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Bridges, Craig A.

Publications and source records attributed to Bridges, Craig A..

Shaping the Future of Self-Driving Autonomous Laboratories Workshop

The "Shaping the Future of Self-Driving Autonomous Laboratories" workshop, held in Denver on November 7-8, 2024, brought together leading experts from materials science and computing to address the growing need to revolutionize scientific research through AI-driven autonomous laboratories. The workshop identified critical challenges, including the integration of heterogeneous data, development of AI systems that understand fundamental physical principles, and comprehensive safety protocols. Key recommendations emerged around developing universal laboratory equipment interfaces, implementing automated metadata collection systems, and creating hybrid AI approaches that combine data-driven learning with scientific principles. The workshop emphasized maintaining human oversight while leveraging automation, transforming scientific education to prepare the next generation of researchers, and establishing a national consortium leveraging DOE facilities as anchors for broader collaboration with academia and industry. Participants stressed the urgency of addressing the growing disconnect between human decision-making timescales and modern instrumentation capabilities, highlighting the need for strategic automation while preserving essential human insight and oversight in the research process.

36 MATERIALS SCIENCE↗

In Situ Cyclized Polyacrylonitrile Coating: Key to Stabilizing Porous High-Entropy Oxide Anodes for High-Performance Lithium-Ion Batteries

High-entropy oxides (HEOs) composed of multiple metal elements have attracted great attention as anode materials for lithium-ion batteries (LIBs) due to the synergistic effects of various metal species. However, the practical applications of HEOs are still plagued by poor conductivity, unstable solid electrolyte interphase (SEI) and poor cycling stability. In this work, nanosized (FeCoNiCrMn) 3 O 4 HEO (NHEO) is prepared successfully by the NaCl-assisted mechanical ball-milling strategy. Novelly, polyacrylonitrile (PAN) is used as the binder and then in situ thermochemically cyclized to construct a cyclized PAN (cPAN) outer layer onto NHEO (NHEO-cPAN). The in situ formed cPAN coating not only improves the electrical conductivity, but also reinforces the structural and interfacial stability, and thereby, the resulted NHEO-cPAN electrode exhibits significantly enhanced rate and cyclic performance. Specifically, NHEO-PAN500 electrode delivers a high reversible capacity of 560 mAh g –1 at 5 A g –1 and a high-capacity retention of 83% over 800 cycles at 3 A g –1 . Furthermore, the structural evolution and electrochemical behavior of NHEO-PAN electrode during discharge/charge is systematically investigated by operando X-ray diffraction, in situ impedance spectroscopy and ex situ high-resolution transmission electron microscopy. Therefore, this work provides new insights into the engineering of electrode and interphase for high-performance HEO electrode materials, potentially enlightening the practical applications of HEO-based LIBs.

25 ENERGY STORAGE↗

Cross-Facility Orchestration of Electrochemistry Experiments and Computations

Instrument-computing ecosystems supporting automated electrochemical workflows typically require the integration of disparate instruments such as syringe pump, fraction collector, and potentiostat, all connected to an electrochemical cell. These specialized instruments with custom software and interfaces are not typically designed for network integration and remote automation. We developed a networked ecosystem of these instruments and computing platforms, which includes software to enable automated workflow orchestration from remote computers. Specifically, we developed Python wrappers of APIs and custom Pyro client-server modules to support remote operation of these instruments over the ecosystem network. Herein, we describe a specific workflow for generating and validating voltammogram (I-V) measurements of an electrolyte solution pumped into the electrochemical cell. We demonstrate the orchestration of this workflow which is composed using a Jupyter notebook and executed on a remote computer.

Al Najjar, Anees↗

Normality of I-V Measurements Using ML

There is an increased interest in instrument-computing ecosystems (ICEs) that support science workflows empowered by AI-automated experiments and computations in diverse areas. In particular, electrochemistry ICEs are promising for accelerating the design and discovery of electrochemical systems for energy storage and conversion, by automating significant parts of workflows that combine synthesis and characterization experiments with computations. They require the integration of flow controllers, solvent containers, pumps, fraction collectors, and potentiostats, all connected to an electrochemical cell, as illustrated in Fig. 1. These are specialized instruments with custom software that is not originally designed for network integration. We developed network and software solutions for electrochemical workflows that adapt system and instrument settings in real-time for multiple rounds of experiments. In particular, we developed Python wrappers for Application Programming Interfaces (APIs) of instrument commands and Pyro client-server modules that enable them to be executed from remote computers. The entire workflow is orchestrated by a Jupyter notebook running on a remote computer.

