric for future Mg cathode development.

25 ENERGY STORAGE↗
DOE OSTI2023

Modeling Short-Range Order in Disordered Rocksalt Cathodes by Pair Distribution Function Analysis

Pair distribution function (PDF) analysis is a powerful technique for the characterization of short-range order (SRO) in disordered materials. Accurate interpretation of experimental PDF data is critically reliant on the development of structural models that can account for local variations in site occupancies and bond lengths. To this end, we outline an approach to model SRO using first-principles calculations based on the cluster-expansion formalism. These methods are validated on neutron scattering data from two disordered rocksalt oxyfluorides, Li 1.3 Mn 0.4 Ti 0.3 O 1.7 F 0.3 and Li 1.3 Mn 0.4 Nb 0.2 Ti 0.1 O 1.7 F 0.3 . For each composition, we demonstrate that an average structure without any SRO fails to reproduce several key features in the experimental PDF. To pinpoint the origin of the suspected SRO in these materials, configurational and displacive effects were separately investigated using two disparate models. Special quasi-random structures were relaxed using density functional theory to account for local changes in bond lengths while maintaining a near-random ionic configuration. This leads to slightly improved accuracy but still misrepresents asymmetry in the first few peaks of the PDF. Monte Carlo simulations were performed to model configurational SRO on a fixed lattice, which by itself is shown to have a minimal influence on the PDF. Instead, we find that it is the bond length relaxations within environments created by SRO which controls the details of the PDF, thereby highlighting the subtle but important coupling between configurational and displacive SRO in disordered materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Precursor recommendation for inorganic synthesis by machine learning materials similarity from scientific literature

Synthesis prediction is a key accelerator for the rapid design of advanced materials. However, determining synthesis variables such as the choice of precursor materials is challenging for inorganic materials because the sequence of reactions during heating is not well understood. In this work, we use a knowledge base of 29,900 solid-state synthesis recipes, text-mined from the scientific literature, to automatically learn which precursors to recommend for the synthesis of a novel target material. The data-driven approach learns chemical similarity of materials and refers the synthesis of a new target to precedent synthesis procedures of similar materials, mimicking human synthesis design. When proposing five precursor sets for each of 2654 unseen test target materials, the recommendation strategy achieves a success rate of at least 82%. Our approach captures decades of heuristic synthesis data in a mathematical form, making it accessible for use in recommendation engines and autonomous laboratories.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Unraveling Li growth kinetics in solid electrolytes due to electron beam charging

Revealing the local structure of solid electrolytes (SEs) with electron microscopy is critical for the fundamental understanding of the performance of solid-state batteries (SSBs). However, the intrinsic structural information in the SSB can be misleading if the sample’s interactions with the electron beams are not fully understood. In this work, we systematically investigate the effect of electron beams on Al-doped lithium lanthanum zirconium oxide (LLZO) under different imaging conditions. Li metal is observed to grow directly on the clean surface of LLZO. The Li metal growth kinetics and the morphology obtained are found to be heavily influenced by the temperature, accelerating voltage, and electron beam intensity. We prove that the lithium growth is due to the LLZO delithiation activated by a positive charging effect under electron beam emission. Our results deepen the understanding of the electron beam impact on SEs and provide guidance for battery material characterization using electron microscopy.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quantitative Decoupling of Oxygen-Redox and Manganese-Redox Voltage Hysteresis in a Cation-Disordered Rock Salt Cathode

Pronounced voltage hysteresis in Li-excess cathode materials is commonly thought to be associated with oxygen redox. However, these materials often possess overlapping oxygen and transition-metal redox, whose contributions to hysteresis between charge and discharge are challenging to distinguish. In this work, a two-step aqueous redox titration is developed with the aid of mass spectrometry (MS) to quantify oxidized lattice oxygen and Mn 3+/4+ redox in a representative Li-excess cation-disordered rock salt—Li 1.2 Mn 0.4 Ti 0.4 O 2 (LMTO). Two MS-countable gas molecules evolve from two separate titrant-analyte reactions, thereby allowing Mn and O redox capacities to be decoupled. The decoupled O and Mn redox coulombic efficiencies are close to 100% for the LMTO cathode, indicating high charge-compensation reversibility. As incremental Mn and O redox capacities are quantitatively decoupled, each redox voltage hysteresis is further evaluated. Overall, LMTO voltage hysteresis arises not only from an intrinsic charge-discharge voltage mismatch related to O redox, but also from asymmetric Mn-redox overvoltages. The results reveal that O and Mn redox both contribute substantially to voltage hysteresis. In conclusion, this work further shows the potential of designing new analytical workflows to experimentally quantify key properties, even in a disordered material having complex local coordination environments.

25 ENERGY STORAGE↗