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At least 217 records · Page 12

Structure-property relationships and mobility optimization in sputtered La-doped BaSn O 3 films: Toward 100cm 2 V -1 s -1

he wide band gap semiconducting perovskite BaSnO 3 is of high current interest due to outstanding room temperature mobility at high electron density, fueled by potential applications in oxide, transparent, and power electronics. Due in part to a lack of lattice-matched substrates, BaSnO 3 thin films suffer from high defect densities, however, limiting electron mobility. Additionally, the vast majority of BaSnO 3 thin film research has focused on pulsed laser deposition or molecular beam epitaxy. In this work, we present an exhaustive optimization of the mobility of Ba 0.98 La 0.02 SnO 3 films grown by a scalable, high-throughput method: high-pressure-oxygen sputter deposition. Considering target synthesis conditions, substrate selection, buffer layer structure, deposition temperature, deposition rate, thickness, and postdeposition annealing conditions, and by combining high-resolution x-ray diffraction, reciprocal space mapping, rocking curve analysis, scanning transmission electron microscopy, atomic force microscopy, and temperature-dependent electronic transport measurements, detailed understanding of synthesis-structure-property relationships is attained. Optimized room temperature mobility of 96 cm 2 V –1 s –1 is achieved in vacuum-annealed GdScO 3 (110)/BaSnO 3 (120 nm)/Ba 0.98 La 0.02 SnO 3 (200 nm) heterostructures, as well as 92 cm 2 V –1 s –1 on unbuffered substrates and 87 2 V –1 s –1 without postdeposition annealing. These results, including important trends in defect densities and a surprising dependence of mobility on lattice mismatch, substantially expand the understanding of the interplay between deposition conditions, microstructure, and transport in doped BaSnO 3 films, establishing competitive mobilities in films fabricated via a scalable, high-throughput, industry-standard technique.

36 MATERIALS SCIENCE↗

Strain-Induced asymmetry and on-site dynamics of silicon defects in graphene

In the last decade, the atomically-focused electron beams utilized in scanning transmission electron microscopes (STEMs) have been shown to induce a broad set of local structural transformations in materials, opening pathways for directing material synthesis and modification atom-by-atom. The mechanisms underlying these transformations remain largely unknown, due to the intractability of modeling the myriad of reaction pathways that can be accessed through high-energy electron scattering. The information on materials’ structure and dynamics that can be extracted from STEM images is similarly left underexplored. Here, we report the observation of anomalous on-site dynamics of individual silicon impurity atoms in graphene during STEM imaging. Density functional theory-based structural optimizations of anisotropically-strained molecular nanographenes reveal two distinct (but nearly degenerate) stable structures for four-fold coordinated silicon impurities, where interconversion between the two structures manifests slight changes of the silicon position within the lattice site. Implications for defect-based strain engineering in graphene are discussed.

36 MATERIALS SCIENCE↗

The universal suppressor mutation restores membrane budding defects in the HSV-1 nuclear egress complex by stabilizing the oligomeric lattice

Nuclear egress is an essential process in herpesvirus replication whereby nascent capsids translocate from the nucleus to the cytoplasm. This initial step of nuclear egress–budding at the inner nuclear membrane–is coordinated by the nuclear egress complex (NEC). Composed of the viral proteins UL31 and UL34, NEC deforms the membrane around the capsid as the latter buds into the perinuclear space. NEC oligomerization into a hexagonal membrane-bound lattice is essential for budding because NEC mutants designed to perturb lattice interfaces reduce its budding ability. Previously, we identified an NEC suppressor mutation capable of restoring budding to a mutant with a weakened hexagonal lattice. Using an established in-vitro budding assay and HSV-1 infected cell experiments, we show that the suppressor mutation can restore budding to a broad range of budding-deficient NEC mutants thereby acting as a universal suppressor. Cryogenic electron tomography of the suppressor NEC mutant lattice revealed a hexagonal lattice reminiscent of wild-type NEC lattice instead of an alternative lattice. Further investigation using x-ray crystallography showed that the suppressor mutation promoted the formation of new contacts between the NEC hexamers that, ostensibly, stabilized the hexagonal lattice. This stabilization strategy is powerful enough to override the otherwise deleterious effects of mutations that destabilize the NEC lattice by different mechanisms, resulting in a functional NEC hexagonal lattice and restoration of membrane budding.

