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At least 1,387 records · Page 77

Selectivity in Yttrium Manganese Oxide Synthesis via Local Chemical Potentials in Hyperdimensional Phase Space

In sharp contrast to molecular synthesis, materials synthesis is generally presumed to lack selectivity. The few known methods of designing selectivity in solid-state reactions have limited scope, such as topotactic reactions or strain stabilization. This contribution describes a general approach for searching large chemical spaces to identify selective reactions. This novel approach explains the ability of a nominally “innocent” Na 2 CO 3 precursor to enable the metathesis synthesis of single-phase Y 2 Mn 2 O 7 : an outcome that was previously only accomplished at extreme pressures and which cannot be achieved with closely related precursors of Li 2 CO 3 and K 2 CO 3 under identical conditions. By calculating the required change in chemical potential across all possible reactant-product interfaces in an expanded chemical space including Y, Mn, O, alkali metals, and halogens, using thermodynamic parameters obtained from density functional theory calculations, we identify reactions that minimize the thermodynamic competition from intermediates. In this manner, only the Na-based intermediates minimize the distance in the hyperdimensional chemical potential space to Y 2 Mn 2 O 7 , thus providing selective access to a phase which was previously thought to be metastable. Experimental evidence validating this mechanism for pathway-dependent selectivity is provided by intermediates identified from in situ synchrotron-based crystallographic analysis. Finally, this approach of calculating chemical potential distances in hyperdimensional compositional spaces provides a general method for designing selective solid-state syntheses that will be useful for gaining access to metastable phases and for identifying reaction pathways that can reduce the synthesis temperature, and cost, of technological materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High sensitivity pressure and temperature quantum sensing in pentacene-doped p-terphenyl single crystals

Quantum sensors’ responsiveness to their physical environment enables detection of variables such as temperature (T), pressure (P), and strain. We present a molecular platform for PT sensing using para-terphenyl crystals doped with pentacene (PDP), leveraging optically detected magnetic resonance (ODMR) of photoexcited triplet electron spins. We observe maximal frequency variations of df/dP=1.8 MHz/bar from 0-8 bar and df/dT=247 kHz/K from 79–330 K, over 1200 times and threefold greater, respectively, than those seen with nitrogen-vacancy centers in diamond and > 85-fold greater pressure sensitivity over the previous record. Density functional theory calculations indicate picometer-level PT-induced molecular orbital shifts are measurable via ODMR. PDP offers additional advantages including high sensor doping levels, narrow ODMR linewidths, high contrast, and low-cost single crystal growth. Overall, this work reports low-cost, optically-interrogated PT sensors and lays the foundation for increased versatility of quantum sensors through synthetic molecular design.

Magnetic properties and materials↗

Alloying multiple halide perovskites on the same sublattice in search of stability and target band gaps

Single-component halide perovskites (HPs) rarely satisfy all the necessary criteria for optoelectronic applications, such as achieving an optimal band gap while maintaining high chemical and structural stability. Alloying halide perovskites has emerged as a promising strategy, not only to enhance stability but also to fine-tune their electronic and optical properties. In this work, we explore multiple degrees of freedom in alloy design, considering different substitution sublattices sites (A, B, or X in ABX3 perovskites), various chemical species (isovalent and hetero-valent elements), and multi-component compositions on a given sublattice. Using first-principles calculations based on density functional theory (DFT), we investigate how compositional variations influence the electronic (band gap) and structural properties (mixing enthalpy) of HP alloys. Our approach employs the polymorphous cell model, allowing full local relaxation which breaks local symmetry while preserving global cubic symmetry—an essential framework for accurately modeling HPs. Our results reveal that X-site mixing (halogen substitution) primarily affects the valence band maximum, allowing target band gap engineering. Additionally, variations in halogen radii introduce internal strain through octahedral distortions, influencing the mixing enthalpy. A-site substitution, while not directly contributing to the band edge states, modifies structural stability via volume effects, indirectly impacting the band gap. B-site alloying plays a dominant role in band gap modulation, leading to either positive or negative band gap bowing. Specifically, isovalent B-site mixing (Sn–Pb) induces strong positive bowing, where the alloy band gap is smaller than the average gap of parent compounds, whereas hetero-valent mixing (Cd–Pb) results in pronounced negative bowing. As an aside, we investigate the competition between the excess energy of disordered alloys vs. that of long-range ordered double perovskites of the same compositions, seeking examples of ordered phases emerging from disordered alloys. Furthermore, our findings provide fundamental insights into the electronic and structural behavior of HP alloys, offering valuable design principles for the development of stable and efficient materials for next-generation photovoltaic and optoelectronic devices.

