Optimized Alloy Composites Final Technical Report
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21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
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Strain-driven oxygen vacancy ordering in LaNiO 3 thin films revealed by integrated differential phase contrast imaging in scanning transmission electron microscopy
Rare-earth nickelates, such as LaNiO 3 (LNO), exhibit complex electronic properties, with ordered oxygen vacancies (OOV) influencing conductivity and magnetic behavior. We investigate the structural stability of strain-induced OOV phases in LNO thin films grown on SrTiO 3 substrates and the impact of Ruddlesden–Popper (RP) faults. Using high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) and integrated differential phase contrast (iDPC) STEM imaging, we conducted atomic-scale structural and compositional analyses of OOV. Geometric phase analysis (GPA) was employed to measure the strain in fault-free and RP fault regions, while density functional theory (DFT) calculations explored different OOV arrangements in the LNO phase. Simulated iDPC-STEM imaging of energy-stabilized structures was performed to correlate with experimental results. Here, our findings reveal superstructure modulation in the chemical composition and atomic-scale lattice structure in LNO, primarily due to the formation of the OOV in Ni–O layers of the LaNiO 2.5 phase. The out-of-plane compressive strain of about 2% stabilizes this phase, reducing the strain, diminishing OOV, and transforming them into LNO.
36 MATERIALS SCIENCE↗
Casting at Sigma: Moving from an art to a science.
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36 MATERIALS SCIENCE↗
Developing the Science Basis for Understanding Polymer Encapsulant Degradation Mechanisms: DuraMAT 2.0 Final Project Report
Polymeric encapsulants are essential materials in photovoltaic modules, protecting sensitive electronics from the environment while providing mechanical integrity to the multilayered assembly. However, these polymeric materials are susceptible to degradation processes driven by the ingress of environmental species, ultraviolet radiation, thermal stresses, and mechanical loading. In this study, we employ a combined atomistic simulation and accelerated aging experimental approach to study the molecular-scale mechanisms of encapsulant degradation. Classical molecular dynamics simulations quantify the diffusion of environmental and degradation species through the polymer matrix, producing composition-specific diffusion coefficients. Reactive simulations characterize activation energy barriers and reaction rate constants for key chemical pathways. In parallel, thermal-desorption analyses coupled with mass spectrometry monitor the emergence and concentration profiles of degradation products under controlled stressor conditions. By integrating simulation and experiment, we establish quantitative correlations between polymer composition, species diffusivity, and chemical reactivity. We anticipate that these relations and quantitative values could serve as high-fidelity inputs to reaction-diffusion models, enabling physics-informed lifetime predictions and guiding the design of more durable encapsulant materials for solar energy applications.
36 MATERIALS SCIENCE↗
Turn‐On of Current‐Induced Spin Torque Upon Non‐collinear Antiferromagnetic Ordering in Delafossite PdCrO 2
We report measurements of the current-induced spin torque produced by the delafossite antiferromagnet PdCrO 2 and acting on an adjacent ferromagnetic permalloy layer. The spin torque increases strongly as the temperature is reduced through the Néel temperature, when the PdCrO 2 transitions from a paramagnetic phase to a noncollinear antiferromagnetic state. This result is qualitatively consistent with density functional theory calculations regarding how spin-current generation changes upon antiferromagnetic ordering in PdCrO 2 .
36 MATERIALS SCIENCE↗
Toward engineering lattice structures with the material point method (MPM)
This study examines the potential of two variants of the material point method—the generalized interpolation material point (GIMP) and dual domain material point (DDMP) methods—in developing a robust computational framework for engineering lattice structures under different loading conditions. The study begins with assessing the ability of the two methods in predicting elastic buckling phenomena using column geometries with and without initial geometric imperfections. The results indicate that both methods effectively capture buckling phenomena when initial geometric imperfections are introduced. After this verification step, we create several models of tetrahedral lattice structures with varying strut diameter and orientation and subject them to quasi-static loading. We then validate the numerical results using laboratory test results. The results show that, while both methods accurately predict load–displacement curves in the pre-buckling regime, their predictive capabilities diminish in the post-buckling regime. Through visual comparison between the numerical and experimental deformed shapes, it appears that the discrepancies between model and experimental results are attributed to initial geometric imperfections in the lattices that occurred during 3D printing. We then establish a second set of lattice models where different types of initial geometric imperfections are considered. The results from these models show that imperfections have a negligible influence in the pre-buckling regime but affect the behavior considerably in the post-buckling regime. As a final step in this work, we subject the lattice models to impact loading and employ hypothetical soft and stiff materials. These results show that the lattice stiffness, which depends on material stiffness, strut diameter, and orientation, significantly influences the ability of a lattice structure to resist impact. In particular, we find that a stiffer lattice (i.e., one made with a stiff material and thicker struts) is capable of absorbing more energy than a softer one during impact. Although material nonlinearities, inelasticity, and detailed contact formulations are not considered in this study, the findings obtained herein lay the groundwork for engineering lattice structures under extreme loading conditions through a simulation-driven framework based on particle-based methods.
