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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 361 records · Page 20

Hidden features in the OH-stretching spectra of amino acid decorated air–water interfaces

Chemical reactivity at the air–water interface is governed by the interfacial solvation of reactive species. For instance, during aqueous amino acid-based CO 2 absorption, water reorganizes around the reactive sites and couples dynamically with reaction pathways, facilitating the reaction. In this context, surface-sensitive vibrational sum-frequency generation (vSFG) spectroscopy can probe the OH stretch vibrations of interfacial water and determine the solvation structures around reactants and products, thereby furthering our understanding of the role of interfacial solvation. However, vSFG spectra of the air–water interface in the presence of charged species can be remarkably complex; key species-bound local water structures with distinct orientations may be hidden beneath prominent vSFG peaks arising from water–water hydrogen bonds and remain difficult to resolve. Here, we measure and compute vSFG spectra of the water OH stretch at air–water interfaces decorated with amino acids in their zwitterionic and anionic forms, as well as equimolar mixtures of these forms with bicarbonate. The latter represents post-CO 2 -absorption conditions. We find that computing depth- and frequency-dependent spectral densities—decomposed into contributions from water molecules hydrogen-bonded exclusively to other water molecules, exclusively to amines, exclusively to carboxylates, or shared between these polar/charged groups—is indispensable for accurate interpretation of the vSFG spectra. Key findings include orientational flip-flop in water sub-layers, strong carboxylate-water H-bonding, and water orientational ordering extending into the bulk aqueous phase induced by anionic amino acids. Here, this study provides a computational spectroscopic platform for improved understanding of interfacial solvation relevant to interfacial reactivity.

Air-water interface↗

Development of Lightweight Structural Materials with Improved Properties for Fission Batteries

Fission batteries require lightweight structural materials that demonstrate structural resilience when subjected to repeated shutdown, transportation, startup cycles, and certain external conditions, including rare events such as seismic vibrations and tsunamis. The objectives of this project are (1) to produce lightweight structural materials whose strength-to-weight ratios and fatigue resistance exceed those of current widely used structural materials such as 316 stainless steels (SS316), and (2) to enhance radiation tolerance of structural materials over a suitable service temperature range. To achieve these, (1) a lattice structure will be produced, (2) advanced modeling and simulation tools will be employed to design lattice structures (e.g., a gyroid structure) that reduce stress concentrations and thus increase fatigue resistance, and (3) one-dimensional (1-D) carbon nanotubes will be added to enhance radiation resistance. To validate our solution, high-temperature tensile and fatigue testing, in combination with microstructure characterization, will be conducted on wrought materials, additively manufactured solid materials, and the designed lightweight lattice structure material. Ion irradiation, microstructure characterization, and nanoindentation will be carried out to investigate the effect of 1-D carbon nanotubes on radiation tolerance. Successful completion of this project will deliver a material to serve as a substitute for current SS316 using the same chemistry but with lighter weight and improved mechanical properties. In addition, a material with carbon nanotubes can be designed for improved radiation tolerance over a suitable service temperature range. This project will establish new techniques in innovative materials/lattice design, advanced macroscale properties prediction, and the application of state-of-the-art processes.

36 MATERIALS SCIENCE↗

Benchmarking machine learning interatomic potentials via phonon anharmonicity

Abstract Machine learning approaches have recently emerged as powerful tools to probe structure-property relationships in crystals and molecules. Specifically, machine learning interatomic potentials (MLIPs) can accurately reproduce first-principles data at a cost similar to that of conventional interatomic potential approaches. While MLIPs have been extensively tested across various classes of materials and molecules, a clear characterization of the anharmonic terms encoded in the MLIPs is lacking. Here, we benchmark popular MLIPs using the anharmonic vibrational Hamiltonian of ThO 2 in the fluorite crystal structure, which was constructed from density functional theory (DFT) using our highly accurate and efficient irreducible derivative methods. The anharmonic Hamiltonian was used to generate molecular dynamics (MD) trajectories, which were used to train three classes of MLIPs: Gaussian approximation potentials, artificial neural networks (ANN), and graph neural networks (GNN). The results were assessed by directly comparing phonons and their interactions, as well as phonon linewidths, phonon lineshifts, and thermal conductivity. The models were also trained on a DFT MD dataset, demonstrating good agreement up to fifth-order for the ANN and GNN. Our analysis demonstrates that MLIPs have great potential for accurately characterizing anharmonicity in materials systems at a fraction of the cost of conventional first principles-based approaches.

