Search NASA⌕ Search

Engineering topics

Ceder, Gerbrand

Publications and source records attributed to Ceder, Gerbrand.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Dynamic Barriers to Crystallization of Calcium Barium Carbonates

Metastable carbonates play important roles in geochemistry, biomineralization and serve as model systems for nonclassical theories of nucleation and growth. Balcite (Ca 0.5 Ba 0.5 CO 3 ) is a remarkable carbonate phase that is isostructural with a high-temperature modification of calcite (CaCO 3 ), yet can be synthesized at ambient conditions. Here, we investigate crystallization pathways in the Ba-Ca-CO 3 -H 2 O system, with a focus on the transformation of amorphous calcium barium carbonate (ACBC) to balcite and subsequent decomposition into the equilibrium calcite (CaCO3) and witherite (BaCO 3 ) phases. Density functional theory calculations show that balcite is an unstable solid solution (Ca 1-x BaxCO 3 , R 3¯ m) in the range 0.17 < x < 0.5, but is accessible through the amorphous ACBC precursor for x ≲ 0.5, and predict its decomposition into calcite and witherite. We confirm this pathway experimentally but found demixing to proceed slowly and remain incomplete even after 9 months. Nucleation kinetics of balcite from ACBC was assessed using a microfluidic assay, where increasing barium content led to a surprising increase in the balcite nucleation rate, despite decreasing thermodynamic driving force. We attribute crystallization rates that dramatically accelerate with time to changes in interfacial structure and composition during coarsening of the amorphous precipitate. By carefully quantifying the thermodynamic and kinetic contributions in the multistep crystallization of a metastable carbonate, we produce insights that allow us to better interpret the formation and persistence of metastable minerals in natural and synthetic environments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Fluorination-Enhanced Surface Stability of Cation-Disordered Rocksalt Cathodes for Li-Ion Batteries

Cation-disordered rocksalt (DRX) materials have emerged as a class of novel high-capacity cathodes for Li-ion batteries. However, commercialization of DRX cathodes will require reducing their capacity decay, which has been associated with oxygen loss during cycling. Recent studies have shown that fluorination of DRX cathodes can effectively reduce the oxygen loss and improve the cycling stability; however, the underlying atomic-scale mechanisms remain elusive. Herein, using a combination of electrochemical measurements, scanning transmission electron microscopy, and electron energy loss spectroscopy, we examine the correlation between the electrochemical properties and structural evolution in Mn-redox-based DRX cathodes, Li1.2Ti0.4-xMn0.4+xO2.0-xFx (x = 0 and 0.2). We find that fluorination strongly suppresses structural amorphization and void formation initiated from the particle surface, therefore greatly enhancing the cyclability of the cathode. We further reveal a novel rocksalt-to-spinel-like structural transformation in the DRX bulk, which surprisingly contributes to a gradual capacity increase during cycling. Our results provide important insight for the design of novel DRX cathodes with high capacity and long cycle life.

Li, Linze↗
DOE OSTI2021

Probabilistic Deep Learning Approach to Automate the Interpretation of Multi-phase Diffraction Spectra

Autonomous synthesis and characterization of inorganic materials requires the automatic and accurate analysis of X-ray diffraction spectra. For this task, we designed a probabilistic deep learning algorithm to identify complex multi-phase mixtures. At the core of this algorithm lies an ensemble convolutional neural network trained on simulated diffraction spectra, which are systematically augmented with physics-informed perturbations to account for artifacts that can arise during experimental sample preparation and synthesis. In this work, larger perturbations associated with off-stoichiometry are also captured by supplementing the training set with hypothetical solid solutions. Spectra containing mixtures of materials are analyzed with a newly developed branching algorithm that utilizes the probabilistic nature of the neural network to explore suspected mixtures and identify the set of phases that maximize confidence in the prediction. Our model is benchmarked on simulated and experimentally measured diffraction spectra, showing exceptional performance with accuracies exceeding those given by previously reported methods based on profile matching and deep learning. We envision that the algorithm presented here may be integrated in experimental workflows to facilitate the high-throughput and autonomous discovery of inorganic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Insights into Layered Oxide Cathodes for Rechargeable Batteries

Layered intercalation compounds are the dominant cathode materials for rechargeable Li-ion batteries. In this article we summarize in a pedagogical way our work in understanding how the structure’s topology, electronic structure, and chemistry interact to determine its electrochemical performance. We discuss how alkali–alkali interactions within the Li layer influence the voltage profile, the role of the transition metal electronic structure in dictating O3-structural stability, and the mechanism for alkali diffusion. We then briefly delve into emerging, next-generation Li-ion cathodes that move beyond layered intercalation hosts by discussing disordered rocksalt Li-excess structures, a class of materials which may be essential in circumventing impending resource limitations in our era of clean energy technology.