97 MATHEMATICS AND COMPUTING↗
Polymer-iron oxide hybrid films for controlling electrokinetic properties
Electrokinetic phenomena at polymer-water interfaces are central to technologies for water purification, ion separations, and energy conversion, yet the ability to systematically control polymer surface charge and associated electrokinetic processes remains limited. Here, we demonstrate a simple liquid-phase infiltration (LPI) method to synthesize polymer–metal oxide hybrid films with controllable interfacial properties. Hydroxy-terminated poly(2-vinylpyridine) (P2VP-OH) brushes grafted to silicon substrates were infiltrated with iron nitrate from ethanolic solution, followed by low-temperature thermal treatment to convert the infiltrated precursor into iron oxide. Spectroscopic ellipsometry, X-ray photoelectron spectroscopy, and thermogravimetric analysis confirmed oxide incorporation and hybrid film formation without polymer degradation. Electrokinetic measurements reveal that the hybrid films acquire the electrokinetic properties of the infiltrated oxide, with concentration-dependent streaming potentials and surface conductivities closely matching those of pure iron oxide films. These results establish metal oxide infiltration as a scalable and low-cost strategy for controlling interfacial charge in polymer surfaces. The approach introduces new materials and design parameters for tailoring ion selectivity, transport, and energy conversion, with broad implications for the development of advanced membranes, electrokinetic harvesting devices, and polymer-supported oxide electrodes.
36 MATERIALS SCIENCE↗
Upcycling Polycrystalline LiNi1/3Mn1/3Co1/3O2 to High-Performance Large-Grained LiNi0.6Mn0.2Co0.2O2 via Simplified Polyol-Mediated Recycling
The escalating demand for lithium-ion batteries (LIBs) necessitates advanced recycling strategies that can address both resource scarcity and environmental impact. While conventional hydrometallurgy shows promise, it is challenged by complexity, impurity management, and environmental footprint. Here, we report a strategic polyol-metallurgy recycling process that efficiently transforms spent polycrystalline LiNi1/3Mn1/3Co1/3O2 (NMC111) into high-performance large-grained LiNi0.6Mn0.2Co0.2O2 (NMC622), offering dual benefits of compositional upcycling and morphology upgradation. Our approach leverages a polyol system with meticulous control over nickel salt addition and the precipitation process. This yields upcycled cathode materials possessing excellent structural integrity, well-defined large-grained particles (5-10?..mu..m), and robust electrochemical performance, including a specific capacity of ~182 mAh g-1 at C/10 and 88.0% capacity retention after 100 cycles. This facile and multifunctional process provides an environmental-friendly pathway for advanced cathode recycling, significantly contributing to a circular economy for LIBs through precise control over critical material attributes.
25 ENERGY STORAGE↗
Confinement-Driven Segregation Enables Glassy Polymer Hybrid Materials Featuring Disordered Hyperuniformity and Integrated Self-Healing
The blending of glassy copolymer-brush modified colloids with a viscoelastic linear copolymer featuring intrinsic self-healing enabled disordered hyperuniform hybrid materials that combined mechanical robustness with structural color, processability, environmental stability, and the ability to recover structure and properties after incurring physical damage via ‘integrated self-healing’. Symmetric linear n-butyl acrylate/methyl methacrylate (BA/MMA) were co-assembled with asymmetric glassy BA/MMA statistical copolymer brush (silica) particles. ‘Confinement-driven segregation’ resulted in a microphase-separated morphology in which the linear copolymer resided within the interstitial regions of a rigid (∼1 GPa) copolymer brush particle template with disordered hyperuniform microstructure. Diffusion of the self-healing copolymer additive into damage regions drove the recovery after damage, along with the restoration of structural color due to the materials hyperuniform microstructure. The synergistic action of intrinsic and extrinsic healing mechanisms could provide a versatile platform for the bottom-up fabrication of multifunctional hybrid materials with increased damage resistance and functional longevity.