14 SOLAR ENERGY↗

Engineering exchange bias at the interface of self-polarized ultrathin ferroelectric Ba⁢Ti⁢O 3 and ferromagnetic La 0.67⁢ Sr 0.33 ⁢Mn⁢O 3

We investigate the emergence and optimization of conventional exchange bias (EB) in ultrathin (<10 nm) ferroelectric (FE) Ba⁢Ti⁢O 3 (BTO)/ferromagnetic (FM) La 0.67 ⁢Sr 0.33⁢ Mn⁢O 3 (LSMO) epitaxial bilayers without an antiferromagnetic (AFM) material. The EB originates from the electronic orbital reconstruction at the FE-FM interface due to the ferroelectric polarization. We achieve maximum EB of approximately 42 Oe with single-domain polarization in nine-unit-cell-thick BTO, setting the BTO thickness above the critical threshold for ferroelectricity yet below the thickness of strain relaxation and multidomain breakdown. Furthermore, the LSMO layer needs to be thick enough to sustain both the FM layer and polarization-induced AFM spin configuration at the LSMO/BTO interface, yet as thin as possible to enable the EB loop shift. The temperature, training, field, and thickness dependence of the EB confirm that the LSMO/BTO interface exhibits conventional EB despite its unconventional origin. Using x-ray magnetic circular dichroism, scanning transmission electron microscopy, and density-functional-theory calculations, we confirm that the macroscopic EB effect originates from the interfacial AFM spin configuration in LSMO driven by FE-induced d-orbital modifications in interfacial Mn ions. Thus, we engineer strong interfacial EB coupling in artificial multiferroics without a conventional AFM material by controlling FE polarization, highlighting the potential for advanced spintronic applications.

exchange bias↗

Applications of Nickelate perovskites for neuromorphic computing from electronic structure and Machine Learning

While the limit of Moore's law is presently being reached with current microelectronic technologies, we need to develop new paradigms that overcome this limitation. In that respect, neuromorphic computing is a concept that emulates the neural behavior and response of the human brain, and it has been recognized as a promising alternative approach. In this research project, we will perform multi-fidelity scale bridging to explore the potential use of materials with metal to insulator transition for neuromorphic applications. In particular, rare earth nickelates are promising for such purposes, as the transition in these materials is quite sensitive to a broad set of different external stimuli. Our multi-fidelity approach will bridge the high-fidelity electronic structure calculations with classical potentials. We will bridge dynamical mean field theory with a classical atomistic representation via a deep learning force field. The neural network is trained with energies, charges, and forces obtained by accurate electronic structure theories based on Dynamical Mean Field Theory. The configurational space is generated from known crystal phases, ab initio molecular dynamics with exchange-correlation functionals corrected with the Hubbard model, disordered phases with different concentrations of oxygen vacancies, and nonsymmetrical positions and induced strain by grain interfaces or contact with a substrate. Strategies to train the model with a reduced number of training examples are obtained from active learning methods, and new structures for improving the learning process are generated by using machine learning autoencoders. This classical potential will be validated through a diversity of electronic structure methods and represents an important step to combine the flexibility and accuracy of first-principles with the speed of classical potentials. The generated multi-fidelity surrogate model will be used to understand the role of strain, oxygen vacancies, proton doping, the variation of the crystal phase, substrate effects, vibrational effects as the octahedral rotation, grain boundaries and defect effects on the response of a Metal to Insulator Transition (MIT) in correlated materials. Long time and large-scale simulations will help understand the role of different stimuli to control the hysteresis of the MIT, as it has been experimentally suggested. Selected configurations will be analyzed with higher-level theories to provide an accurate electronic description and to study how the orbitals and charges are rearranged under different conditions.