25 ENERGY STORAGE↗
DOE OSTI2021

Toward autonomous design and synthesis of novel inorganic materials

Autonomous experimentation driven by artificial intelligence (AI) provides an exciting opportunity to revolutionize inorganic materials discovery and development. Herein, we review recent progress in the design of self-driving laboratories, including robotics to automate materials synthesis and characterization, in conjunction with AI to interpret experimental outcomes and propose new experimental procedures. We focus on efforts to automate inorganic synthesis through solution-based routes, solid-state reactions, and thin film deposition. In each case, connections are made to relevant work in organic chemistry, where automation is more common. Characterization techniques are primarily discussed in the context of phase identification, as this task is critical to understand what products have formed during synthesis. The application of deep learning to analyze multivariate characterization data and perform phase identification is examined. To achieve “closed-loop” materials synthesis and design, we further provide a detailed overview of optimization algorithms that use active learning to rationally guide experimental iterations. Lastly, we highlight several key opportunities and challenges for the future development of self-driving inorganic materials synthesis platforms.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Non-topotactic reactions enable high rate capability in Li-rich cathode materials

High-rate cathode materials for Li-ion batteries require fast Li transport kinetics, which typically rely on topotactic Li intercalation/de-intercalation because it minimally disrupts Li transport pathways. In contrast to this conventional view, here we demonstrate that the rate capability in a Li-rich cation-disordered rocksalt cathode can be significantly improved when the topotactic reaction is replaced by a non-topotactic reaction. The fast non-topotactic lithiation reaction is enabled by facile and reversible transition metal octahedral-to-tetrahedral migration, which improves rather than impedes Li transport. Using this concept, we show that high-rate performance can be achieved in Mn- and Ni-based cation-disordered rocksalt materials when some of the transition metal content can reversibly switch between octahedral and tetrahedral sites. Overall, this study provides a new perspective on the design of high-performance cathode materials by demonstrating how the interplay between Li and transition metal migration in materials can be conducive to fast non-topotactic Li intercalation/de-intercalations.

25 ENERGY STORAGE↗
DOE OSTI2021

Observing and Modeling the Sequential Pairwise Reactions that Drive Solid‐State Ceramic Synthesis

Abstract Solid‐state synthesis from powder precursors is the primary processing route to advanced multicomponent ceramic materials. Designing reaction conditions and precursors for ceramic synthesis can be a laborious, trial‐and‐error process, as heterogeneous mixtures of precursors often evolve through a complicated series of reaction intermediates. Here, ab initio thermodynamics is used to model which pair of precursors has the most reactive interface, enabling the understanding and anticipation of which non‐equilibrium intermediates form in the early stages of a solid‐state reaction. In situ X‐ray diffraction and in situ electron microscopy are then used to observe how these initial intermediates influence phase evolution in the synthesis of the classic high‐temperature superconductor YBa 2 Cu 3 O 6+ x (YBCO). The model developed herein rationalizes how the replacement of the traditional BaCO 3 precursor with BaO 2 redirects phase evolution through a low‐temperature eutectic melt, facilitating the formation of YBCO in 30 min instead of 12+ h. Precursor selection plays an important role in tuning the thermodynamics of interfacial reactions and emerges as an important design parameter in planning kinetically favorable synthesis pathways to complex ceramic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Atomic Structure of Surface-Densified Phases in Ni-Rich Layered Compounds

