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At least 451 records · Page 25

Wet chemical synthesis and properties of argyrodite sulfide solid electrolytes for solid state lithium batteries

The commercialization of the lithium-ion battery (LIB) in 1991 was responsible for the explosion in portable electronic technologies that has been seen over the past 30 years. With the advent of electric vehicles and other high-powered technologies, there is tremendous demand for LIBs with higher energy density and high safety. To achieve this, new electrode materials must be explored. The obvious choice of anode material would be pure metal lithium, which has a theoretical specific capacity of 3860 mAh g-1 . Unfortunately, metal lithium anodes have not been widely commercialized due to their tendency to react violently with the flammable liquid electrolytes used in today’s batteries. Battery safety can best be achieved by adopting solid electrolytes in place of liquid electrolytes. Solid electrolytes are nonvolatile and nonflammable, safely allowing for the combination of high-capacity cathode materials with a Li metal anode. Argyrodite sulfide solid electrolytes such as halogen-doped Li6PS5X (X = Cl, Br, I) are noted for their high ionic conductivity. But before sulfides can be commercially adopted, they possess several disadvantages which must be addressed, including time- and energy-consuming synthesis processes, poor electrochemical stability, and intrinsically poor air stability. This dissertation seeks to address each of these challenges through materials design an synthesis strategies. In this work, we pioneer a solvent-based approach for the synthesis of argyrodite solid electrolytes Li7PS6 and Li6PS5Xinstead of a stringent solid-state synthesis. Nontoxic ethanol is employed as the solvent, enabling a rapid synthetic approach to produce argyrodite solid electrolytes with high phase purity and compositional flexibility. Compared with Li7PS6, halogen doping (i.e. X = F, Cl, Br, I) not only increases the ionic conductivity, but also enhances the electrochemical stability at the interface towards Li metal. Specifically, F-doped argyrodites produce a robust SEI layer containing LiF, contributing to enhanced interfacial stability. Finally, to address the air instability challenge, argyrodite-incorporated composite solid electrolytes (CSEs) are designed and prepared to produce stable and flexible membranes that are demonstrated in solid-state Li metal batteries. These advances push argyrodite sulfide solid electrolyte research further and pave the way for the proliferation of next generation lithium metal batteries.

25 ENERGY STORAGE↗

High-throughput oxygen chemical potential engineering of perovskite oxides for chemical looping applications

Chemical looping (CL) represents a versatile, emerging strategy for sustainable chemical and energy conversion. Designing metal oxide oxygen carriers with suitable redox properties remains one of the most critical challenges to CL due to the considerably different thermodynamic property requirements for different applications. Here, taking SrFeO 3–δ as a base-structure, this study seeks to rationally substitute its A- and/or B-site cations to tailor the equilibrium oxygen partial pressure over 20 orders of magnitude. 2401 Sr x A 1–x Fe y B 1–y O 3–δ perovskite-phase structures were investigated using high-throughput density functional theory (DFT) and 227, 273 high-entropy perovskites were screened via machine learning (ML). This significantly expands the materials design space. While most of the compositions predicted are new and nonobvious, 19 previously reported oxygen carriers, with excellent redox properties, were correctly identified by the algorithm. Moreover, we experimentally demonstrated 15 new oxygen carriers with superior redox performance. These results support the effectiveness of the high-throughput approaches for accelerated materials discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine learning for accuracy in density functional approximations

Machine learning techniques have found their way into computational chemistry as indispensable tools to accelerate atomistic simulations and materials design. In addition, machine learning approaches hold the potential to boost the predictive power of computationally efficient electronic structure methods, such as density functional theory, to chemical accuracy and to correct for fundamental errors in density functional approaches. In this paper, recent progress in applying machine learning to improve the accuracy of density functional and related approximations is reviewed. Promises and challenges in devising machine learning models transferable between different chemistries and materials classes are discussed with the help of examples applying promising models to systems far outside their training sets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational discovery of a novel double transition metal nitride MXene and its applications as an anchoring and catalytic material in Li–Se batteries

