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At least 829 records · Page 46

Evaluating the Effect of Electrolyte Additive Functionalities on NMC622/Si Cell Performance

Unstable electrode/electrolyte interface is the major cause of degradation for silicon (Si)-based anodes for lithium (Li)-ion batteries. Development of functional electrolyte additives can provide a viable path toward stabilizing the dynamic Si/electrolyte interface, which will benefit the development of high energy density Li-ion batteries. Here, we evaluate polymerizable electrolyte additives with varying functional groups (fluorocarbon, thiophosphate, and fluorophosphazene). The additives are examined using LiNi 0.6 Mn 0.2 Co 0.2 O 2 /Si full cells where the cycle performance and impedance are measured. Electrochemical tests show that the fluorine-containing additives provide better passivation at the Si electrode, leading to enhanced full cell performance. Here, among the three additives examined, best electrochemical performance is observed from the fluorocarbon-containing compound, followed by fluorophosphazene- and thiophosphate-containing compounds. Characterization of the solid electrolyte interphase (SEI) on cycled electrodes using Auger electron spectroscopy (AES), X-ray photoelectron spectroscopy (XPS), and attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) reveal that higher concentration of fluorine and lithium oxide, and lower concentration of carbonate and organic species correlate with enhanced electrochemical performance.

25 ENERGY STORAGE↗

Pt-Assisted Carbon Remediation of Mo2C Materials for CO Disproportionation

Using the CO disproportionation (Boudouard) reaction as a probe reaction, an in-depth analysis of temperature-programmed pulse response data shows that the addition of Pt to Mo2C mitigates deactivation of Mo active sites by acting as a carbon collector. CO2 production on Mo2C and Pt/Mo2C materials is dependent on both the activation energy and the CO surface concentration. Detailed plane-wave density functional theory calculations of the CO adsorption and disproportion reactions on Mo2C-supported Pt nanoparticles (NPs) are reported. The Mo2C was modeled by the ß-Mo2C (100) surface, and the Pt/Mo2C interface was modeled by the addition of 12 Pt atoms to the Mo2C (100) surface (12Pt@Mo2C). The potential energy surfaces of the Boudouard reaction were calculated on pure Mo2C, 12Pt@Mo2C, and Pt (111) surfaces. CO dissociation readily occurs on the Mo2C (100) surface, but not on the Pt (111) surface, with the former being exothermic and the latter being endothermic. At the Pt/Mo2C interface, CO dissociation is still exothermic, but with a larger energy barrier. The Boudouard reaction takes place on the Mo2C region, where CO2 is formed from a surface O atom dissociated from one CO molecule in reaction with another CO molecule, leaving one C atom on the surface. C adsorption is preferential on the Pt site in comparison to the Mo site. The supported Pt domains can collect the remaining C atoms, facilitating further CO2 formation on the active Mo sites. A Bader charge analysis shows that the surface metal-carbon bond is a mixture of covalent and ionic bonds, whereas the surface metal-oxygen bond is ionic. Electron localization function (ELF) and partial charge density calculations agree well with the Bader charge analysis. These computational results are consistent with experimental observations of the interaction of CO with Mo2C nanotube supported Pt domains in the transient regime under far from equilibrium conditions. The Boudouard reaction is an important side reaction, and the unexpected role found for Pt as a carbon collector, with Mo serving as a disproportionation site, provides a unique vantage point for understanding carbon and coke formation on catalytic materials.

Pt-assisted carbon remediation, Pt/Mo2C interface,↗

Libration of hydroxyl groups in layered aluminum (oxy)hydroxides and other material analogs: insights from inelastic neutron scattering and theory

We analyzed the hydroxyl librational signatures of five structurally related aluminum (oxy)hydroxides, using inelastic neutron scattering (INS) and plane-wave lattice dynamics simulations. A clear trend across these aluminum-containing phases illustrates the relationship between hydrogen bonding, local atomic structure, and the spectral location and profile of the librational bands. The INS spectra have been compared to previous optical spectroscopy and computational studies, highlighting the complementary nature of the INS technique. Taking into account other structurally or chemically related material analogs, we have identified a correlation between a blueshift (to higher energy) of the upper librational band edge and the geometry of the hydrogen bond interactions, mirroring (with opposite correlation) the well-known redshift in the intramolecular O–H stretching energy with increasing hydrogen bond strength. For hydroxyl groups that do not participate in hydrogen bonding effectively, the bending librations occur at lower energies and hybridize with metal–oxygen lattice modes. Standard density functional theory approximations, including dispersion corrections, struggle to correctly predict vibrational frequencies of motions dominated by H but perform well for metal–oxygen modes, allowing us to make detailed mode assignments in several cases, including a demonstration of how layer-to-layer disorder in boehmite hydrogen bond orientations is reflected in the sharp but minor low energy peaks (at ∼70–80 meV) of the INS spectrum.