In this work, we report the presence of surface-densified phases (β-Ni 5 O 8 , γ-Ni 3 O 4 , and δ-Ni 7 O 8 ) in LiNiO 2 (LNO)- and LiNi 0.8 Al 0.2 O 2 (LNA)-layered compounds by combined atomic level scanning transmission electron microscopy (STEM) and electron energy loss spectroscopy (EELS). These surface phases form upon electrochemical aging at high state of charge corresponding to a fully delithiated state. A unique feature of these phases is the periodic occupancy by Ni 2+ in the Li layer. This periodic Ni occupancy gives rise to extra diffraction reflections, which are qualitatively similar to those of the LiNi 2 O 4 spinel structure, but these surface phases have a lower Ni valence state and cation content than spinel. Furthermore, these experimental results confirm the presence of thermodynamically stable surface phases and provide new insights into the phenomena of surface phase formation in Ni-rich layered structures.

25 ENERGY STORAGE↗
DOE OSTI2021

Kinetic origins of the metastable zone width in the manganese oxide Pourbaix diagram

Pourbaix diagrams show solid–aqueous phase stability as a function of pH and redox potential and can be a valuable tool to guide the hydrothermal synthesis of transition metal oxides. However, the Pourbaix diagram is based on thermodynamics, and nucleation kinetics are not readily apparent in this framework. Here, we conduct a combined experimental and theoretical study to measure the onset of MnO 2 precipitation from an MnO 4 - (aq) solution at various pH conditions, which we then compare against Pourbaix diagram phase boundaries. Using a combination of in situ X-ray absorption spectroscopy and X-ray wide-angle scattering, we directly observe the transformation kinetics from the tetrahedral MnO 4 - (aq) ion to octahedrally coordinated Mn pre-nuclei, as well as its initiation into crystalline δ'-MnO 2 at various pH. The kinetics of octahedral-Mn precursor availability is observed to govern induction times of crystalline MnO 2 nucleation, which results in a metastable zone width in the Mn–H 2 O Pourbaix diagram. These results suggest that synthesis conditions often need to be prepared far beyond the phase boundaries in a Pourbaix diagram to initiate crystallization within a reasonable timescale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Manufacturing scalability implications of materials choice in inorganic solid-state batteries

The pursuit of scalable and manufacturable all-solid-state batteries continues to intensify, motivated by the rapidly increasing demand for safe, dense electrical energy storage. Here, we describe the numerous, often conflicting implications of materials choices that have been made in the search for effective mitigations to the interfacial instabilities plaguing solid-state batteries. Specifically, we show that the manufacturing scalability of solid-state batteries can be governed by at least three principal consequences of materials selection: (1) the availability, scaling capacity, and price volatility of the chosen materials’ constituents, (2) the manufacturing processes needed to integrate the chosen materials into full cells, and (3) the cell performance that may be practically achieved with the chosen materials and processes. While each of these factors is, in isolation, a pivotal determinant of manufacturing scalability, we show that consideration and optimization of their collective effects and trade-offs is necessary to more completely chart a scalable pathway to manufacturing.

25 ENERGY STORAGE↗
DOE OSTI2020

Promises and Challenges of Next-Generation “Beyond Li-ion” Batteries for Electric Vehicles and Grid Decarbonization

The tremendous improvement in performance and cost of lithium-ion batteries (LIBs) have made them the technology of choice for electrical energy storage. While established battery chemistries and cell architectures for Li-ion batteries achieve good power and energy density, LIBs are unlikely to meet all the performance, cost, and scaling targets required for energy storage, in particular, in large-scale applications such as electrified transportation and grids. The demand to further reduce cost and/or increase energy density, as well as the growing concern related to natural resource needs for Li-ion have accelerated the investigation of so-called "beyond Li-ion" technologies. In this review, we will discuss the recent achievements, challenges, and opportunities of four important "beyond Li-ion" technologies: Na-ion batteries, K-ion batteries, all-solid-state batteries, and multivalent batteries. Here, the fundamental science behind the challenges, and potential solutions toward the goals of a low-cost and/or high-energy-density future, are discussed in detail for each technology. While it is unlikely that any given new technology will fully replace Li-ion in the near future, "beyond Li-ion" technologies should be thought of as opportunities for energy storage to grow into mid/large-scale applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Data-driven materials research enabled by natural language processing and information extraction