Double transition metal (DTM) nitride MXenes offer enhanced electrical conductivity and tunable catalytic properties compared to conventional carbide-based MXenes. In this study, we employed first-principles density functional theory (DFT) calculations to discover and computationally validate a novel DTM nitride MXene, Nb 2 TiN 2 , derived from its MAX phase precursor and investigated its potential as an anchoring material (AM) for Li–Se batteries. This newly proposed MXene expands the compositional landscape of DTM nitrides and opens new avenues for functional material design. We performed a comprehensive analysis of the thermodynamic and electronic properties of Nb 2 TiAlN 2 , and the MAX phase precursor to Nb 2 TiN 2 to assess its structural stability and exfoliation potential. Exfoliation energy calculations confirmed the feasibility of synthesizing Nb 2 TiN 2 from Nb 2 TiAlN 2 . We then explored the functionalized form, Nb 2 TiN 2 S 2 , evaluating its capability to serve as an effective anchoring material (AM) in Li–Se batteries by analyzing the reaction mechanisms and kinetics of the selenium reduction reaction (SeRR). Our results indicate that Nb 2 TiN 2 S 2 exhibits a strong binding affinity for lithium polyselenides (Li 2 Se n ), effectively suppressing the shuttle effect. Gibbs free energy calculations for the rate-limiting step of the SeRR reveal favorable kinetics and reduced reaction barriers. Overall, this study provides a detailed evaluation of the structural and electronic properties of a newly proposed DTM nitride MXene and its S-functionalized derivative and the catalyzing effect of Nb 2 TiN 2 S 2 in accelerating the reaction kinetics in Li–Se batteries. These findings underscore the potential importance of the further exploration of MXenes to address current challenges in high-performance Li–Se batteries.

25 ENERGY STORAGE↗

Perovskite-Derivative Valleytronics

Halide perovskites are revolutionizing the renewable energy sector owing to their high photovoltaic efficiency, low manufacturing cost, and flexibility. Their remarkable mobility and long carrier lifetime are also valuable for information technology, but fundamental challenges like poor stability under an electric field prevent realistic applications of halide perovskites in electronics. Here, it is discovered that valleytronics is a promising route to leverage the advantages of halide perovskites and derivatives for information storage and processing. The synthesized all-inorganic lead-free perovskite derivative, Cs 3 Bi 2 I 9 , exhibits strong light-matter interaction and parity-dependent optically addressable valley degree of freedom. In this work, robust optical helicity in all odd-layer-number crystals with inversion symmetry breaking is observed, indicating excitonic coherence extending well beyond 11 layers. The excellent optical and valley properties of Cs 3 Bi 2 I 9 arise from the unique parallel bands, according to first principles calculations. This discovery points to new materials design principles for scalable valleytronic devices and demonstrates the promise of perovskite derivatives beyond energy applications.

2D materials↗

Li 2.9 Fe 0.9 Zr 0.1 Cl 6 as Redox-Active Catholyte for Solid-State Li-Ion Batteries

Solid electrolytes are one of the key challenges that hinder the commercialization of all-solid-state batteries. Most efforts have been made to advance the development of solid electrolytes as separators, while the development of catholytes, particularly redox-active catholytes, has been less extensively studied. The high loading of catholytes in composite cathodes, while facilitating ionic conduction, drastically decreases the energy density of the battery. Here, we report an alternative strategy to improve the energy density by using Li 2.9 Fe 0.9 Zr 0.1 Cl 6 as a redox-active catholyte. With a composite cathode containing uncoated LiCoO2 and Li 2.9 Fe 0.9 Zr 0.1 Cl 6 , the solid-state cell not only shows excellent rate capability and stable long-term cycling, benefiting from the high ionic conductivity of Li 2.9 Fe 0.9 Zr 0.1 Cl 6 , but also shows a high cathode specific capacity of ~153 mAh·g –1 . This study broadens the chemical space of the materials design for lithium-ion conductors with redox-active elements (e.g., Fe, Ti, V, and Cr), offering new opportunities to reduce the cost and improve the energy density for all-solid-state batteries.