36 MATERIALS SCIENCE↗
Macroscale-area patterning of three-dimensional DNA-programmable frameworks
Not Available
36 MATERIALS SCIENCE↗
Active oversight and quality control in standard Bayesian optimization for autonomous experiments
The fusion of experimental automation and machine learning has catalyzed a new era in materials research, prominently featuring Gaussian Process (GP) Bayesian Optimization (BO) driven autonomous experiments. Here we introduce a Dual-GP approach that enhances traditional GPBO by adding a secondary surrogate model to dynamically constrain the experimental space based on real-time assessments of the raw experimental data. This Dual-GP approach enhances the optimization efficiency of traditional GPBO by isolating more promising space for BO sampling and more valuable experimental data for primary GP training. We also incorporate a flexible, human-in-the-loop intervention method in the Dual-GP workflow to adjust for unanticipated results. We demonstrate the effectiveness of the Dual-GP model with synthetic model data and implement this approach in autonomous pulsed laser deposition experimental data. This Dual-GP approach has broad applicability in diverse GPBO-driven experimental settings, providing a more adaptable and precise framework for refining autonomous experimentation for more efficient optimization.
36 MATERIALS SCIENCE↗
Ferroaxial density wave from intertwined charge and orbital order in rare-earth tritellurides
The discovery of the axial amplitude mode—commonly referred to as the Higgs mode—in charge density wave systems, such as rare-earth tritellurides, indicates the presence of a hidden order. A theoretical study proposed that this axial Higgs mode arises from a hidden orbital texture of the charge density wave, which produces a ferroaxial charge order. However, experimental evidence for the specific hidden order has been lacking. Here, we demonstrate a ferroaxial order of electronic origin throughout the rare-earth tritellurides. In ErTe 3 and HoTe 3 , which exhibit two distinct charge density waves with different ordering temperatures, a detailed investigation shows that the high-temperature charge order phase breaks translational, rotational and all vertical as well as diagonal mirror symmetries. Furthermore, this phase produces an axial Higgs mode and an axial electronic gap. By contrast, the low-temperature phase breaks only translational symmetry and gives rise to a scalar Higgs mode. Notably, both phases preserve the space inversion and time-reversal symmetries. These findings are consistent with a ferroaxial phase driven by coupled orbital and charge orders, highlighting the role of Higgs modes in revealing hidden orders in systems with intertwined charge density waves.
36 MATERIALS SCIENCE↗
Proximity ferroelectricity in wurtzite heterostructures
Proximity ferroelectricity is an interface-associated phenomenon in electric-field-driven polarization reversal in a non-ferroelectric polar material induced by one or more adjacent ferroelectric materials. Here, in this paper, we report proximity ferroelectricity in wurtzite ferroelectric heterostructures. In the present case, the non-ferroelectric layers are AlN and ZnO, whereas the ferroelectric layers are Al 1−x B x N, Al 1−x Sc x N and Zn 1−x Mg x O. The layered structures include nitride–nitride, oxide–oxide and nitride–oxide stacks that feature two-layer (asymmetric) and three-layer (symmetric) configurations. Ferroelectric switching in both layers is validated by multimodal characterization methods, including polarization hysteresis, anisotropic chemical etching, second harmonic generation, piezo response force microscopy, electromechanical testing and atomic resolution polarization orientation imaging in real space by scanning transmission electron microscopy. We present a physical switching model in which antipolar nuclei originate in the ferroelectric layer and propagate towards the internal non-ferroelectric interface. The domain wall leading edge produces elastic and electric fields that extend beyond the interface at close proximity, reducing the switching barrier in the non-ferroelectric layer, and allowing complete domain propagation without breakdown. Density functional theory calculations of polymorph energies, reversal barriers and domain wall energies support this model. Proximity ferroelectricity enables polarization reversal in wurtzites without the chemical or structural disorder that accompanies elemental substitution, opening new questions and opportunities regarding interface-based ferroelectricity.