36 MATERIALS SCIENCE↗

Dynamic fracture mechanics

Dynamic fracture and crack propagation concepts for ductile materials are reviewed. The equations for calculating dynamic stress integrity and the dynamic energy release rate in order to study dynamic crack propagation are provided. The stress intensity factor versus crack velocity relation is investigated. The uses of optical experimental techniques and finite element methods for fracture analyses are described. The fracture criteria for a rapidly propagating crack under mixed mode conditions are discussed; crack extension and fracture criteria under combined tension and shear loading are based on maximum circumferential stress or energy criteria such as strain energy density. The development and use of a Dugdale model and finite element models to represent crack and fracture dynamics are examined.

Kobayashi, A. S.↗

ElasTool v3.0: Efficient computational and visualization toolkit for elastic and mechanical properties of materials

Efficient computation and visualization of elastic and mechanical properties are crucial in the selection of materials and the design of new materials. Here, the ElasTool v3.0 toolkit marks a significant advancement in the computational analysis and visualization of elastic and mechanical properties of materials, essential in material selection and design. This enhanced version extends beyond standard calculations like elastic tensor, Young's modulus, bulk modulus, and Poisson's ratio. It introduces capabilities for computing minimum thermal conductivity, linear compressibility, rendering the Christoffel equation, and elastic energy density. Notably, it integrates advanced visualization tools, including compatibility with Plotly and Elate web platforms for interactive web-based property exploration. A key feature of ElasTool v3.0 is the implementation of second-order elastic constants (SOECs) for tubular 2D-based nanostructures and nanotubes. Leveraging high-efficiency strain-matrix sets (OHESS), the toolkit now facilitates efficient computation of elastic constants and mechanical properties at both zero and finite temperatures for 1D, 2D, and 3D dimensions. ElasTool is openly accessible on GitHub: https://github.com/gmp007/elastool.

1D, 2D, 3D, and tubular 2D nanostructure and nanot↗

Molecular dynamics studies of helium bubble effects on grain boundary fracture vulnerabilities in an Fe 70 Ni 11 Cr 19 –1%H austenitic stainless steel

Comprehensive molecular dynamics tensile test simulations have been performed to study the delamination processes of seven different grain boundaries / cleavage planes (Σ1{111}, Σ3{111}, Σ5{100}, Σ7{111}, Σ9{411}, Σ11{311}, and R{100}/{411}) containing a helium bubble. Combinations of a variety of conditions are explored including different strain rates, system dimensions, bubble density, bubble radius, bubble pressure, and temperature. We found that in general, grain boundaries absorb less energies with decreasing strain rate but increasing bubble areal density, bubble pressure, bubble radius, and temperature. The propensity of grain boundary delamination is sensitive to grain boundary type: The random grain boundary R{100}/{411} is one of the most brittle boundaries whereas the Σ1{111} cleavage plane and the Σ3{111} twin boundary are two of the toughest boundaries. The sorted list of grain boundary fracture vulnerability obtained from our dynamic tensile test simulations differs from the one obtained from our decohesion energy calculations, confirming the important role of plastic deformation during fracture. Finally, detailed mechanistic analyses are performed to interpret the simulated results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In-Situ Calibrated Modeling of Residual Stresses Induced in Machining under Various Cooling and Lubricating Environments