36 MATERIALS SCIENCE↗

Directed self-assembly of block copolymers for high-precision patterning in the era of extreme ultraviolet lithography

Extreme ultraviolet (EUV) lithography enables unprecedented resolution in semiconductor patterning but faces critical challenges in developing resist materials that achieve high-precision at economically viable throughput. Directed self-assembly (DSA) of block copolymers (BCPs) offers a promising solution for pattern rectification by leveraging thermodynamically determined domain structures to decouple BCP pattern quality from the imperfect original lithographic pattern. This prospective presents an overview of recent progress on the EUV + DSA strategy, covering advances in BCP material design, processing, metrology, and pattern transfer. We highlight recent advances in high-χ BCPs with perpendicular orientation and domain spacings compatible with EUV dimensions, leveraging A-b-(B-r-C) architectures. We also discuss progress in chemical pre-pattern fabrication using both positive- and negative tone resists, along with processing strategies to minimize defects and roughness based on BCP thermodynamics and assembly kinetics. We further examine metrology platforms for characterizing the thermodynamics of BCP materials and quantifying the size and shape of BCP domains. Lastly, we review pattern transfer strategies for generating functional inorganic masks suitable for semiconductor manufacturing. Together, these advances highlight the potential of DSA to complement EUV lithography, offering a pathway to address critical challenges in achieving high-precision patterning for the semiconductor industry.

Lee, Kyunghyeon [Univ. of Chicago, IL (United Stat↗

Coal Enhanced PEEK Filament Production for Additive Manufacturing in Industrial Services

The project (Award DE-FE0032146), led by Baker Hughes in collaboration with the University of Wyoming, aims to develop composite PEEK (Polyether-ether-ketone) materials enhanced using coal-derived graphene-based additives suitable for additive manufacturing (3D printing). Coal char (CC), graphene oxide (GO), and reduced graphene oxide (rGO), derived from Powder River Basin (PRB) coal, were successfully integrated into commercial PEEK feedstock. The composite PEEK materials demonstrated tensile and flexural strengths and modulus, Shore hardness, and thermal properties similar to unfilled PEEK. Dielectric strength of 0.5% GO/PEEK is twice that of unfilled PEEK. However, tensile elongation and Izod impact toughness of the composite materials are lower than unfilled PEEK. The 10% CC/PEEK material also shows good recyclability albeit with slightly increased glass transition and cold crystallization temperatures. Filaments of the composite PEEK materials were fabricated using a Filabot system. 3D printing of the composite PEEK initially encountered feeding stoppage caused by the non-uniform diameter of the filament, which was resolved by reducing the nominal diameter from 1.75 to 1.65 mm. The printability of the composite PEEK filaments is limited in geometry and build time, driven by differences in base PEEK feedstock from the commercial PEEK filament at printing conditions. Prototype part printed using the composite filaments shows inconsistent bead width and bead interruption resulting in porosity. Preliminary process and economic evaluation using PRB coal char estimates the cost of GO to be $0.5/lb. Considering the small fraction expected in the composite PEEK, the GO cost is several orders of magnitude lower than the commercial PEEK filament. It is recommended that the printability of composite PEEK filaments to be improved by optimizing the composite PEEK material at the printing conditions and reducing the variations in filament extrusion. Also important is to identify the mechanisms of how coal-derived additives affect the composite PEEK performance and printing characteristics to allow customized material design and processing for target performance.

01 COAL, LIGNITE, AND PEAT↗

Layer spacing gradient (NaLi) 1–x CoO 2 for electrochemical Li extraction

Designing materials with high Li to Na selectivity is the key for direct extraction of Li from unconventional sources, such as seawater, without complex separations. However, material discovery is hindered by an insufficient understanding on how a material's composition and structure relate to Li selectivity during electrochemical co-intercalation. Here, we synthesized a core-shell structured (NaLi) 1-x CoO 2 with a core Li phase (Li 0.94 CoO 2 ), a shell Na phase (Na 0.51 CoO 2 ), and a transition intermediate phase via Na ion-exchange of parent Li 1-x CoO 2 . We reveal that the chemical compositions and spatial relation of these phases play critical roles in governing high Li to Na selectivity. The core Li phase restricts large layer spacing expansion and inhibits Na intercalation. The shell Na phase serves to maintain the electrode stability against further Na ion exchange. With the layer spacing gradient design, we achieved a high Li selectivity of 1.5 x 10 5 with a recovery of similar to 7.6:1 Li to Na from 1:20,000 initial ratio.