60 APPLIED LIFE SCIENCES↗

Monocrystalline CdSeTe/MgCdTe Double‐Heterostructure Solar Cells

This article reports monocrystalline CdSeTe/MgCdTe double‐heterostructure (DH) solar cells with varying Se compositions in the absorber layers that are grown on InSb substrates by using molecular beam epitaxy. The Se composition in the samples studied is determined to be 4%–11% through high‐resolution X‐ray diffraction (XRD) and photoluminescence measurements. Increased Se incorporation induces higher defect density attributed to increased lattice mismatch, and mixed‐phase formation due to the small difference in formation energies between the wurtzite and zinc blende phases of CdSe, which causes stacking faults and grain boundaries. Devices are fabricated by directly depositing an n‐type indium tin oxide (ITO) layer on the CdSeTe/MgCdTe DHs followed by Ag metal contacts. Reduced bandgap is observed in solar cells with increased Se composition. The devices with an absorber containing 4% Se exhibit an average open‐circuit voltage ( V OC ) of 0.925 V, a short‐circuit current density ( J SC ) of 23.4 mA/cm 2 , a fill factor ( FF ) of 0.650 and an efficiency of 14.1% without anti‐reflection coating. Absorbers with higher Se compositions result in poor device performance, mainly attributed to high defect density in the materials.

Ju, Zheng [Center for Photonics Innovation Arizona↗

First-principles determination of the phonon-point defect scattering and thermal transport due to fission products in ThO 2

This work presents the first-principles calculations of the lattice thermal conductivity degradation due to point defects in thorium dioxide using an iterative solution of the Pierels-Boltzmann transport equation. We have used the non perturbative Green’s function methodology to compute the phonon- point defect scattering rates that consider the local distortion around the point defect, including the mass difference changes, interatomic force constants, and structural relaxation near the point defects. The point defects considered in this work include the vacancy of thorium ($V$ $TH$ ) and oxygen ($V$ $O$ ), substitutions of helium ($He$ $Th$ ), krypton ($Kr$ $Th$ ), zirconium ($Zr$ $Th$ ), iodine ($I$ $Th$ ) and xenon ($Xe$ $Th$ ) in the thorium site, and the three different configurations of the Schottky defects. The results of the phonon-defect scattering rate reveal that, among all the considered intrinsic defects, the thorium vacancy and helium substitution in the thorium site scatter the phonon most due to the substantial changes in the force constant and structural distortions. The scattering of phonons due to the substitutional defects unveils that the zirconium atom scatters phonons the least, followed by xenon, iodine, krypton, and helium. This is contrary to the intuition that the scattering strength follows $He$ $Th$ > $Kr$ $Th$ > $Zr$ $Th$ > $I$ $Th$ > $Xe$ $Th$ based on the mass difference. This striking difference in the zirconium phonon scattering is due to the local chemical environment changes. Zirconium is an electropositive element with valency similar to thorium and, therefore, can bond with the oxygen atoms, thus creating less force constant variance compared to iodine, an electronegative element noble gas helium, xenon, and krypton. In conclusion, these results can serve as the benchmark for the analytical models and help the engineering-scale modeling effort for nuclear design.

36 MATERIALS SCIENCE↗

Microdynamics of active particles in defect-rich colloidal crystals

Hypothesis. Because they are self-propulsive, active colloidal particles can interact with their environment in ways that differ from passive, Brownian particles. Here, we explore how interactions in different microstructural regions may contribute to colloidal crystal annealing. Experiments. We investigate active particles propagating in a quasi-2D colloidal crystal monolayer produced by alternating current electric fields (active-to-passive particle ratio ~ 1:720). The active particle is a platinum Janus sphere propelled by asymmetric decomposition of hydrogen peroxide. Crystals are characterized for changes in void properties. The mean-squared-displacement of Janus particles are measured to determine how active microdynamics depend on the local microstructure, which is comprised of void regions, void-adjacent regions (defined as within three particle diameters of a void), and interstitial regions. Findings. At active particle energy E A = 2.55 k B T, the average void size increases as much as three times and the average void anisotropy increases about 40% relative to the passive case. Further, the average microdynamical enhancement, <δ(t)>, of Janus particles in the crystal relative to an equivalent passive Janus particle is reduced compared to that of a free, active particle (<δ(t) > is 1.88 ± 0.04 and 2.66 ± 0.08, respectively). The concentration of active particles is enriched in void and void-adjacent regions. Active particles exhibit the greatest change in dynamics relative to the passive control in void-adjacent regions (<δ(t)> = 2.58 ± 0.06). The results support the conjecture that active particle microdynamical enhancement in crystal lattices is affected by local defect structure.