Wang, Hsiu-Wen [Oak Ridge National Laboratory (ORN↗

Nanoprecipitates to Enhance Radiation Tolerance in High-Entropy Alloys

The growth of advanced energy technologies for power generation is enabled by the design, development, and integration of structural materials that can withstand extreme environments, such as high temperatures, radiation damage, and corrosion. High-entropy alloys (HEAs) are a class of structural materials in which suitable chemical elements in four or more numbers are mixed to typically produce single-phase concentrated solid solution alloys (CSAs). Many of these alloys exhibit good radiation tolerance like limited void swelling and hardening up to relatively medium radiation doses (tens of displacements per atom (dpa)); however, at higher radiation damage levels (>50 dpa), some HEAs suffer from considerable void swelling limiting their near-term acceptance for advanced nuclear reactor concepts. In this study, we developed a HEA containing a high density of Cu-rich nanoprecipitates distributed in the HEA matrix. The Cu-added HEA, NiCoFeCrCu 0.12 , shows excellent void swelling resistance and negligible radiation-induced hardening upon irradiation up to high radiation doses (i.e., higher than 100 dpa). The void swelling resistance of the alloy is measured to be significantly better than NiCoFeCr CSA and austenitic stainless steels. Density functional theory simulations predict lower vacancy and interstitial formation energies at the coherent interfaces between Cu-rich nanoprecipitates and the HEA matrix. The alloy maintained a high sink strength achieved via nanoprecipitates and the coherent interface with the matrix at a high radiation dose (~50 dpa). From our experiments and simulations, the effective recombination of radiation-produced vacancies and interstitials at the coherent interfaces of the nanoprecipitates is suggested to be the critical mechanism responsible for the radiation tolerance of the alloy. Furthermore, the materials design strategy based on incorporating a high density of interfaces can be applied to high-entropy alloy systems to improve their radiation tolerance.

36 MATERIALS SCIENCE↗

Substitutional doping of 2D transition metal dichalcogenides for device applications: Current status, challenges and prospects

Two-dimensional (2D) transition metal dichalcogenides (TMDs) have emerged as a class of materials with exceptional electronic, optical, and mechanical properties, making them highly tunable for diverse applications in nanoelectronics, optoelectronics, and catalysis. Here, this review focuses on substitutional doping of TMDs, a key strategy to tailor their properties and enhance device performance, with a focus on its applications over the past five years (2019–2024). We delve into both theoretical and experimental doping approaches, including established methods like chemical vapor transport (CVT) and chemical vapor deposition (CVD) alongside liquid phase exfoliation (LPE) and post-synthesis treatments. Advanced growth techniques are also explored. Challenges like dopant uniformity, concentration control, and stability are addressed. The influence of various dopants on the electronic band structure, carrier concentration, and defect engineering is analyzed in detail. We further explore recent advancements in utilizing doped TMDs for field-effect transistors (FETs), photodetectors, sensors, photovoltaics, optoelectronic devices, energy storage and conversion, and even quantum computers. By examining both the potential and limitations of substitutional doping, this review aims to propel future research and technological advancements in this exciting field.

36 MATERIALS SCIENCE↗

Excited states in warm and hot dense matter

Accurate modeling of warm and hot dense matter is challenging in part due to the multitude of excited states that must be considered. Here, we present a variational framework that models these excited states. In this framework an excited state is defined by a set of effective one-electron occupation factors, and the corresponding energy is defined by the effective one-body energy with an exchange and correlation term. Here, the variational framework is applied to an atom-in-plasma model (a generalization of the so-called average atom model). Comparisons with a density functional theory based average atom model generally reveal good agreement in the calculated pressure, but our model also gives access to the excitation energies and charge state distributions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Accurate machine-learning predictions of coercivity in high-performance permanent magnets