36 MATERIALS SCIENCE↗

Computational synthesis of a new generation of 2D-based perovskite quantum materials

Perovskite-based optoelectronic devices have emerged as a promising energy source due to their potential for scalable production. This study introduces “perovskene,” a novel class of 2D materials derived from the ABC3-like perovskites, synthesized via a data-driven, high-throughput computational strategy. We harness machine learning and multitarget deep neural networks to systematically investigate the structure–property relations, paving the way for targeted material design and optimization in fields such as renewable energy, electronics, and catalysis. The characterization of over 1500 synthesized structures shows that more than 500 structures are stable, revealing properties such as ultra-low work function and large magnetic moment, underscoring the potential for advanced technological applications.

2D materials↗

Experimental Considerations for Estimating Degradation in PV Modules

Carefully controlled laboratory experiments and measurements can enable the determination of acceleration factors suitable for extrapolation to durability and performance of a fielded PV module. Ideally, a single mechanism can be identified with appropriate acceleration factors for extrapolation to the field. However, even with a single mechanism, the inherent uncertainty in these factors leads to uncertainty in the extrapolation which is greater the higher the acceleration factor. This course will explain how because of the wide range of acceleration factors for a given degradation mode, utilizing acceleration factors greater than about 10x will typically lead to unacceptable uncertainty in the results. Therefore, if even just a rank ordering of materials is desired, acceleration factors must be minimized which requires a good general understanding of the scale of the different acceleration factors for the degradation mode of interest. In this tutorial we will discuss what the different purposes are for many of the accelerated stress tests used today. E.g., what is a qualification test, a highly accelerated stress test, a rank ordering test, or a service life prediction test. We will discuss how one can understand the relationship between test results and expected field performance. A single accelerated stress test condition cannot duplicate outdoor exposure for all possible degradation pathways; therefore, one must use targeted evaluation of material properties at different stress levels to determine the relevant acceleration factors and fit it to a model. We will also discuss how to interpret the results of experiments understanding what is relevant/not relevant, or not e valuated in a test. There are many common error people make in their test interpretations because they push the stress levels to be too harsh. This creates biases and can mask the relevant failure modes and mechanisms or will erroneously lead one to over design materials against things that aren't relevant. Several case studies will be presented to illustrate appropriate interpretation of accelerated stress testing results.

degradation↗

High–Performance NiCo 2 O 4 /Graphene Quantum Dots for Asymmetric and Symmetric Supercapacitors with Enhanced Energy Efficiency

