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At least 307 records · Page 17

Uncovering multiscale structure-property correlations via active learning in scanning tunneling microscopy

Atomic arrangements and local sub-structures fundamentally influence emergent material functionalities. These structures are conventionally probed using spatially resolved studies and the property correlations are deciphered by a researcher based on sequential explorations, thereby limiting the efficiency and scope. Here we demonstrate a multi-scale Bayesian deep-learning based framework that automatically correlates material structure with its electronic properties using scanning tunneling microscopy (STM) measurements in real-time. Its predictions are used to autonomously direct exploration toward regions of the sample that optimize a given material property. This method is deployed on a low-temperature ultra-high vacuum STM to understand the structure-property relationship in a europium-based semimetal, EuZn 2 As 2 , a promising candidate relevant to magnetism-driven topological phenomena. The framework employs a sparse-sampling approach to efficiently construct the scalar-property space using minimal measurements, about 1–10% of the data required in standard hyperspectral methods. Moreover, we formulate the problem hierarchically across length scales, implementing autonomous workflow to locate mesoscopic and atomic structures that correspond to a target material property. This framework offers the choice to design scalar-property from the spectroscopic data to steer sample exploration. Our findings reveal correlations of the electronic properties unique to surface terminations, local defect density, and point defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Local Spin Density Approximation Strongly Improved by a Better-Informed Local Scaling of Its Self-Interaction Correction

The Perdew−Zunger self-interaction correction (PZSIC) makes density functional approximations (DFAs) exact for all one-electron densities. However, it overcorrects in manyelectron regions, introducing errors for the uniform-density limit, where uncorrected DFAs are exact. The locally scaled PZSIC (LSIC), based on the iso-orbital indicator zσ [which distinguishes single-orbital and slowly varying density regions and is used with the local spin density approximation (LSDA)], restores the uniform-density limit and significantly improves results for many properties, including chemical reaction barrier heights, atomization energies, and ionization potentials. Yet, LSIC performs poorly for weakly bonded systems, leaving many unbound, due to limitations of its iso-orbital indicator. To correct this, in this work we propose a new local scaling, LSIC-α, based on the iso-orbital indicator ασ (which additionally identifies regions of overlapping density tails). A two-parameter scaling function of ασ is fitted to a subset of the nonbonded appropriate norms for the SCAN and r2SCAN meta- GGAs, and tested on many properties of main-group atoms, molecules, and molecular complexes. LSIC-α greatly improves the interaction energies of weakly bonded systems in the S22 data set while retaining LSIC’s accuracy for other properties. This work shows that the errors of LSDA (and presumably of higher-level DFAs) can be largely but not entirely repaired by a proper “do no harm” self-interaction correction.

Approximation↗

Fluidic Flow Assisted Deterministic Folding of Van der Waals Materials

Origami offers a distinct approach for designing and engineering new material structures and properties. The folding and stacking of atomically thin van der Waals (vdW) materials, for example, can lead to intriguing new physical properties including bandgap tuning, Van Hove singularity, and superconductivity. On the other hand, achieving well-controlled folding of vdW materials with high spatial precision has been extremely challenging and difficult to scale toward large areas. In this paper, a deterministic technique is reported to fold vdW materials at a defined position and direction using microfluidic forces. Electron beam lithography (EBL) is utilized to define the folding area, which allows precise control of the folding geometry, direction, and position beyond 100 nm resolution. Using this technique, single-atomic-layer vdW materials or their heterostructures can be folded without the need for any external supporting layers in the final folded structure. In addition, arrays of patterns can be folded across a large area using this technique and electronic devices that can reconfigure device functionalities through folding are also demonstrated. Such scalable formation of folded vdW material structures with high precision can lead to the creation of new atomic-scale materials and superlattices as well as opening the door to realizing foldable and reconfigurable electronics.