Increased demand for high-performance permanent magnets in the electric vehicle and wind-turbine industries has prompted the search for cost-effective alternatives. Discovering magnetic materials with the desired intrinsic and extrinsic permanent magnet properties presents a significant challenge to researchers because of issues with the global supply of rare-earth elements, material stability, and a low maximum magnetic energy product BH max . While first-principles density functional theory (DFT) predicts materials’ magnetic moments, magnetocrystalline anisotropy constants, and exchange interactions, it cannot compute extrinsic properties such as coercivity (H c ). Although it is possible to calculate H c theoretically with micromagnetic simulations, the predicted value is larger than the experiment by almost an order of magnitude due to the Brown paradox. To circumvent these issues, we employ machine-learning (ML) methods on an extensive database obtained from experiments, DFT calculations, and micromagnetic modeling. The use of a large experimental dataset enables realistic H c predictions for materials such as Ce-doped Nd 2 ⁢Fe 14 ⁢B, comparing favorably against micromagnetically simulated coercivities. Remarkably, our ML model accurately identifies uniaxial magneto-crystalline anisotropy as the primary contributor to H c . With DFT calculations, we predict the Nd-site-dependent magnetic anisotropy behavior in Nd 2 ⁢Fe 14 ⁢B, confirming that Nd 4⁢g sites mainly contribute to uniaxial magnetocrystalline anisotropy, and also calculate the Curie temperature (T c ). Finally, both calculated results are in good agreement with the experiments. The coupled experimental dataset and ML modeling with DFT input predict H c with far greater accuracy and speed than was previously possible using micromagnetic modeling. Further, we reverse engineer the grain-boundary and intergrain exchange coupling with micromagnetic simulations by employing the ML predictions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Spontaneous dynamical disordering of borophenes in MgB2 and related metal borides

Abstract Layered boron compounds have attracted significant interest in applications from energy storage to electronic materials to device applications, owing in part to a diversity of surface properties tied to specific arrangements of boron atoms. Here we report the energy landscape for surface atomic configurations of MgB 2 by combining first-principles calculations, global optimization, material synthesis and characterization. We demonstrate that contrary to previous assumptions, multiple disordered reconstructions are thermodynamically preferred and kinetically accessible within exposed B surfaces in MgB 2 and other layered metal diborides at low boron chemical potentials. Such a dynamic environment and intrinsic disordering of the B surface atoms present new opportunities to realize a diverse set of 2D boron structures. We validated the predicted surface disorder by characterizing exfoliated boron-terminated MgB 2 nanosheets. We further discuss application-relevant implications, with a particular view towards understanding the impact of boron surface heterogeneity on hydrogen storage performance.

36 MATERIALS SCIENCE↗

Defect-induced states, defect-induced phase transition, and excitonic states in bent tungsten disulfide (WS 2 ) nanoribbons: Density functional vs. many body theory

Two-dimensional (2D) transition metal dichalcogenide (TMD) materials have versatile electronic and optical properties. TMD nanoribbons exhibit interesting properties due to reduced dimensionality, quantum confinement, and edge states, which make them suitable for various electronic and optoelectronic applications. In a previous work conducted by our group, we demonstrated that the edge bands evolved with bending can tune the optical properties for various widths of TMD nanoribbons. Defects are commonly present in 2D TMD materials, and can dramatically change the material properties. Here, in this following work, we investigate the interaction between the edge and the defect states in tungsten disulfide (WS 2 ) nanoribbons with lines of W- or S-atom vacancies defects under different bending conditions, using density functional theory (DFT). To gain understanding about the limits of density functional approximations, we compare results on band gaps and energies of defect states with quasiparticle GW. We reveal interesting semiconductor-metal phase transitions, suggesting potential applications in nanoelectronics or molecular electronics. We also calculate the optical absorption of the bent and defective nanoribbons with the many-body GW-BSE (Bethe-Salpeter equation) approach, revealing a tunable optical spectrum and diverse exciton states in the defective WS 2 nanoribbons.

36 MATERIALS SCIENCE↗

Adapting UFF4MOF for Heterometallic Rare-Earth Metal–Organic Frameworks

Heterometallic metal–organic frameworks based on rare-earth metals (RE-MOFs) have potential in a number of applications where energy transfer between nearby metal atoms is required. This observation implies that it is important to understand the level of local mixing that is achieved between metals of different types during synthesis of RE-MOFs. Density functional theory calculations can give quantitative information on the relative energy of different configurations of RE-MOFs, but these calculations cannot be applied to the full range of medium- and long-range orderings that are possible in heterometallic materials. This limitation can be overcome using force field (FF)-based calculations if appropriate FFs are available. In this work, we show that an existing generic FF for MOFs, UFF4MOF, does not accurately predict energies of mixing in heterometallic Nd/Yb MOFs and introduce a modified FF to address this shortcoming. The resulting FF is used to explore metal orderings in large simulation volumes for a Nd/Yb MOF, illustrating the complexities that can arise in the structure of heterometallic RE-MOFs.