For the sustainable growth of future generations, energy storage technologies like supercapacitors and batteries are becoming more and more common. However, reliable and high-performance materials’ design and development is the key for the widespread adoption of batteries and supercapacitors. Quantum dots with fascinating and unusual properties are expected to revolutionize future technologies. However, while the recent discovery of quantum dots honored with a Nobel prize in Chemistry, their benefits for the tenacious problem of energy are not realized yet. In this context, herein, chemical-composition tuning enabled exceptional performance of NiCo 2 O 4 (NCO)/graphene quantum dots (GQDs) is reported, which outperform the existing similar materials, in supercapacitors. A comprehensive study is performed on the synthesis, characterization, and electrochemical performance evaluation of highly functional NCO/GQDs in supercapacitors delivering enhanced energy efficiency. The high-performance, functional NCO/GQDs electrode materials are synthesized by the incorporation of GQDs into NCO. The effect of variable amount of GQDs on the energy performance characteristics of NCO/GQDs in supercapacitors is studied systematically. In-depth structural and chemical bonding analyses using X-ray diffraction (XRD) and Raman spectroscopic studies indicate that all the NCO/GQDs composites crystallize in the spinel cubic phase of NiCo 2 O 4 while graphene integration evident in all the NCO/GQDs. The scanning electron microscopy imaging analysis reveals homogeneously distributed spherical particles with a size distribution of 5–9 nm validating the formation of QDs. The high-resolution transmission electron microscopy analyses reveal that the NCOQDs are anchored on graphene sheets, which provide a high surface area of 42.27 m 2 g –1 and high mesoporosity for the composition of NCO/GQDs-10%. In addition to establishing reliable electrical connection to graphene sheets, the NCOQDs provide reliable 3D-conductive channels for rapid transport throughout the electrode as well as synergistic effects. Chemical-composition tuning, and optimization yields NCO/GQDs-10% to deliver the best specific capacitance of 3940 Fg –1 at 0.5 Ag –1 , where the electrodes retain ≈98% capacitance after 5000 cycles. The NCO/GQD-10%//AC asymmetric supercapacitor device demonstrates outstanding energy density and power density values of 118.04 Wh kg –1 and 798.76 W kg –1 , respectively. The NCO/GQDs-10%//NCO/GQDs-10% symmetric supercapacitor device delivers excellent energy and power density of 24.30 Wh kg –1 and 500 W kg –1 , respectively. These results demonstrate and conclude that NCO/GQDs are exceptional and prospective candidates for developing next-generation high-performance and sustainable energy storage devices.

25 ENERGY STORAGE↗

Design of Multicomponent Peptide Fibrils with Ordered and Programmable Compositional Patterns

Advanced applications of biomacromolecular assemblies require a stringent degree of control over molecular arrangement, which is a challenge to current synthetic methods. Here we used a neighbor-controlled patterning strategy to build multicomponent peptide fibrils with an unprecedented capacity to manipulate local composition and peptide positions. Eight peptides were designed to have regulable nearest neighbors upon co-assembly, which, by simulation, afforded 412 different patterns within fibrils, with varied compositions and/or peptide positions. The fibrils with six prescribed patterns were experimentally constructed with high accuracy. The controlled patterning also applies to functionalities appended to the peptides, as exemplified by arranging carbohydrate ligands at nanoscale precision for protein recognition. Importantly, this study offers a route to molecular editing of inner structures of peptide assemblies, prefiguring the uniqueness and richness of patterning-based material design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Doping Metallic Grain Boundaries to Control Atomic Structure and Damage Tolerance (Final Report)

The interfaces between crystals, known as grain boundaries, often act as sites for crack and void nucleation during plastic deformation of metallic materials. While it is known that interfacial character and structural state can greatly influence this damage nucleation process, the current level of control over such details is extremely limited. The objective of this project was to obtain a fundamental understanding of how metallic grain boundary structure can be controlled through intelligent doping, with the idea of inducing planned grain boundary phases or complexions. The effect of complexion structure on dislocation accommodation mechanisms was studied, to improve the field’s understanding of damage nucleation at interfaces. While mechanical damage was the primary focus, the project showed that amorphous complexions can also improve a material’s resistance to radiation damage, providing a single materials design concept that can address multiple important technological areas. This research used a combination of computational, experimental, and characterization techniques to isolate and understand the importance of nanoscale grain boundary structure and interfacial chemistry. The fundamental insights provided by this project enable the creation of advanced engineering metals with improved damage tolerance.