interatomic potentials↗

Negative and zero thermal expansion in α-(Cu 2-x Znx)V 2 O 7 solid solutions

Negative or zero thermal expansion (NTE or ZTE) of materials is intriguing for controllable thermal expansion. In this work, we report a series of orthorhombic α-Cu 2- x Zn x V 2 O 7 ( x = 0, 0.1, 0.2), in which the volumetric coefficients of thermal expansion are successfully tuned from -10.19 × 10 -6 K -1 to -1.58 × 10 -6 K -1 in the temperature range of 100–475 K by increasing the content of Zn 2+ . It has been revealed that the transverse vibrations of oxygen bonded with vanadium are dominant in the contraction of the bc plane, leading to the overall volume NTE in α-Cu 2 V 2 O 7 . The introduction of Zn 2+ densifies the crystal structure, which is presumed to suppress the space of transverse vibrations and results in the ZTE in α-Cu 1.8 Zn 0.2 V 2 O 7 . This work presents an effective method to realize ZTE in anisotropic framework systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing ab initio emergence of nuclear rotation

Structural phenomena in nuclei, from shell structure and clustering to superfluidity and collective rotations and vibrations, reflect emergent degrees of freedom. Ab initio theory describes nuclei directly from a fully microscopic formulation. We can therefore look to ab initio theory as a means of exploring the emergence of effective degrees of freedom in nuclei. For the illustrative case of emergent rotational bands in the $Be$ isotopes, we establish an understanding of the underlying oscillator space and angular momentum (orbital and spin) structure. We consider no-core configuration interaction (NCCI) calculations for 7, 9, 11 Be with the Daejeon16 internucleon interaction. Although shell model or rotational degrees of freedom are not assumed in the ab initio theory, the NCCI results are suggestive of the emergence of effective shell model degrees of freedom (0$\hbar$ω and 2$\hbar$ω excitations) and LS-scheme rotational degrees of freedom, consistent with an Elliott–Wilsdon SU(3) description. Finally, these results provide some basic insight into the connection between emergent effective collective rotational and shell model degrees of freedom in these light nuclei and the underlying ab initio microscopic description.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Large change of interlayer vibrational coupling with stacking in Mo 1-x W x Te 2

Stacking variations in quasi-two-dimensional materials can have an important influence on material properties, such as changing the topology of the band structure. Unfortunately, the weakness of van der Waals (vdW) interactions makes it difficult to compute the stacking dependence of properties, and even in a material as simple as graphite the stacking energetics remain unclear. Mo 1 - x W x Te 2 is a material in which three differently stacked phases are conveniently accessible by temperature changes: 1 T ' , T d * , and the reported Weyl semimetal phase T d . Additionally, the transitions proceed via layer sliding, and the corresponding interlayer shear mode (ISM) is relevant not just for the stacking energetics but also for understanding the relationship between Weyl physics and structural changes. However, the interlayer interactions of Mo 1 - x W x Te 2 are not well understood, with wide variation in computed properties. We report inelastic neutron scattering of the ISM in a Mo 0.91 W 0.09 Te 2 crystal. The ISM energies are generally consistent with the linear chain model, as expected given the weak interlayer interaction, though there are some discrepancies from predicted intensities. However, the interlayer force constants K x in the T d * and 1 T ' phases are substantially weaker than that of T d at 75(3) and 83(3)%, respectively. Considering that the relative positioning of atoms in neighboring layers is approximately the same regardless of overall stacking, our results suggest that longer-range influences, such as stacking-induced electronic band-structure changes, may be responsible for the substantial change in the interlayer vibrational coupling and thus the C 55 elastic constant. These findings should elucidate the stacking energetics of Mo 1 - x W x Te 2 and other vdW layered materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Direct prediction of inelastic neutron scattering spectra from the crystal structure*