36 MATERIALS SCIENCE↗

Theoretical Study of Fe(CO)n-

The structures and CO binding energies are computed for Fe(CO)n- using a hybrid density functional theory (DFT) approach. The structures and ground states can be explained in terms of maximizing the Fe to CO 2pi* donation and minimizing Fe-CO 5 sigma repulsion. The trends in the CO binding energies for Fe(CO)n- and the differences between the trends for Fe(CO)n- and Fe(CO)n are also explained. For Fe(CO)n-, the second, third, and fourth CO bonding energies are in good agreement with experiment, while the first is too small. The first CO binding is also too small using the coupled cluster singles and doubles approach including a perturbation estimate of the connected triple excitations.

Ricca, Alessandra↗

Density Functional Theory Study of Epitaxially Strained Monolayer Transition Metal Chalcogenides for Piezoelectricity Generation

Two-dimensional transition metal chalcogenides (2D TMCs) are known for their wide range of bandgaps, flexibility, and high strength. Recent synthesis and data mining efforts indicate that 56 2D TMCs have low exfoliation energies and are relatively stable in monolayer form. Under epitaxial strain, we predict using density functional theory (DFT) calculations that the majority of these 2D TMCs can accommodate ±10% strain without breaking their crystal symmetry. The elastic and piezoelectric tensors indicate that 22 of 56 candidates are piezoelectric, and we derive their in-plane piezoelectric coefficient d 11 . The epitaxial strain is further predicted to enhance the d 11 by over 100% at 10% tensile epitaxial strain for most of these piezoelectric 2D TMCs. ReSe 2 at pristine state and Au 2 Se 2 at +5% epitaxial strain are predicted to obtain the extreme d 11 coefficients at -120 and 326 pm/V, respectively. Lastly, these findings have implications for the use of high-performance 2D piezoelectric materials in devices.

2D materials↗

Effect of Linker Structure and Functionalization on Secondary Gas Formation in Metal–Organic Frameworks

Rare-earth terephthalic acid (BDC)-based metal–organic frameworks (MOFs) are promising candidate materials for acid gas separation and adsorption from flue gas streams. However, previous simulations have shown that acid gases (H 2 O, NO 2 , and SO 2 ) react with the hydroxyl on the BDC linkers to form protonated acid gases as a potential degradation mechanism. Herein, gas-phase computational approaches were used to identify the formation energies of these secondary protonated acid gases across multiple BDC linker molecules. Formation energies for secondary protonated acid gases were evaluated using both density functional theory (DFT) and correlated wave function methods for varying BDC–gas reaction mechanisms. Upon validation of DFT to reproduce wave function calculation results, rotated conformational linkers and chemically functionalized BDC linkers with -OH, -NH 2 , and -SH were investigated. Furthermore, the calculations show that the rotational conformation affects the molecule stability. Double-functionalized BDC linkers, where two functional groups are substituted onto BDC, showed varied reaction energies depending on whether the functional groups donate or withdraw electrons from the aromatic system. Based on these results, BDC linker design must balance adsorption performance with degradation via linker dehydrogenation for the design of stable MOFs for acid gas separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Revealing Local Structures through Machine-Learning-Fused Multimodal Spectroscopy

Atomistic structures of materials offer valuable insights into their functionality. Determining these structures remains a fundamental challenge in materials science, especially for systems with defects. While both experimental and computational methods exist, each has limitations in resolving nanoscale structures. Core-level spectroscopies, such as X-ray absorption (XAS) or electron energy-loss spectroscopies (EELS), have been used to determine the local bonding environment and structure of materials. Recently, machine learning (ML) methods have been applied to extract structural and bonding information from XAS/EELS data. However, frameworks relying solely on a single data stream, defined as characterization data derived from a single element using one technique, are often insufficient because multiple local environments can yield similar spectral features, making it challenging to differentiate between competing structural hypotheses. Here, in this work, we address this challenge by integrating multimodal ab initio simulations, experimental data acquisition, and ML techniques for structure characterization. Our goal is to determine local structures and properties using EELS and XAS data from multiple elements and edges. To showcase our approach, we use various lithium nickel manganese cobalt (NMC) oxide compounds which are used for lithium ion batteries, including those with oxygen vacancies and antisite defects, as the sample material system. We successfully inferred local element content, ranging from lithium to transition metals, with quantitative agreement with experimental data. Beyond local element inference, we find that ML model based on multimodal spectroscopic data is able to determine whether local defects such as oxygen vacancy and antisites are present, a task which is impossible for single mode spectra or other experimental techniques. Furthermore, our framework is able to provide physical interpretability, bridging spectroscopy with the local atomic and electronic structures.