36 MATERIALS SCIENCE↗

Durable Module Materials Consortium (DuraMAT) FY 2021 Annual Report: New Results and a Renewed Consortium

The Durable Module Materials Consortium (DuraMAT) is a multi-lab consortium led by the National Renewable Energy Laboratory, with Sandia National Laboratories, SLAC National Accelerator Laboratory, and Lawrence Berkeley National Laboratory as core research labs. DuraMAT's overarching goal is to discover, develop, de-risk, and enable the rapid commercialization of improved materials, designs, predictive tests, and models for photovoltaic (PV) modules that increase performance, extend lifetime, and enable new applications. Technical results are highlighted throughout this report, and the new projects awarded for FY 2022 address many of the challenges to making 50-year, high-energy-yield modules that were identified in these working groups.

backsheet↗

Exploiting ultra-large linear elasticity over a wide temperature range in nanocrystalline NiTi alloy

Many shape memory alloys can support large recoverable strains of a few percent by reversible stress-induced martensite transformation, yet they behave non-linear within a narrow operating temperature range. Developing the bulk metallic materials with ultra-large linear elasticity over a wide temperature range has proven to be difficult. In this work, a material design concept was proposed, that is true elastic deformation and reversible twinning-detwinning deformation run in parallel to overcome this challenge. By engineering the residual internal stress to realize the concurrency of true elastic deformation and twinning-detwinning deformation, a bulk nanocrystalline NiTi that possesses an ultra-large linear elastic strain up to 5.1 % and a high yield stress of 2.16 GPa over a wide temperature range of 270 °C was developed. This study offers a new avenue for developing the metallic materials with ultra-large linear elasticity over a wide temperature range of 270 °C (from 70 °C to -197 °C).

36 MATERIALS SCIENCE↗

Chapter 4: Physically informed deep learning networks for simulating microstructure evolution of 3D polycrystals

As discussed in the previous chapter, high energy diffraction microscopy (HEDM) is used to study the micromechanical evolution of a material during in situ loading. HEDM experiments have been used to verify crystal plasticity (CP) simulations [119, 91, 90, 120], for experimental planning, material design, and to further analyze experimental results. However, Fast Fourier transform-based CP (CP-FFT) or finite element-based CP (CP-FE) methods are often too slow to be used in real-time during an experiment. CP-FFT is faster than CP-FE simulations due to the absence of meshing, but can still take hours to simulate the response of a single volume depending on the size and number of strain steps [127]. Reducing computation time would create a larger exploration space in planning and design, and enable faster analysis of experimental results and real-time feedback during an experiment. This research expands upon previous works to develop a workflow for predicting the full-field evolution of a 3D polycrystal. The workflow is simplified from previous works to predict only orientation and elastic strain tensors (from which stress tensors are calculated). The network is physically informed through loss functions and network architecture for a more robust model. The orientation predictions are informed about the cubic crystal symmetry of the material by incorporating disorientation and misorientation information into the network architecture and loss. The Von Mises stress is used to enforce the correct stress-strain trends in the strain tensor predictions. Additional total strain steps from the elastic and elastoplastic region are included to better capture the stress-strain evolution at smaller total strain steps. Material and hardening parameters are additional inputs into the networks to further inform the network and to study the network’s ability to predict different materials other than those used for training.

36 MATERIALS SCIENCE↗

Colossal Cryogenic Electro‐Optic Response Through Metastability in Strained BaTiO 3 Thin Films

The search for thin film electro-optic materials that can retain superior performance under cryogenic conditions has become critical for quantum computing. Barium titanate thin films show large linear electro-optic coefficients in the tetragonal phase at room temperature, which is severely degraded down to ≈200 pm V −1 in the rhombohedral phase at cryogenic temperatures. There is immense interest in manipulating these phase transformations and retaining superior electro-optic properties down to liquid helium temperature. Utilizing the thermodynamic theory of optical properties, a large low-temperature electro-optic response is designed by engineering the energetic competition between different ferroelectric phases, leading to a low-symmetry monoclinic phase with a massive electro-optic response. The existence of this phase is demonstrated in a strain-tuned BaTiO 3 thin film that exhibits a linear electro-optic coefficient of 2516 ± 100 pm V −1 at 5 K, which is an order of magnitude higher than the best reported performance thus far. Importantly, the electro-optic coefficient increases by 100 × during cooling, unlike the conventional films, where it degrades. Further, at the lowest temperature, significant higher order electro-optic responses also emerge. These results represent a new framework for designing materials with property enhancements by stabilizing highly tunable metastable phases with strain.

barium titanate↗