Abstract Inelastic neutron scattering (INS) is a powerful technique to study vibrational dynamics of materials with several unique advantages. However, analysis and interpretation of INS spectra often require advanced modeling that needs specialized computing resources and relevant expertise. This difficulty is compounded by the limited experimental resources available to perform INS measurements. In this work, we develop a machine-learning based predictive framework which is capable of directly predicting both one-dimensional INS spectra and two-dimensional INS spectra with additional momentum resolution. By integrating symmetry-aware neural networks with autoencoders, and using a large scale synthetic INS database, high-dimensional spectral data are compressed into a latent-space representation, and a high-quality spectra prediction is achieved by using only atomic coordinates as input. Our work offers an efficient approach to predict complex multi-dimensional neutron spectra directly from simple input; it allows for improved efficiency in using the limited INS measurement resources, and sheds light on building structure-property relationships in a variety of on-the-fly experimental data analysis scenarios.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A systematic approach to generating accurate neural network potentials: the case of carbon

Abstract Availability of affordable and widely applicable interatomic potentials is the key needed to unlock the riches of modern materials modeling. Artificial neural network-based approaches for generating potentials are promising; however, neural network training requires large amounts of data, sampled adequately from an often unknown potential energy surface. Here we propose a self-consistent approach that is based on crystal structure prediction formalism and is guided by unsupervised data analysis, to construct an accurate, inexpensive, and transferable artificial neural network potential. Using this approach, we construct an interatomic potential for carbon and demonstrate its ability to reproduce first principles results on elastic and vibrational properties for diamond, graphite, and graphene, as well as energy ordering and structural properties of a wide range of crystalline and amorphous phases.

Chemistry↗

Diffusion Monte Carlo approaches for studying nuclear quantum effects in fluxional molecules

Abstract Diffusion quantum Monte Carlo (DMC) provides a powerful approach for obtaining the ground state energy and wave function of molecules, ions, and molecular clusters. The approach is uniquely well suited for studies of fluxional molecules, which undergo large amplitude vibrational motions even in their ground state. In contrast to the electronic structure problem, where the wave function must be antisymmetric with respect to exchange of any pair of electrons, the wave function for the ground vibrational state is nodeless. This greatly simplifies the application of DMC for vibrational problems. Because there is not a single potential function that can be used to describe the intramolecular and intermolecular interactions in all molecular systems, most methods that are used to describe nuclear quantum effects rely on a carefully chosen zero‐order description of the molecular vibrations. In contrast, DMC calculations can be performed in Cartesian coordinates, making the DMC algorithm easily transferable between different chemical systems. In this contribution, the theory that underlies DMC will be discussed along with important considerations for performing DMC calculations. Extensions for evaluating vibrationally excited states and molecular properties are also discussed. Insights that can be obtained from DMC calculations are illustrated in the context of the protonated water clusters. This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Theoretical and Physical Chemistry > Spectroscopy

Chemistry↗

High-Pressure Polymorphism in Silver Ferrite Delafossite, AgFeO 2

The delafossites are a class of layered metal oxides that are notable for being able to exhibit optical trans- parency alongside an in-plane electrical conductivity, making them promising platforms for the development of transparent conductive oxides. Pressure-induced polymorphism offers a direct method for altering the electrical and optical properties in this class, and although the copper delafossites have been studied extensively under pressure, the silver delafossites remain only partially studied. We report two new high-pressure polymorphs of silver ferrite delafossite, AgFeO 2 , that are stabilized above ~6 GPa and ~14 GPa. In situ X-ray diffraction and vibrational spectroscopy measurements are used to examine the structural changes across the two phase transitions. The high-pressure structure between 6–14 GPa is assigned as a monoclinic C2/c structure that is analogous to the high-pressure phase reported for AgGaO 2 . As a result, nuclear resonant forward scattering reveals no change in the spin state or valence state at the Fe 3+ site up to 15.3 GPa.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing the Solvation Shells of Lithium Ions in Glyme-Based Electrolytes

Glymes have been extensively studied as solvents for Li-battery electrolytes, most recently in equimolar mixtures with lithium bis(trifluoromethanesulfonyl)imide (LiTFSI), due to their ability to form stable solvates. However, directly quantifying free and coordinated glyme molecules in the liquid state has been challenging due to several experimental limitations. Here, in this work, new vibrational probes are demonstrated for studying the solvation structures of diglyme and triglyme in LiTFSI electrolytes. These IR probes make use of an amine group to report the solvation state of glymes at salt-to-solvent molar ratios ranging from 1:5 to 1:10. Characterization of the thermodynamic properties of the solvent exchange occurring in the first solvation shell of lithium ions (Li + ) showed an equilibrium constant for these probes close to unity at room temperature. This result demonstrates that the probes exhibit a similar solvation behavior to their glyme analogue. Concentration dependence studies also revealed a lack of significant amounts of contact ion pairs at the studied concentrations. Moreover, the first solvation shell of Li + appears to be formed by two partially chelating glyme molecules, establishing that even triglyme with multiple chelation sites does not fully coordinate the cation. Complementary molecular dynamics (MD) simulations agree with the experimental results and suggest that at these concentrations, TFSI – predominantly forms solvent-separated ion pairs. However, the simulations do not properly capture the partial solvation structure of the glyme molecules in the solvation shell of Li + as derived from the experiments.