36 MATERIALS SCIENCE↗

Transforming an Ionic Conductor into an Electronic Conductor via Crystallization: In Situ Evolution of Transference Numbers and Structure in (La,Sr)(Ga,Fe)O 3–x Perovskite Thin Films

Mixed-conducting perovskites are workhorse electrochemically active materials, but typical high-temperature processing compromises their catalytic activity and chemo-mechanical integrity. Low-temperature pulsed laser deposition of amorphous films plus mild thermal annealing is an emerging route to form homogeneous mixed conductors with exceptional catalytic activity, but little is known about the evolution of the oxide-ion transport and transference numbers during crystallization. Here the coupled evolution of ionic and electronic transport behavior and structure in room-temperature-grown amorphous (La,Sr)(Ga,Fe)O 3-x films as they crystallize is explored. In situ ac-impedance spectroscopy with and without blocking electrodes, simultaneous capturing-synchrotron-grazing-incidence X-ray diffraction, dc polarization, transmission electron microscopy, and molecular dynamics simulations to evaluate isothermal and non-isothermal crystallization effects and the role of grain boundaries on transference numbers is combined. Ionic conductivity increases by ≈2 orders of magnitude during crystallization, with even larger increases in electronic conductivity. Consequently, as crystallinity increases, LSGF transitions from a predominantly ionic conductor to a predominantly electronic conductor. The roles of evolving lattice structural order, microstructure, and defect chemistry are examined. Grain boundaries appear relatively nonblocking electronically but significantly blocking ionically. The results demonstrate that ionic transference numbers can be tailored over a wide range by tuning crystallinity and microstructure without having to change the cation composition.

36 MATERIALS SCIENCE↗

3D Printing of Highly Porous Polypropylene Separators for Lithium‐Ion Batteries Using Fused Deposition Modeling and Thermally Induced Phase Separation

Appearing as one of the key-components of lithium-ion batteries (LIBs), this work specifically focuses on the additive manufacturing (AM) of custom-shape separators, facilitated by the filament material extrusion process, also called fused deposition modeling (FDM). The development and optimization of composite thermoplastic filament feedstocks combining polypropylene and paraffin wax, followed by the 3D printing of the separator membranes is shown. A post-processing step, based on thermal induced phase separation (TIPS), is introduced to promote porosity formation through removal of the paraffin wax sacrificial phase within the 3D printed items. Separators with different polypropylene/paraffin wax ratios are developed and the impact on printability, mechanical strength, porosity, and electrochemical performances, is thoroughly discussed. X-ray micro-computed tomography is employed to assess the geometric fidelity and to detect printing defects in a complex 3D lattice structure. The performance of the 3D printed porous separators is also compared to a commercial separator. This pioneering research establishes a foundation for the creation of porous separators that can adapt to and conform into 3D printed battery architectures with novel form factors, and also creates opportunities for the use of FDM and TIPS for a wide range of applications that employ porous structures beyond the energy storage field.