36 MATERIALS SCIENCE↗
Unconventional nonlinear Hall effects in twisted multilayer 2D materials
We present the first investigation of unusual nonlinear Hall effects in twisted multilayer 2D materials. Contrary to expectations, our study shows that these nonlinear effects are not merely extensions of their monolayer counterparts. Instead, we find that stacking order and pairwise interactions between neighboring layers, mediated by Berry curvatures, play a pivotal role in shaping their collective nonlinear optical response. By combining large-scale Real-Time Time-Dependent Density Functional Theory (RT-TDDFT) simulations with model Hamiltonian analyses, we demonstrate a remarkable second-harmonic transverse response in hexagonal boron nitride four-layers, even in cases where the total Berry curvature cancels out. Furthermore, our symmetry analysis of the layered structures provides a simplified framework for predicting nonlinear responses in multilayer materials in general. Our investigation challenges the prevailing understanding of nonlinear optical responses in layered materials and opens new avenues for the design and development of advanced materials with tailored optical properties.
36 MATERIALS SCIENCE↗
Equal resistance single and bilayer films decouple role of solid electrolyte interphase from lithium morphology in batteries
Equal resistance single and bilayer films establish that thin film/electrolyte interfaces are more important for battery performance compared to copper/thin film interfaces due to their role in inorganic-rich solid electrolyte interphase formation.
Shuchi, Sanzeeda Baig [Department of Chemical Engi↗
Invariant discovery of features across multiple length scales: Applications in microscopy and autonomous materials characterization
Physical imaging is a foundational characterization method in areas from condensed matter physics and chemistry to astronomy and spans length scales from atomic to universe. Images encapsulate crucial data regarding atomic bonding, materials microstructures, and dynamic phenomena such as microstructural evolution and turbulence, among other phenomena. The challenge lies in effectively extracting and interpreting this information. Variational Autoencoders (VAEs) have emerged as powerful tools for identifying the underlying factors of variation in image data, providing a systematic approach to distilling meaningful patterns from complex data sets. However, a significant hurdle in their application is the definition and selection of appropriate descriptors reflecting local structures. Here, we introduce the scale-invariant VAE approach (SI-VAE) based on the progressive training of the VAE with the descriptors sampled at different length scales. The SI-VAE allows the discovery of the length scale-dependent factors of variation in the system. Here, we illustrate this approach using the ferroelectric domain images and generalize it to the movies of the electron-beam induced phenomena in graphene and topography evolution across combinatorial libraries. This approach can further be used to initialize the decision making in automated experiments including structure–property discovery and can be applied across a broad range of imaging methods. This approach is universal and can be applied to any spatially resolved data including both experimental imaging studies and simulations, and can be particularly useful for exploration of phenomena such as turbulence and scale-invariant transformation fronts.
36 MATERIALS SCIENCE↗
Ferro-ionic states and domains morphology in Hf x Zr 1–x O 2 nanoparticles
Unique polar properties of nanoscale hafnia-zirconia oxides (Hf x Zr 1–x O 2 ) are of great interest for condensed matter physics, nanophysics, and advanced applications. These properties are connected (at least partially) to the ionic–electronic and electrochemical phenomena at the surface, interfaces, and/or internal grain boundaries. Here, we calculated the phase diagrams, dielectric permittivity, spontaneous polar, and antipolar ordering, as well as the domain structure morphology in Hf x Zr 1–x O 2 nanoparticles covered by ionic–electronic charge originating from surface electrochemical adsorption. We revealed that the ferro-ionic coupling supports the polar long-range order in nanoscale Hf x Zr 1–x O 2 , induces, and/or enlarges the stability region of the labyrinthine domains toward smaller sizes and smaller environmental dielectric constant at low concentrations of the surface ions. The ferro-ionic coupling causes the transition to the single-domain ferro-ionic state at high concentrations of the surface ions. We predict that the labyrinthine domain states, being multiple-degenerated, may significantly affect the emergence of the negative differential capacitance state in the nanograined/nanocrystalline Hf x Zr 1–x O 2 films.
36 MATERIALS SCIENCE↗
Decoding diffraction and spectroscopy data with machine learning: A tutorial
This Tutorial provides a step-by-step guide on how to apply supervised machine-learning techniques to analyze diffraction and spectroscopy data. This Tutorial details four models—a reconstruction-focused model, a regression-focused model, a hybrid reconstruction/regression model, and a multimodal model—that use x-ray diffraction profiles and vibrational density of states spectra to predict various microstructural descriptors. In this Tutorial, we cover data pre-processing steps, constructions of the models via dimensionality reduction and regression, training, and analysis of these models. Comparisons of the model’s performance are provided, highlighting the strength and weakness of the various approaches utilized.
36 MATERIALS SCIENCE↗