Although many functional characteristics, such as fatigue life and damage resistance depend on residual stresses, there are currently no industrially viable ‘Digital Process Twin’ models (DPTs) capable of efficiently and quickly predicting machining-induced stresses. By leveraging advances in ultra-high-speed in-situ experimental characterization of machining and finishing processes under plane strain (orthogonal/2D) conditions, we have developed a set of physics-based semi-analytical models to predict residual stress evolution in light of the extreme gradients of stress, strain and temperature, which are unique to these thermo-mechanical processes. Initial validation trials of this novel paradigm were carried out in Ti-6Al4V and AISI 4340 alloy steel. A variety dry, cryogenically cooled and oil lubricated conditions were evaluated to determine the model’s ability to capture the tribological changes induced due to lubrication and cooling. The preliminarily calibrated and validated model exhibited an average correlation of better than 20% between the predicted stresses and experimental data, with calculation times of less than a second. Based on such fast-acting DPTs, the authors envision future capabilities in pro-active surface engineering of advanced structural components (e.g., turbine blades).

36 MATERIALS SCIENCE↗

Finite Element Modeling of Spent Nuclear Fuel in Dry Storage under Seismic Excitation

Spent nuclear fuel (SNF) is currently stored at independent spent fuel storage installations (ISFSIs) at nuclear power plant sites across the US. The US Department of Energy (DOE) Spent Fuel and Waste Science and Technology (SFWST) program is currently working to understand the response of SNF during a seismic event. This investigation is part of a long-term effort by DOE to quantify the external mechanical loads on SNF. The SFWST program has recently completed campaigns evaluating SNF behavior during normal conditions of transport and in 30 cm package drop scenarios; both campaigns included a combination of testing and modeling. Likewise, the investigation into seismic response of SNF will include full-size shake table tests of a vertical storage overpack containing instrumented surrogate fuel assemblies, as well as pre- and post-test finite element modeling. This work focuses on the development of finite element models simulating the planned test configuration. The seismic response is calculated at two scales: at the package level, and at the fuel level. The package level model evaluates the behavior of the storage overpack and its contents in response to the ground motions of a representative earthquake. The motion of the package is input to the fuel level model, which consists of a detailed finite element model of a 17x17 or 16x16 pressurized water reactor (PWR) fuel assembly or of a 10x10 boiling water reactor (BWR) fuel assembly. The stress and strain on individual components such as fuel rods and guide tubes are extracted from this model. This work details the SNF response to various input ground motions, considering representative earthquakes in the Central and Eastern US under various site conditions. Also discussed is the development of a “reduced scope” finite element model of the SNF, which consists of a single fuel rod while retaining the dynamic response of the entire fuel assembly. This reduced scope model addresses the significant computational expense of modeling the SNF under long-duration input ground motions and facilitates simulating additional parameter variations of the model beyond the as-tested configuration. The modeling results provide important insight that will help to inform future testing and modeling efforts by the SFWST program to close the knowledge gap related to external loads on SNF.

Kadooka, Kevin↗

Development of procedures for calculating stiffness and damping of elastomers in engineering applications, part 6

An elastomer damper was designed, tested, and compared with the performance of a hydraulic damper for a power transmission shaft. The six button Viton-70 damper was designed so that the elastomer damper or the hydraulic damper could be activated without upsetting the imbalance condition of the assembly. This permitted a direct comparison of damper effectiveness. The elastomer damper consistently performed better than the hydraulic mount and permitted stable operation of the power transmission shaft to speeds higher than obtained with the squeeze film damper. Tests were performed on shear specimens of Viton-79, Buna-N, EPDM, and Neoprene to determine performance limitations imposed by strain, temperature, and frequency. Frequencies of between 110 Hz and 1100 Hz were surveyed with imposed strains between 0.0005 and 0.08 at temperatures of 32 C, 66 C, and 80 C. A set of design curves was generated in a unified format for each of the elastomer materials.