electrolytes↗

Structure and Dynamics of Water Confined in Transition Metal Carbide MXenes: Implications for Electrochemical Applications

Two-dimensional transition metal carbides and nitrides (MXenes) are an important family of electrochemically active 2D materials. MXenes combine high conductivity with hydrophilicity, making them attractive materials for many applications, including electrochemical energy storage, sensing, desalination, and others. In order to better understand the role of structure on MXene properties, here, we investigated the vibrational properties and diffusion of water in MXenes with differing layer thicknesses and transition metal compositions using inelastic, quasi-elastic, and small-angle neutron scattering. We found that all of the Mo-containing MXenes studied here exhibited comparable vibrational dynamics and diffusion coefficients to each other and to previously studied Ti 3 C 2 T x . However, Ti 2 CT x was distinguished by its faster diffusion and more hydroxyl groups compared to the other MXenes studied. These results can help guide the selection of appropriate MXenes for energy storage and electrochemical water purification applications.

MXenes↗

Parity-doublet coherence times in optically trapped polyatomic molecules

Polyatomic molecules provide complex internal structures that are ideal for applications in quantum information science, quantum simulation and precision searches for physics beyond the standard model. A key feature of polyatomic molecules is the presence of parity-doublet states. These structures, which generically arise from the rotational and vibrational degrees of freedom afforded by polyatomic molecules, are a powerful feature to pursue diverse quantum science applications. Linear triatomic molecules contain ℓ-type parity-doublet states in the vibrational bending mode, which are predicted to exhibit robust coherence properties. Here we report optically trapped CaOH molecules prepared in ℓ-type parity-doublet states and realize a bare qubit coherence time of $T$$^{*}_{2}$, which is longer than the 0.36 s lifetime of the bending mode. We suppress differential Stark shifts by cancelling ambient electric fields using molecular spectroscopy and characterize parity-dependent trap shifts, which are found to limit the coherence time. Furthermore, the parity-doublet coherence times achieved in this work are a defining milestone for the use of polyatomic molecules in quantum science.

Quantum information↗

Femtosecond stimulated Raman spectro-microscopy for probing chemical reaction dynamics in solid-state materials

Femtosecond stimulated Raman spectroscopy (FSRS) is a chemically specific vibrational technique that has the ability to follow structural dynamics during photoinduced processes such as charge transfer on the ultrafast timescale. FSRS has a strong background in following structural dynamics and elucidating chemical mechanisms; however, its use with solid-state materials has been limited. As photovoltaic and electronic devices rely on solid-state materials, having the ability to track the evolving dynamics during their charge transfer and transport processes is crucial. Following the structural dynamics in these solid-state materials will lead to the identification of specific chemical structures responsible for various photoinduced charge transfer reactions, leading to a greater understanding of the structure–function relationships needed to improve upon current technologies. Furthermore, isolating the specific nuclear motions and molecular structures that drive a desired physical process will provide a chemical blueprint, leading to the rational design and fabrication of efficient electronic and photovoltaic devices. In this perspective, we discuss technical challenges and experimental developments that have facilitated the use of FSRS with solid-state samples, explore previous studies that have identified structure–function relationships in charge transfer reactions, and analyze the future developments that will broaden and advance the field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Order-disorder versus displacive transitions in Jahn-Teller active layered materials

Large anharmonic vibrations often play a crucial role in dynamically stabilizing crystalline phases whose structures are unstable at low temperature. Although the average structure of such phases can be measured through diffraction experiments, their local structure remains a challenge to characterize and understand. Dynamically stabilized phases are often classified as order/disorder or displacive based on the qualitative nature of their local structure. A robust understanding of how chemistry determines this distinction in behavior, however, is lacking. This article presents a parametric study of an anharmonic vibrational model that describes the transition from a cooperative to a noncooperative Jahn-Teller distortion in layered oxides—a class of materials widely used in Li-ion and Na-ion batteries. The results illustrate how the shape of the energy landscape determines the extent to which the high-temperature phase has order/disorder vs displacive character. In this work, we find that the nature of the high-temperature phase is determined by a competition between the strength of the elastic coupling between Jahn-Teller distortions at nearby sites and the energy scale driving the Jahn-Teller distortion. A comparison of the model to energy landscapes calculated with density-functional theory suggests that the high-temperature phases of the Jahn-Teller active layered compounds LiNiO 2 , NaNiO 2 , LiMnO 2 , and NaMnO 2 exhibit order/disorder character.