2D materials↗

Synthesizing intermetallic thermoelectric materials using metal flux growth method

With zero energy poverty by 2050 goals, exploring innovative energy technologies is essential. Thermoelectric materials (TEMs) have the potential to harness waste heat and convert it to electricity (e.g., for spacecraft power, sensors, and cryogenic cooling). Two limitations of thermoelectric compounds are their low efficiency and limited pool of materials. Optimizing the efficiency of TEMs is challenging due to the interdependent relationship between electrical and thermal conductivity. A deeper understanding of electronic properties and lattice thermal conductivity is necessary to “understand, predict and ultimately control” the thermoelectric properties of TEMs. Understanding the influence of light-atom-doping and intrinsic defects on the electronic properties of the f-element containing TEMs are important questions that need to be answered to design and synthesize TEMs with optimal parameters. The purpose of this work is to understand how doping f-element based TEMs with light elements, such as carbon and boron, would impact the crystal structure, bond lengths, band gaps, and thermoelectric characteristics. High-quality f¬-element containing intermetallic single crystals are grown in metal flux media. In molten metal flux growth method, one or more low-melting metals such as aluminum, gallium, tin, and bismuth are used in excess as the reaction medium. As these are solution-state reactions, we can use lower temperatures than solid-state reactions and isolate the kinetic products instead of the thermodynamically stable compound. Then these are characterized using X-ray diffraction, scanning electron microscopy, energy dispersive spectroscopy, magnetization, electrical and thermal conductivities, and thermoelectric power.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗

Giant momentum-dependent spin splitting in centrosymmetric low-$\textit{Z}$ antiferromagnets

The energy vs crystal momentum $\textit{E(k)}$ diagram for a solid (band structure) constitutes the road map for navigating its optical, magnetic, and transport properties. By selecting crystals with specific atom types, composition, and symmetries, one could design a target band structure and thus desired properties. A particularly attractive outcome would be to design energy bands that are split into spin components with a momentum-dependent splitting, as envisioned by Pekar and Rashba, enabling spintronic application. The current paper provides “design principles” for wave-vector dependent spin splitting (SS) of energy bands that parallel the traditional Dresselhaus and Rashba spin-orbit coupling (SOC)–induced splitting, but originates from a fundamentally different source—antiferromagnetism. Here, we identify a few generic antiferromagnetic (AFM) prototypes with distinct SS patterns using magnetic symmetry design principles. These tools allow also the identification of specific AFM compounds with SS belonging to different prototypes. A specific compound—centrosymmetric tetragonal MnF 2 —is used via density functional band-structure calculations to quantitatively illustrate one type of AFM SS. Unlike the traditional SOC-induced effects restricted to noncentrosymmetric crystals, we show that antiferromagnetic-induced spin splitting broadens the playing field to include even centrosymmetric compounds, and gives SS comparable in magnitude to the best known (“giant’” SOC effects, even without traditional SOC, and consequently does not rely on the often-unstable high atomic number elements required for high SOC. We envision that use of the current design principles to identify an optimal antiferromagnet with spin-split energy bands would be beneficial for efficient spin-charge conversion and spin-orbit torque applications without the burden of requiring compounds containing heavy elements.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Ferromagnetic resonances in single-crystal yttrium iron garnet nanofilms fabricated by metal-organic decomposition

Tunable microwave and millimeter wave oscillators and bandpass filters with ultra-low phase noise play a critical role in electronic devices, including wireless communication, microelectronics, and quantum computing. Magnetic materials, such as yttrium iron garnet (YIG), possess ultra-low phase noise and a ferromagnetic resonance tunable up to tens of gigahertz. Here, we report structural and magnetic properties of single-crystal 60 and 130 nm-thick YIG films prepared by metal-organic decomposition epitaxy. These films, consisting of multiple homoepitaxially grown monolayers, are atomically flat and possess magnetic properties similar to those grown with liquid-phase epitaxy, pulsed laser deposition, and sputtering. Our approach does not involve expensive high-vacuum deposition systems and is a true low-cost alternative to current commercial techniques that have the potential to transform the industry.