Rieger, A.↗

Molecular Dynamics Simulation of Hygroscopic Aging Effects in Epoxy Polymer

The automobile industry is incorporating more lightweight content in car designs to boost fuel-economy. New structural adhesives are needed to mitigate the corrosion and thermal expansion issues associated with joining dissimilar lightweight materials, but adhesive developers lack a fundamental understanding of the chemistry that occurs in the adhesive as the joint ages. In this study, we developed structural adhesive molecular models and applied classical molecular dynamics simulations and density functional theory calculations to gain molecular insights into the influence of water molecules on the properties of epoxy-based adhesives (DGEBA + Jeffamine (JD230)). The simulations were complemented by experimental synthesis and characterization. Our work underscores the impact of water molecules on the local structure of the epoxy network as well as resulting mechanical properties. Water molecules were mainly coordinated with hydroxyls, primary amines and secondary amines, but also weakly coordinated with ether linkages, which were found most probable to be labile. Simulated stress–strain data indicates that increasing the water content deteriorates the mechanical properties. The Young’s modulus decreased by ~ 30% when the water content increased to 3 wt%. We conclude, this integration of molecular-level chemical insights with mechanical property simulations of the hydrated epoxy system and experimental validation holds the promise to advance lightweight joint technologies.

36 MATERIALS SCIENCE↗

Low-index mesoscopic surface reconstructions of Au surfaces using Bayesian force fields

Metal surfaces have long been known to reconstruct, significantly influencing their structural and catalytic properties. Many key mechanistic aspects of these subtle transformations remain poorly understood due to limitations of previous simulation approaches. Using active learning of Bayesian machine-learned force fields trained from ab initio calculations, we enable large-scale molecular dynamics simulations to describe the thermodynamics and time evolution of the low-index mesoscopic surface reconstructions of Au (e.g., the Au(111)-‘Herringbone,’ Au(110)-(1 × 2)-‘Missing-Row,’ and Au(100)-‘Quasi-Hexagonal’ reconstructions). This capability yields direct atomistic understanding of the dynamic emergence of these surface states from their initial facets, providing previously inaccessible information such as nucleation kinetics and a complete mechanistic interpretation of reconstruction under the effects of strain and local deviations from the original stoichiometry. We successfully reproduce previous experimental observations of reconstructions on pristine surfaces and provide quantitative predictions of the emergence of spinodal decomposition and localized reconstruction in response to strain at non-ideal stoichiometries. A unified mechanistic explanation is presented of the kinetic and thermodynamic factors driving surface reconstruction. Furthermore, we study surface reconstructions on Au nanoparticles, where characteristic (111) and (100) reconstructions spontaneously appear on a variety of high-symmetry particle morphologies.

36 MATERIALS SCIENCE↗

Strong laser polarization control of coherent phonon excitation in van der Waals material Fe 3 GeTe 2

Optical manipulation of coherent phonon frequency in two-dimensional (2D) materials could advance the development of ultrafast phononics in atomic-thin platforms. However, conventional approaches for such control are limited to doping, strain, structural or thermal engineering. Here, we report the experimental observation of strong laser-polarization control of coherent phonon frequency through time-resolved pump-probe spectroscopic study of van der Waals (vdW) materials Fe 3 GeTe 2 . When the polarization of the pumping laser with tilted incidence is swept between in-plane and out-of-plane orientations, the frequencies of excited phonons can be monotonically tuned by as large as 3% (~100 GHz). Our first-principles calculations suggest the strong planar and vertical inter-atomic interaction asymmetry in layered materials accounts for the observed polarization-dependent phonon frequencies, as in-plane/out-of-plane polarization modifies the restoring force of the lattice vibration differently. Our work provides insightful understanding of the coherent phonon dynamics in layered vdW materials and opens up new avenues to optically manipulating coherent phonons.