3D printing↗

Thermal Energy Transport in Oxide Nuclear Fuel

To efficiently capture the energy of the nuclear bond, advanced nuclear reactor concepts seek solid fuels that must withstand unprecedented temperature and radiation extremes. In these advanced fuels, thermal energy transport under irradiation is directly related to reactor performance as well as reactor safety. The science of thermal transport in nuclear fuel is a grand challenge as a result of both computational and experimental complexities. Here we provide a comprehensive review of thermal transport research on two actinide oxides: one currently in use in commercial nuclear reactors, uranium dioxide (UO 2 ), and one advanced fuel candidate material, thorium dioxide (ThO 2 ). In both materials, heat is carried by lattice waves or phonons. Crystalline defects caused by fission events effectively scatter phonons and lead to a degradation in fuel performance over time. Bolstered by new computational and experimental tools, researchers are now developing the foundational work necessary to accurately model and ultimately control thermal transport in advanced nuclear fuels. We begin by reviewing research aimed at understanding thermal transport in perfect single crystals. The absence of defects enables studies that focus on the fundamental aspects of phonon transport. Next, we review research that targets defect generation and evolution. Here the focus is on ion irradiation studies used as surrogates for damage caused by fission products. We end this review with a discussion of modeling and experimental efforts directed at predicting and validating mesoscale thermal transport in the presence of irradiation defects. While efforts in these research areas have been robust, challenging work remains in developing holistic tools to capture and predict thermal energy transport across widely varying environmental conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Atomic-Scale Tracking of Topological Defect Motion and Incommensurate Charge Order Melting

Charge order pervades the phase diagrams of quantum materials where it competes with superconducting and magnetic phases, hosts electronic phase transitions and topological defects, and couples to the lattice generating intricate structural distortions. Incommensurate charge order is readily stabilized in manganese oxides, where it is associated with anomalous electronic and magnetic properties, but its nanoscale structural inhomogeneity complicates precise characterization and understanding of its relationship with competing phases. Leveraging atomic-resolution variable-temperature cryogenic scanning transmission electron microscopy, we characterize the thermal evolution of charge order as it transforms from its ground state in a model manganite system. We find that mobile networks of discommensurations and dislocations generate phase inhomogeneity and induce global incommensurability in an otherwise lattice-locked modulation. Driving the order to melt at high temperatures, the discommensuration density grows, and regions of order locally decouple from the lattice periodicity. Published by the American Physical Society 2025

Schnitzer, Noah (ORCID:0000000210421146)↗

Properties of Electronic Materials

This final technical report summarizes the research conducted under DOE Grant DE-SC0002623, "Properties of Electronic Materials," led by Principal Investigator Shengbai Zhang at Rensselaer Polytechnic Institute. Over the 16-year period, the project employed first-principles computational methods to investigate the structural, electronic, and dynamic properties of a wide range of electronic materials, with applications in energy technologies, optoelectronics, and data storage. Key areas included topological insulators, phase-change materials, graphene and two-dimensional systems, perovskites for photovoltaics, defect engineering in semiconductors, kagome lattices, and ultrafast carrier dynamics. The research resulted in 115 peer-reviewed publications, advancing fundamental understanding of material behaviors at the atomic scale and contributing to innovations in renewable energy, memory devices, and quantum materials. Findings have implications for improving energy efficiency, developing lead-free solar cells, and enabling high-speed data processing. The work has trained numerous graduate students and postdocs, fostering the next generation of computational materials scientists. The original goals were to develop theoretical models and computational tools to predict and optimize electronic properties of materials for energy applications. All objectives were accomplished, with no major departures from planned methodologies. Challenges in computational scaling were addressed through access to high-performance computing resources.

36 MATERIALS SCIENCE↗

Describing Point Defect Topology in 2D Energy Materials through Computer Vision

Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. Here we employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science.

2d materials↗

Describing Point Defect Topology in 2D Energy Materials Through Computer Vision

Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. We employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science.

2D materials↗

Describing Point Defect Topology in 2D Energy Materials Through Computer Vision

Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. Here we employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science. ML is often not just a matter of straightforward application, and pretrained models proved ineffective in this case. Instead, we trained our own neural network (NN) and applied data augmentation techniques and fine-tuning to the training dataset. Since labeled microscopy data is often scarce, we developed training data from a previously published wide-frame MXene image, using customized Gaussian fitting to locate atomic positions. Our trained model was then applied to a large dataset of experimental images, enabling a statistical study of defect configurations across three samples prepared with different HF etchant concentrations (5%, 9.1%, and 12.5%), as shown in Fig. 1. This also allowed us to investigate local strain around vacancies, though we find that we are limited by the precision of measurements using high-angle annular dark field (HAADF) images, as shown in Fig. 2. This study demonstrates how ML enables large-scale, quantitative analysis of atomic defects - an otherwise infeasible task with traditional methods. While our NN was specialized for Ti3C2 MXenes, the pipeline we developed provides a foundation for future ML models tailored to other materials. Ultimately, we envision embedding the NN onto the microscope to give real-time feedback to the user. To make this a reality, continued work is necessary to fully understand the NN's capabilities and limitations. This study gets one step closer to our goals of automated experimentation moving away from traditional methods of manual labeling. As ML capabilities advance, we hope to continue adapting and applying these techniques in microscopy.