battery↗

Practical Considerations for Testing Polymer Electrolytes for High-Energy Solid-State Batteries

Polymer electrolytes are an important class of materials in enabling solid-state batteries, which have the potential to exceed 400 Wh/kg energy density. Despite significant advancements in their lithium-ion transport and mechanical properties over the last two decades, the integration and testing of these novel electrolyte materials into functioning cells with the electrode loadings and dimensions required to meet the cell-level energy density goals have been limited. Here, through multiple representative examples, we demonstrate the need of testing in close to practical cell conditions for a faster and more reliable evaluation of polymeric electrolytes. In particular, the need for testing with thin lithium anodes and practical cycling capacities is demonstrated for evaluation of their lithium-metal interfacial stability and dendritic resistance, respectively, and a testing protocol is suggested. The guidelines presented here will also apply to testing of other solid electrolytes for solid-state batteries.

25 ENERGY STORAGE↗

Surface Gibbs free energy analyses of Sr segregation in lanthanum strontium iron oxide

Sr surface segregation in mixed-cation oxides often causes degradation of chemical or electrochemical performance. In this work, the thermodynamic driving force for Sr segregation is investigated to explain the Sr segregation behavior in La0.5Sr0.5FeO3 (LSF). Specifically, Density Functional Theory is used to calculate the surface Gibbs free energy of various surface terminations of cubic (100) LSF as a function of chemical potential and temperature. Here, SrO-terminated surfaces are predicted to be dominant, promoting Sr segregation at high temperatures and low oxygen partial pressure.

08 HYDROGEN↗

Nonstationary Dynamics Data Analysis with Wavelet-SVD Filtering

Nonstationary time-frequency analysis is used for identification and classification of aeroelastic and aeroservoelastic dynamics. Time-frequency multiscale wavelet processing generates discrete energy density distributions. The distributions are processed using the singular value decomposition (SVD). Discrete density functions derived from the SVD generate moments that detect the principal features in the data. The SVD standard basis vectors are applied and then compared with a transformed-SVD, or TSVD, which reduces the number of features into more compact energy density concentrations. Finally, from the feature extraction, wavelet-based modal parameter estimation is applied.

Brenner, Marty↗

Anion Vacancies Coupling with Heterostructures Enable Advanced Aerogel Cathode for Ultrafast Aqueous Zinc‐Ion Storage

As a potential cathode material, manganese-based sulfide has recently attracted increasing interest due to its many advantages in aqueous zinc-ion storage. Unfortunately, some challenges such as sluggish kinetics, unstable structure, and controversial phase transition mechanism during the energy storage process hinder its practical application. Herein, inspired by density functional theory (DFT) calculations, a novel 3D sulfur vacancy-rich and heterostructured MnS/MXene aerogel is designed, and used as a cathode for aqueous Zn-ion batteries/hybrid capacitors (ZIBs/ZICs) for the first time. Thanks to the synergistic modification strategy of sulfur vacancies and heterostructures, the as-constructed MnS/MXene//Zn ZIBs exhibit significantly enhanced electrochemical properties, especially outstanding rate capability and cyclic stability. More encouragingly, the as-assembled MnS/MXene//porous carbon (PC) ZICs exhibit an ultrahigh energy density, a high power density, and a splendid cycling lifespan. Most notably, systematic kinetic analyses, ex situ characterizations, and DFT calculations illustrate that MnS/MXene first irreversibly converts into MnO x @ZnMnO 3 /MXene, and then undergoes a reversible conversion from MnO x @ZnMnO 3 /MXene to MnOOH@ZnMn 2 O 4 /MXene, accompanied by the co-insertion/extraction of H + and Zn 2+ . Further, the synergistic modification strategy of sulfur vacancies and heterostructures and the thorough mechanistic study proposed in this work offer valuable guidance for designing and exploiting high-performance cathodes in aqueous zinc-based energy storage devices.

25 ENERGY STORAGE↗