36 MATERIALS SCIENCE↗

Optical signal processing of spatially distributed sensor data in smart structures

Smart structures which contain dense two- or three-dimensional arrays of attached or embedded sensor elements inherently require signal multiplexing and processing capabilities to permit good spatial data resolution as well as the adequately short calculation times demanded by real time active feedback actuator drive circuitry. This paper reports the implementation of an in-line optical signal processor and its application in a structural sensing system which incorporates multiple discrete optical fiber sensor elements. The signal processor consists of an array of optical fiber couplers having tailored s-parameters and arranged to allow gray code amplitude scaling of sensor inputs. The use of this signal processor in systems designed to indicate the location of distributed strain and damage in composite materials, as well as to quantitatively characterize that damage, is described. Extension of similar signal processing methods to more complicated smart materials and structures applications are discussed.

Bennett, K. D.↗

Grain boundary slip – twin transmission in titanium

Here, using a combination of mechanical testing, scanning electron microscopy, and a unified crystal plasticity framework for discrete intragranular shear localization, we investigate intense, localized slip bands on prismatic planes and {10$\bar{1}$2} $\langle$$\bar{1}$011$\rangle$ tensile twins, and their transmission across the grain boundaries (GBs) in commercially pure titanium. The analyses show that the orientation and curvature of the GB influence the local stress fields at the GBs, and consequently, the slip/twin transmission across the boundary. In addition to host grain properties, neighboring grain properties, such as active slip systems and instances of heterogeneity like slip bands and twins, heavily affect the deformation mechanisms in each grain. Finally, the applicability of geometric factors to predict the transmission in the experimentally observed co-located pairs is discussed. The local stress field calculated by the discrete slip and twin band model is shown to be capable of determining whether a transmission has occurred in an observed co-located pair, and also the direction of the transmission.

36 MATERIALS SCIENCE↗

Life prediction modeling based on strainrange partitioning

Strainrange partitioning (SRP) is an integrated low-cycle-fatigue life predicting system. It was created specifically for calculating cyclic crack initiation life under severe high-temperature fatigue conditions. The key feature of the SRP system is its recognition of the interacting mechanisms of cyclic inelastic deformation that govern cyclic life at high temperatures. The SRP system bridges the gap between the mechanistic level of understanding that breeds new and better materials and the phenomenological level wherein workable engineering life prediction methods are in great demand. The system was recently expanded to address engineering fatigue problems in the low-strain, long-life, nominally elastic regime. This breakthrough, along with other advances in material behavior and testing technology, has permitted the system to also encompass low-strain thermomechanical loading conditions. Other important refinements of the originally proposed method include procedures for dealing with life-reducing effects of multiaxial loading, ratcheting, mean stresses, nonrepetitive (cumulative loading) loading, and environmental and long-time exposure. Procedure were also developed for partitioning creep and plastic strain and for estimating strainrange versus life relations from tensile and creep rupture properties. Each of the important engineering features of the SRP system are discussed and examples shown of how they help toward predicting high-temperature fatigue life under practical, although complex, loading conditions.

Halford, Gary R.↗

Virtual texture analysis to investigate the deformation mechanisms in metal microstructures at the atomic scale

Understanding the deformation behavior of metallic materials at high strain rates requires the characterization of plasticity contributors such as twins, phase transformed regions, and dislocations. However, predicting the contributions from phase transformation and twinning relies on a complete understanding of the selection of variants for various loading orientations and the evolution of their volume fractions. This manuscript presents a new virtual texture (VirTex) analysis approach to characterize phase transformation and twinning variants in deformed microstructures generated using molecular dynamics (MD) simulations. Furthermore, the VirTex method involves the construction of a rotation matrix to calculate the angle/axis pairs and misorientation angles for each atom in the microstructure. Any changes in the orientation angle from angle/axis pairs and/or structure types are analyzed to determine the nucleation and evolution of variants in the microstructure. The study uses shock deformed single-crystal Fe, Ta, and Cu to analyze the variant selections for phase transformation or twinning or both in BCC and FCC systems. In addition, the VirTex analysis is able to characterize the phase transformation and twinning variants in nanocrystalline Fe and Ta microstructures. Besides characterizing variants, orientation mapping also provides an accelerated and on-the-fly approach for quantifying twin fractions in MD microstructures.

36 MATERIALS SCIENCE↗