Wang, Szu-Fan (Paul)↗

A machine learning approach to quantify degradation of nuclear fuels and the effects of fission products

Nuclear fuel performance is critically dependent on understanding the evolution of fuel properties under operational conditions, a complex challenge driven by chemical changes and substantial radiation damage during fission. Traditionally, property evolution has been determined via empirical data collected following irradiation. However, these empirical correlations are limited in their applicability beyond the specific conditions in which they were obtained. This study explores a novel approach to address this challenge by applying materials informatics to develop a machine learning random forest (ML-RF) model that captures the effects of fission products on fuel compounds. The model predicts formation enthalpy (ΔH f ) by leveraging extensive quantum materials property data and correlating it with material descriptors such as composition, atomic and site features, and crystal lattice properties. This ML-RF model enables rapid interpolation across the compositional and structural spaces covered by the training data, thus supporting high-throughput screening and energetic ranking of candidate phases. The model demonstrates the ability to predict ΔH f with a mean absolute error (MAE) of approximately 0.1 to 0.2 eV/atom across a wide range of compounds, including key nuclear fuel systems (U-O, U-N, U-C, U-Si, and U-Mo). For example, it was used to assess shifts in stoichiometry for UO 2 (O/M) and UN (N/M) fuels, revealing their distinct tendencies in chemical potential variation and enabling preliminary convex hull analyses. Furthermore, the model provides insights into how individual fission products affect fuel properties. Results indicate that larger fission products (e.g., Nd, Pu, Ce) have a more pronounced impact on UO 2 , while lighter ones (e.g., Zr) strongly influence UN. Here, the model developed in this work can be used to support the Accelerated Fuel Qualification approach by facilitating preliminary evaluations prior to extensive materials modeling and experimentation. To this end, the trained model has been made available to the fuel community to support ongoing fuel development efforts.

Accelerated fuel qualification↗

Modeling of deposit formation in mesoporous substrates via atomic layer deposition: Insights from pore‐scale simulation

Atomic layer deposition (ALD) has been a promising technique in fabricating membranes and tuning their properties with a precision at the atomic level. Fabrication of zeolitic imidazolate framework (ZIF) membranes using the ligand-induced permselectivation (LIPS) method starts with the formation of an oxide in a mesoporous substrate by ALD and is followed by the transformation of this oxide to ZIF using imidazolate vapor treatment. The objective of the ALD step is to block the mesopores with a thin deposit, that is, one with small penetration depth and small thickness on the top surface of the substrate. Unlike typical ALD on nonporous substrates, where all available sites react per ALD cycle, thin deposit formation in a mesoporous substrate requires that only a small fraction of the available deposition sites (i.e., close to the substrate surface) is subjected to ALD. Consequently, reactant dosing and duration of pulses are important process variables which, together with diffusion and reaction kinetics determine the deposit structure. Quantitative understanding of the interplay of these variables and phenomena can enable the rational design of ALD within mesoporous substrates. Here, we extend our earlier modeling effort considering the coexistence of ALD both inside the pores and on the external surface of the substrate. Finite-volume based models were developed and validated to simulate the two distinct modes of deposition cycle by cycle. The total mass uptake of the substrate with ALD cycles can be predicted using the combined surface deposition and pore reaction–diffusion models as affirmed by in situ quartz crystal microbalance experimental data. The ALD reactor model combined with the deposition model can accurately capture the number of ALD cycles needed to block the pores of the substrate. Based on the model, we designed a modified ALD process and examined the performance of the corresponding LIPS membranes. Furthermore, the present modeling work provides a new understanding of the deposit formation via ALD within mesoporous substrates for a variety of membrane applications.

atomic layer deposition↗

Shear Softening in a Metallic Glass: First-Principles Local-Stress Analysis

Metallic glasses deform elastically under stress. However, the atomic-level origin of elastic properties of metallic glasses remain unclear. In this Letter using ab initio molecular dynamics simulations of the Cu 5 0Zr 50 metallic glass under shear strain, we show that the heterogeneous stress relaxation results in the increased charge transfer from Zr to Cu atoms, enhancing the softening of the shear modulus. Changes in compositional short-range order and atomic position shifts due to the nonaffine deformation are discussed. It is shown that the Zr subsystem exhibits a stiff behavior, whereas the displacements of Cu atoms from their initial positions, induced by the strain, provide the stress drop and softening.