36 MATERIALS SCIENCE↗

Magnetic Gears: The Key to Robust, Cost-Effective Hydropower Drivetrains

Based on previous demonstrated success at fabricating 5 and 10 kW scale magnetic gearbox (MGB) prototypes, Emrgy and its partners (the project team) proposed to design and construct a 100 kW scale MGB with a 30:1 gear ratio for the low-head hydro applications. The Statement of Project Objectives included tasks covering: 1) Market Applicability; 2) Technical Metrics; 3) Design (initial); 4) Electromagnetic (EM) Load and Structural Analysis; 5) Modal Analysis; 6) Sealing Design and 7) Final Design during Budget Period 1. Budget Period 2 included tasks covering: 1) Materials Procurement and Test Plan Development; 2) Assembly; and 3) Testing. The Market Applicability study (Task 1) led to a clear conclusion and recommendation toward “Low Head” technologies for maximum market share of both New Stream Reach development as well as powering Non-Powered Dams. The findings of this study also identified the opportunity for a larger scale magnetic gearbox-based drive train as a function of increased torque, as opposed to increased speed. The Technical Metrics Study (Task 2) concluded a horizontal orientation was preferred, examined potential loss mechanisms, concluded that a Halbach Array magnetic design was preferred, established a 30:1 gear ratio as optimal, and established a power rating of 100 kW as optimal. The subsequent initial and final detailed design process included electro-magnetic (EM) load and structural analysis (Task 4), a Modal analysis (for vibration) (Task 5), and a sealing design (Task 6) to assure water impermeability. The final design package (Task 7) included 729 individual parts, 117 unique part numbers, and 15 assemblies. In order to facilitate procurement, the full bill of materials was broken down into several sub-components: 1) custom magnetic parts; 2) custom machined parts; 3) custom casted parts; and 4) commercial off the shelf (COTS) parts. The casted parts were fabricated by Oak Ridge National Laboratory (ORNL) via a Cooperative Research and Development Agreement (CRADA) with Emrgy and funded by the Advanced Manufacturing Office (AMO). The procurement effort (Task 8) ultimately covered three time periods based on challenges encountered in meeting the budgeted cost for the prototype. Following the first effort in the early stages of Budget Period 2 in 2017, a no-cost time extension was granted to seek alternative fabrication and procurement options. The project was re-booted in 2020 based on the new ORNL CRADA that would focus on five (5) of the more difficult and expensive parts using their advanced manufacturing expertise. Procurement efforts for the other custom machined parts resulted in quotations that still exceeded the budget by more than $\$$100k. This was, in part, also due to the concurrent COVID-19 pandemic that caused both supply chain disruptions and labor shortages. As the project continued, pricing and availability degraded further. In Q2 FY’22, it was decided to not proceed with the fabrication of the prototype (Task 9) based on budgetary limitations. Outcomes included a full and detailed design of a 100 kW magnetic gearbox and associated indented bill of materials (BOM) and CAD drawings, a full assembly instruction manual with an associated BOM for materials necessary to support assembly, the fabrication of the double Halbach magnetic array for the rotor/stator system, fabrication of five (5) sand-casted/machined parts (via CRADA with ORNL) and an initial draft of a comprehensive testing plan. The most significant non-outcome was the actual fabrication and testing of the prototype gearbox based on budget limitations. Lessons learned included the need for an Application / Design / Cost trade analysis to better elucidate the cost potential of the MGB in the projected volumes anticipated for future demand. This would better establish the efficacy of the original cost target ($\$$0.80/Watt) and/or the need for reconsideration of designs and applications. Likewise, additional consideration of the prototype nature of the gearbox – single use, short lifetime, etc. - either as a separate exercise or in place of the design process completed, to reduce the cost of the demonstration prototype device. Additionally, project continuity was cited as a significant risk based on the loss of the primary design engineering firm after Budget Period 1. A design analysis exercise was conducted at the conclusion of the project to identify potential areas for cost reduction. One concept considered was the removal of the inner ring of magnets (with associated changes in the outer ring magnets) to enable a horizontal collapse of the design. It was estimated this could reduce cost by 10-25% without impacting performance.