Al Najjar, Anees↗

In Situ Ion‐Exchange Metathesis Induced Conformal LiF Surface Films on Cathode (NMC811) as a Cathode Electrolyte Interphase

High-capacity cathodes (LiNi 0.8 Mn 0.1 Co 0.1 O 2 , NMC811) are promising for vehicle electrification because of their high gravimetric energy density. However, their electrochemical performance still relies upon the stability of the cathode electrolyte interphase (CEI). A highly reactive cathode interface leads to parasitic side reactions with electrolytes, resulting in accelerated capacity fading. Well-developed LiF and LiF-like inorganic compounds are believed to be good CEI components for stabilizing such reactive electrode interfaces. However, it is challenging to form an optimal surface sub-nanolayer of LiF on the cathode surfaces because of the complexity of the electrochemical reaction during battery cycling. Herein, the formation of a conformal LiF layer on the NMC811 electrode surface via an in situ ion-exchange metathesis process is reported, demonstrating a promising electrochemical performance because of a LiF-stabilized CEI. In situ generated LiF-coated NMC811 electrodes exhibit ≈97% capacity retention up to 100 cycles at a 0.3 C rate with average coulombic efficiency of ≈99.9% and ≈80% capacity retention up to 200 cycles at a 1 C rate with average coulombic efficiency of >99.6%. This finding may pave the way for reengineering the CEI to enhance the electrochemical performances and cycling stability of the high-capacity cathodes.

25 ENERGY STORAGE↗

Cyber Framework for Steering and Measurements Collection Over Instrument-Computing Ecosystems

We propose a framework to develop cyber solutions to support the remote steering of science instruments and measurements collection over instrument-computing ecosystems. It is based on provisioning separate data and control connections at the network level, and developing software modules consisting of Python wrappers for instrument commands and Pyro server-client codes that make them available across the ecosystem network. We demonstrate automated measurement transfers and remote steering operations in a microscopy use case for materials research over an ecosystem of Nion microscopes and computing platforms connected over site networks. The proposed framework is currently under further refinement and being adopted to science workflows with automated remote experiments steering for autonomous chemistry laboratories and smart energy grid simulations.

Al Najjar, Anees↗

Local cation ordering in compositionally complex Ruddlesden–Popper n = 1 oxides

The Ruddlesden–Popper (RP) layered perovskite structure is of great interest due to its inherent tunability, and the emergence and growth of the compositionally complex oxide (CCO) concept endows the RP family with further possibilities. Here, a comprehensive assessment of thermodynamic stabilization, local order/disorder, and lattice distortion was performed in the first two reported examples of lanthanum-deficient La n+1 B n O 3n+1 (n = 1, B = Mg, Co, Ni, Cu, Zn) obtained via various processing conditions. Chemical short-range order (CSRO) at the B-site and the controllable excess interstitial oxygen (δ) in RP-CCOs are uncovered by neutron pair distribution function analysis. Reverse Monte Carlo analysis of the data, Metropolis Monte Carlo simulations, and extended x-ray absorption fine structure analysis implies a modest degree of magnetic element segregation on the local scale. Further, ab initio molecular dynamics simulations results obtained from special quasirandom structure disagree with experimentally observed CSRO but confirm Jahn–Teller distortion of CuO 6 octahedra. These findings highlight potential opportunities to control local order/disorder and excess interstitial oxygen in layered RP-CCOs and demonstrate a high degree of freedom for tailoring application-specific properties. They also suggest a need for expansion of theoretical and data modeling approaches in order to meet the innate challenges of CCO and related high-entropy phases.

36 MATERIALS SCIENCE↗

Structure and Anharmonicity of α- and β -Sb 2 O 3 at Low Temperature

Antimony oxides are important materials for catalysis and flame-retardant applications. The two most common phases, α-Sb 2 O 3 (senarmontite) and β-Sb 2 O 3 (valentinite), have been studied extensively. Specific focus has been placed recently on their lattice dynamics properties and how they relate to the α-β phase transformation and their potential anharmonicity. However, there has not been any direct investigation of anharmonicity in these systems, and a surprising lack of low-temperature structural information has prevented further study. Here, we report the powder neutron diffraction data of both phases of Sb 2 O 3 , as well as structural information. α-Sb 2 O 3 behaved as expected, but β-Sb 2 O 3 revealed a small region of zero thermal expansion along the c axis. Additionally, while the β phase matched well with reported atomic displacement parameters, the α phase displayed a marked deviation. This data will enable further investigations into these systems.