36 MATERIALS SCIENCE↗

Molecular-Dynamics Analysis of the Mechanical Behavior of Plasma-Facing Tungsten

We report a systematic computational analysis of the mechanical behavior of plasma-facing component (PFC) tungsten focusing on the impact of void and helium (He) bubble defects on the mechanical response beyond the elastic regime. Specifically, we explore the effects of porosity and He atomic fraction on the mechanical properties and structural response of PFC tungsten, at varying temperature and bubble size. We find that the Young modulus of defective tungsten undergoes substantial softening that follows an exponential scaling relation as a function of matrix porosity and He atomic content. Beyond the elastic regime, our high strain rate simulations reveal that the presence of nanoscale spherical defects (empty voids and He bubbles) reduces the yield strength of tungsten in a monotonically decreasing fashion, obeying an exponential scaling relation as a function of tungsten matrix porosity and He concentration. Our detailed analysis of the structural response of PFC tungsten near the yield point reveals that yielding is initiated by emission of dislocation loops from bubble/matrix interfaces, mainly 1/2<111> shear loops, followed by gliding and growth of these loops and reactions to form <100> dislocations. Furthermore, dislocation gliding on the <111>{211} twin systems nucleates 1/6<111> twin regions in the tungsten matrix. These dynamical processes reduce the stress in the matrix substantially. Subsequent dislocation interactions and depletion of the twin phases via nucleation and propagation of detwinning partials lead the tungsten matrix to a next deformation stage characterized by stress increase during applied straining. Furthermore, our structural analysis reveals that the depletion of twin boundaries (areal defects) is strongly impacted by the density of He bubbles at higher porosities. After the initial stress relief upon yielding, increase in the dislocation density in conjunction with decrease in the areal defect density facilitates the initiation of dislocation-driven deformation mechanisms in the PFC crystal.

36 MATERIALS SCIENCE↗

Magnetoelectric properties at the Co/AlN(0001) interface

AlN nitride is a large-band-gap polar material that has gained interest due to its ability to become ferroelectric and its compatibility with Si- and GaN-based technologies. This compound could, therefore, be a good candidate to design new artificial multiferroics if combined with a ferromagnetic electrode. For this work, we performed first-principles calculations to investigate the set up of the magnetoelectric coupling at the Co/AlN(0001) interface. Our results describe a complex interfacial atomic structure with variable local magnetic properties as a function of the atom alignment. We predict an average variation of interface spin magnetization, when the polarization is reversed, of 3.83 𝜇B nm −2 , close to the values already reported in the literature at metal/oxide interfaces. This confirms the potential of this AlN-based ferroelectric compound to be used in future voltage-controlled spintronic devices.

36 MATERIALS SCIENCE↗

Single-Atom Nanozymes Linked Immunosorbent Assay for Sensitive Detection of A β 1-40: A Biomarker of Alzheimer’s Disease

Single-atom nanozymes (SANs) possess unique features of maximum atomic utilization and present highly assembled enzyme-like structure and remarkable enzyme-like activity. By introducing SANs into immunoassay, limitations of ELISA such as low stability of horseradish peroxidase (HRP) can be well addressed, thereby improving the performance of the immunoassays. In this work, we have developed novel Fe-N-C single-atom nanozymes (Fe-N x SANs) derived from Fe-doped polypyrrole (PPy) nanotube and substituted the enzymes in ELISA kit for enhancing the detection sensitivity of amyloid beta 1-40. Results indicate that the Fe-N x SANs contain high density of single-atom active sites and comparable enzyme-like properties as HRP, owing to the maximized utilization of Fe atoms and their abundant active sites, which could mimic natural metalloproteases structures. Further designed SAN-linked immunosorbent assay (SAN-LISA) demonstrates the ultralow limit of detection (LOD) of 0.88 pg/mL, much more sensitive than that of commercial ELISA (9.98 pg/mL). The results confirm that the Fe-N x SANs can serve as a satisfactory replacement of enzyme labels, which show great potential as an ultrasensitive colorimetric immunoassay.

60 APPLIED LIFE SCIENCES↗

Temperature-Dependent Thermal and Mechanical Properties of a Wire Arc Additively Manufactured Low Transformation Temperature Steel