2D materials↗

Vortex Lattices in Active Nematics with Periodic Obstacle Arrays

Here, we numerically model a two-dimensional active nematic confined by a periodic array of fixed obstacles. Even in the passive nematic, the appearance of topological defects is unavoidable due to planar anchoring by the obstacle surfaces. We show that a vortex lattice state emerges as activity is increased, and that this lattice may be tuned from “ferromagnetic” to “antiferromagnetic” by varying the gap size between obstacles. We map the rich variety of states exhibited by the system as a function of distance between obstacles and activity, including a pinned defect state, motile defects, the vortex lattice, and active turbulence. We demonstrate that the flows in the active turbulent phase can be tuned by the presence of obstacles, and explore the effects of a frustrated lattice geometry on the vortex lattice phase.

36 MATERIALS SCIENCE↗

Complex Oxides under Simulated Electric Field: Determinants of Defect Polarization in AB O 3 Perovskites

Abstract Polarization of ionic and electronic defects in response to high electric fields plays an essential role in determining properties of materials in applications such as memristive devices. However, isolating the polarization response of individual defects has been challenging for both models and measurements. Here the authors quantify the nonlinear dielectric response of neutral oxygen vacancies, comprised of strongly localized electrons at an oxygen vacancy site, in perovskite oxides of the form AB O 3 . Their approach implements a computationally efficient local Hubbard U correction in density functional theory simulations. These calculations indicate that the electric dipole moment of this defect is correlated positively with the lattice volume, which they varied by elastic strain and by A‐site cation species. In addition, the dipole of the neutral oxygen vacancy under electric field increases with increasing reducibility of the B‐site cation. The predicted relationship among point defect polarization, mechanical strain, and transition metal chemistry provides insights for the properties of memristive materials and devices under high electric fields.

36 MATERIALS SCIENCE↗

Understanding the Mechanism of Secondary Cation Release from the (001) Surface of Li(Ni 1/3 Mn 1/3 Co 1/3 )O 2 : Insights from First-Principles

The transformations of complex metal oxides in aqueous settings must be studied to form a chemical understanding of how technologically relevant nanomaterials impact the environment upon disposal. Owing to the inherent heterogeneity and structural complexity of the ternary intercalation material Li(Ni x Mn y Co 1-x-y )O 2 (NMC), the mechanisms of chemical processes at the solid–water interfac e are challenging to model. Here, density functional theory (DFT) + solvent ion methodology is used to study the energetics of stepwise release of two surface metals following unique pathways. Further, the study spans different combinations of metal removal and also considers unique patterns of defects formed by modeling the NMC surface in supercells. The approach here also considers the equilibration of the surface with the surroundings between successive metal removals. A key finding is that a second metal removal prefers to proceed at a metal lattice site adjacent to the initial defect, and this is attributed in part to how the resulting slab with two metal vacancies maintains the most antiferromagnetic couplings between the remaining Ni/Mn.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tracking the evolution from isolated dimers to many-body entanglement in $\mathrm{NaLu}_x \mathrm{Yb}_{1-x}\mathrm{Se_2}$

Here, we synthesize homogeneous compositions of NaLu x Yb 1-x Se 2 , connecting nonmagnetic NaLuSe 2 to the triangular lattice spin liquid candidate NaYbSe 2 . Thermal and magnetic properties are studied as the system evolves from one with dilute magnetic defects to one of a dense magnetic lattice. The field- and temperature-dependent heat capacity show the carriers of entropy cross over from isolated magnetic ions to a correlated lattice born from spin dimers. For the dilute system we estimate the single-ion anisotropy (g ⟂ /g ∥ =3.13) and also the dimer exchange couplings J ⟂ (=5.4 K) and J ⟂ (=9.6 K), in order to draw comparison to the half-doped and full magnetic compounds.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