Given the emergence of data science and machine learning throughout all aspects of society, but particularly in the scientific domain, there is increased importance placed on obtaining data. Data in materials science are particularly heterogeneous, based on the significant range in materials classes that are explored and the variety of materials properties that are of interest. This leads to data that range many orders of magnitude, and these data may manifest as numerical text or image-based information, which requires quantitative interpretation. The ability to automatically consume and codify the scientific literature across domains - enabled by techniques adapted from the field of natural language processing - therefore has immense potential to unlock and generate the rich datasets necessary for data science and machine learning. This review focuses on the progress and practices of natural language processing and text mining of materials science literature and highlights opportunities for extracting additional information beyond text contained in figures and tables in articles. Here, we discuss and provide examples for several reasons for the pursuit of natural language processing for materials, including data compilation, hypothesis development, and understanding the trends within and across fields. Current and emerging natural language processing methods along with their applications to materials science are detailed. We, then, discuss natural language processing and data challenges within the materials science domain where future directions may prove valuable.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Increasing Capacity in Disordered Rocksalt Cathodes by Mg Doping

Using both computations and experiments, we demonstrate that the performance of Li-excess cation-disordered rocksalt cathodes can be improved by Mg substitution. Furthermore we find that Mg reduces the amount of Li in the compound that is strongly bound to F and thereby increases the capacity. This enables the use of fluorination as a tool to improve stability of the compounds without significant loss of capacity. Mg emerged as the most optimal substitution element from a systematic computational study aimed at identifying inactive doping elements with a strong enough bonding strength to fluorine to displace Li from the F environments. Our results also show that capacity can be traded for cycle life depending on whether Mg is substituted for Li or for the redox metal. This design strategy should be considered in fluorinated cathodes, which will facilitate the design of optimized disordered rocksalt oxyfluoride cathodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

First-principles study of CaB 12 H 12 as a potential solid-state conductor for Ca

Calcium dodecahydro-closo-dodecaborate, CaB 12 H 12 , was calculated to have a percolating Ca migration path with low activation barrier (650 meV). The formation of Ca vacancies required for diffusion was calculated to be thermodynamically feasible by substitution of Ca with Al, Bi, or a number of trivalent rare-earth cations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

First-principles Modeling and Design of Solid-State Interfaces for the Protection and Use of Lithium Metal Anodes

Li-ion batteries are one of the most advanced energy storage technologies in use today. Li-ion batteries are used in a multitude of applications ranging from consumer electronics, medical devices, sensors and grid storage. However, improving the capacity and energy density delivered by current Li-ion technology requires advanced materials research into novel chemical systems. In this project we have focused particularly in the use of solid-state electrolytes with lithium metal electrodes. Research into all solid-state batteries (ASSB) with Li metal electrodes has significantly expanded in recent years, however most studies reported experimental findings, which left substantial room for theoretical and modeling work as a tool to understand and determine design principles allowing reliable and safe use of ASSBs with Li metal. Among the remaining obstacles preventing reliable use of ASSBs with a Li metal electrode, the stability of the interface between the solid electrolyte and Li metal, and the propagation/dendrite formation of Li metal and resulting mechanical degradation of the electrolyte are key phenomenon that are yet to be fully understood. In the current project we have addressed these two coupled phenomena using first principles calculations and mesoscale continuum modeling. We have obtained chemical and electrochemical stability windows for several solid electrolyte materials. Additionally, from mathematical and numerical modeling of Li protrusion and dendrite initiation during plating and stripping we have determined design criteria in terms of chemical, electrochemical, and mechanical properties and operating conditions for which stable deposition can occur. We also considered the effects of mixed electronic-ionic conduction in solid electrolytes, which has more recently been suggested as another important mechanism involved in ASSB failure. Throughout our work we have successfully addressed important questions necessary for the use of ASSB’s. We have determined guiding principles for materials properties and operating conditions necessary to operate ASSB’s. And have proposed novel solid electrolyte materials with predicted chemical stability an ionic conductivity. Although this represents significant progress in our understanding, open questions remain in order to fully develop reliable and safely operate ASSBs with Li metal. Future work, building on this project will require further experimental, theoretical and simulation efforts to address remaining questions.

25 ENERGY STORAGE↗