Recent research has studied the use of low transformation temperature (LTT) martensite steel as feedstock for wire arc additive manufacturing (WAAM) and low tensile residual stresses or compressive residual stresses were detected in the printed walls. These residual stress states help to improve printed product properties such as fatigue strength and corrosion resistance. However, the thermal and mechanical properties of WAAM printed LTT martensite steel walls are largely unknown. In this work, a printed LTT martensite steel was characterized for its thermal, metallurgical, and mechanical behavior at room and elevated temperatures. The temperature-dependent specific heat capacity, thermal expansion, atomic lattice spacing, and tensile properties were measured during both heating and cooling and related to observed microstructural features and computational thermodynamics predictions. These results revealed a large hysteresis in the martensitic transformation, with a martensite start temperature of 240 °C and austenite start temperature of 680 °C. Additional thermal cycles and specimen orientation did not affect the printed specimen austenite and martensite transformations. However, it was observed that the printed metal may exhibit tempering embrittlement at about 350 °C but further studies are needed to confirm that. Further, these results suggest that a temperature control of 250 °C to 350 °C during WAAM is needed to maximize the stress reduction potential of the LTT250 martensite steel. Opportunities for future implementation of LTT martensite steels and optimization of additive manufacturing process conditions are identified.

36 MATERIALS SCIENCE↗

Breaking atomic-level ordering via biaxial strain in functional oxides: A DFT study

Oxygen vacancies are found to play a crucial role in inducing many functional properties at the heterointerfaces in complex oxides. Gaining better control over the properties requires an understanding of the atomic structure of oxygen vacancies at the heterointerfaces. In this paper, we elucidate the effects of the interfacial strain on the oxygen-vacancy ordering in fluorite δ-Bi 2 O 3 and perovskite LaNiO 2.5 using first-principles calculations. By applying biaxial strains, we find that the <110>-<111> oxygen vacancy order in δ-Bi2O3 is broken, resulting in a faster diffusion of oxygen ions. Similarly, the biaxial strain is used to leverage both ordered and disordered arrangements of vacancies in LaNiO 2.5 . Besides the vacancy order, we find that the biaxial strain can also be used to break the cation order in Gd 2 Ti 2 O 7 , where Gd and Ti antisites can be created on the cation sublattice, which leads to enhanced radiation tolerance and higher oxygen diffusivity. Overall, these results indicate that the biaxial strain that is commonly present at heterointerfaces can be used to gain control over both ordered and disordered arrangements of defects, potentially opening new opportunities to functionalize complex oxides.

36 MATERIALS SCIENCE↗

Unraveling peculiar magnetism and band topology in Mn 3 Sb

Magnetic, pseudogap, topological, magnetostructural, and elastic behaviors of Mn 3 Sb have been unraveled. The ferrimagnetism (FIM) is described by localized and delocalized electron magnetism resulting in different magnetic moments on Mn atoms, confirming the neutron diffraction data. The identified magnetostructural properties are due to the non-equivalent Mn atoms in its lowest symmetry structure. The electronic structure is also unique due to variable valance states of Mn atoms. The magnetic moment (4.10 μB) of non-equivalent Mn1 atom is antiparallely aligned with the magnetic moments (2.34 μB) of Mn 2 and Mn 3 atoms. The estimated Curie temperature, TC, is higher than the room temperature, which may have above the room temperature applications in spintronic devices. The band structure and density of states (DOS) show the characteristics of band topology (opening of a gap in Dirac-like band features) and pseudo-gap, respectively, around the Fermi level. While expanding the unit cell, the tetragonal FIM ground state transforms to the cubic primitive FIM phase, however, the contraction transforms it to the L1 2 ferromagnetic (FM) phase. The estimated elastic constants, bulk to shear modulus ratio, and elastic anisotropy factor indicate that Mn3Sb exhibits mechanically stable, ductile, and anisotropic behaviors, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ion-Assisted Nanoscale Material Engineering in Atomic Layers

Achieving deterministic control over the properties of low-dimensional materials with nanoscale precision is a long-sought goal. Mastering this capability has a transformative effect on the design of multifunctional electrical and optical devices. Here, we present an ion-assisted synthetic technique that enables precise control over the material composition and energy landscape of two-dimensional (2D) atomic crystals. Our method transforms binary transition-metal dichalcogenides, like MoSe2, into ternary MoS2αSe2(1-α) alloys with systematically adjustable compositions, α. By piecewise assembly of the lateral, compositionally modulated MoS2αSe2(1-α) segments within 2D atomic layers, we present a synthetic pathway toward the realization of multicompositional designer materials. Our technique enables the fabrication of advanced 2D structures with arbitrary boundaries, dimensions as small as 30 nm, and fully customizable energy landscapes. Our optical characterizations further showcase the potential for implementing tailored optoelectronics in these engineered 2D crystals.

2D materials↗