36 MATERIALS SCIENCE↗

Reactive matrix infiltration of powder preforms

A reactive matrix infiltration process is described herein, which includes contacting a surface of a preform comprising reinforcement material particles with a molten infiltrant comprising a matrix material, the matrix material comprising an Al—Ce alloy, whereby the infiltrant at least partially fills spaces between the reinforcement material particles by capillary action and reacts with the reinforcement material particles to form a composite material form, the composite material comprising the matrix material, at least one intermetallic phase, and, optionally, reinforcement material particles. A composite material form also is described, which includes a plurality of reinforcement material particles comprising a metal alloy or a ceramic, a matrix material at least partially filling spaces between the reinforcement material particles; and at least one intermetallic phase surrounding at least some of the reinforcement material particles. The reinforcement material particles and intermetallic phase together may form a gradient core-shell structure.

Rios, Orlando↗

A machine learning approach to predict thermal expansion of complex oxides

Although it is of scientific and practical importance, the state-of-the-art of predicting the thermal expansion of oxides over broad temperature and composition ranges by physics-based atomistic simulations is currently limited to qualitative agreements. We present an emerging machine learning (ML) approach to accurately predict the thermal expansion of cubic oxides with a dataset consisting of experimentally measured lattice parameters while using the metal cation polyhedron and temperature as descriptors. High-fidelity ML models that can accurately predict temperature- and composition-dependent lattice parameters of cubic oxides with isotropic thermal expansions have been successfully trained. The ML-predicted thermal expansions of oxides not included in the training dataset have shown good agreement with available experiments. The limitations of the current approach and challenges to go beyond cubic oxides with isotropic thermal expansion are also briefly discussed.

36 MATERIALS SCIENCE↗

Conformal LiF Stabilized Interfaces via Electrochemical Fluorination on High Voltage Spinel Cathodes (≈4.9 V) for Lithium-Ion Batteries

The high voltage LiNi 0.5 Mn 1.5 O 4 (LNMO) spinel is one of the promising cathodes for the lithium-ion batteries due to its high energy densities, good rate performance. However, its high operating potential (≈4.75 V) causes extensive oxidation of conventional carbonate electrolytes, resulting an unstable and thick cathode electrolyte interphase (CEI) layer with a large irreversible capacity and low coulombic efficiency. In this work, we report the formation of thin LiF stabilized interfaces on LNMO via electrochemical fluorination that significantly improves the cycling stability and enhanced the capacity. An electrochemically induced conformal LiF layer acts as a part of a robust CEI by reducing the leakage of electrons and allowing the conduction of Li ions through it. Because of the robust LiF stabilized CEI, LNMO delivers a discharge capacity of ≈148.5 and ≈117.1 mAh g -1 at 0.1 and 1 C rate, respectively. It exhibits excellent cyclability with 80% capacity retention (CR) after 600 cycles in lithium-half cell and ≈90% CR after 200 cycles in full cell with only 0.03% and 0.05% capacity decay per cycle in conventional carbonate electrolytes without additives. Such an excellent electrochemical performance could lead to the potential development of high energy density batteries with high voltage cathodes for grid-based applications.

25 ENERGY STORAGE↗

Insight into the Fast-Rechargeability of a Novel Mo 1.5 W 1.5 Nb 14 O 44 Anode Material for High-Performance Lithium-Ion Batteries

Wadsley–Roth phased niobates are promising anode materials for lithium-ion batteries, while their inherently low electrical conductivity still limits their rate-capability. Herein, a novel doped Mo 1.5 W 1.5 Nb 14 O 44 (MWNO) material is facilely prepared via an ionothermal-synthesis-assisted doping strategy. The detailed crystal structure of MWNO is characterized by neutron powder diffraction and aberration corrected scanning transmission electron microscope, unveiling the full occupation of Mo 6+ -dopant at the t1 tetrahedral site. In half-cells, MWNO exhibits enhanced fast-rechargeability. In this work, the origin of the improved performance is investigated by ultraviolet–visible diffuse reflectance spectroscopy, density functional theory (DFT) computation, and electrochemical impedance spectroscopy, revealing that bandgap narrowing improves the electrical conductivity of MWNO. Furthermore, operando X-ray diffraction elucidates that MWNO exhibits a typical solid-solution phase conversion-based lithium-ion insertion/extraction mechanism with reversible structural evolution during the electrochemical reaction. The boosted lithium-ion diffusivity of MWNO, due to the Mo 6+ /W 6+ doping effect, is confirmed by a galvanostatic intermittent titration technique and DFT. With the simultaneously enhanced electrical conductivity and lithium-ion diffusivity, MWNO successfully demonstrates its fast-rechargeability and practicality in the LiNi 0.5 Mn 1.5 O 4 -coupled full-cells. Therefore, this work illustrates the potential of ionothermal synthesis in energy storage materials and provides a mechanistic understanding of the doping effect on improving material's electrochemical performance.

25 ENERGY STORAGE↗