13 HYDRO ENERGY↗

Bridging the time scale in exascale computing of chemical systems (Final Technical Report)

This report summarizes the work carried out with support of the United States Department of Energy under Award DE-SC0019441. The theme of this project was to develop and apply methods that allowed for the acceleration of atomistic calculations, particularly in challenging areas such as multiphase systems, electrified interfaces, uncertainty estimation, and applications requiring chemical accuracy, which tend to be applications where simulation time is severely bottlenecked by the computational time requirements. Much of the focus was on the application of emerging machine-learning methodologies, although a wide range of methodologies were employed. This report has two major sections. The first focuses on the methodological advances themselves. Within this part, we report a number of major advances, a few examples of which are described here. We report the first machine-learning scheme for the acceleration of electronically grand-canonical calculations (that is, those applicable to electrochemistry). We report new methods of performing transfer learning, in which physics-based priors can be used to provide predictions, often with uncertainty estimates, of images well outside of training sets; we also offer ways to fine-tune these transfer-learning models. We provide a new systematic means to generate and apply minimal training data sets to very large (10,000’s of atoms) systems, with only small training sets appropriate for electronic structure. We developed new methodologies to integrate surface vibrations into surface adsorption calculations. We made advances to the applicability of diffusion Monte Carlo methods to allow (learned) force prediction, finite-size error correction, and force-free means of searching for transition states. We integrated machine-learned atomistic predictions into mechanism generation codes. Additionally, we released new software including AmpTorch, a modernized version of our original atomistic machine-learning code Amp. The second part of this report focuses on the scientific applications that accompanied, and were often enabled by, the methodological advances described earlier. A few examples follow, but full details are in the individual chapters of the report. For example, we developed a general theory of phonon-induced friction on molecular adsorbates. We showed fundamentally how solvent influences the adsorption and desorption process and how it differs from the processes typically involved at the solid–gas interface, making aqueous-phase and electrocatalysis different from traditional thermocatalysis. We examined how metal–insulator and magnetic transitions can be probed, and accelerated exciton dynamics via Frenkel Hamiltonian parameters. We showed that the nearsighted force-training approach, developed within this project, can predict both the stability and reactivity of large nanoparticles, and can also lead to insights on catalyst coverage on binding energies and entropies. These applied studies, which generally integrated with our method development, allowed us to push forward the theoretical understanding of several reaction classes.

08 HYDROGEN↗

High-pressure response of vibrational properties of b-As x P 1– x : in situ Raman studies

The structural evolution of black arsenic-phosphorous (b-As x P 1–x ) alloys with varying arsenic concentrations was investigated under hydrostatic pressure using in situ Raman spectroscopy. High-pressure experiments were conducted using a diamond anvil cell, which revealed pressure-induced shifts in vibrational modes associated with P–P bonds (A 1 g , A 2 g , ${B}_{2g}$), As–As bonds (A 1 g , A 2 g , ${{B}}_{2g}$), and As–P bonds in b-As x P 1–x alloys. Two distinct pressure regimes were observed. In the first regime (region I), all vibrational modes exhibited a monotonic upshift, indicating phonon hardening due to hydrostatic pressure. In the second regime (region II), As 0.4 P 0.6 and As 0.6 P 0.4 alloys displayed a linear blueshift (or negligible change in some modes) at a reduced rate, suggesting local structural reorganization with less compression on the bonds. Notably, the alloy with the highest As concentration, As 0.8 P 0.2 , exhibited anomalous behavior in the second pressure regime, with a downward shift observed in all As–As and As–P Raman modes (and some P–P modes). Interestingly, the emergence of new peaks corresponding to the E g mode and A 1g mode of the gray-As phase was observed in this pressure range, indicating compressive strain-induced structural changes. The anomalous change in region II confirms the formation of a new local structure, characterized by elongation of the P–P, As–As, and As–P bonds along the zigzag direction within the b-As x P 1–x phase, possibly near the grain boundary. Additionally, a gray-As phase undergoes compressive structural changes. This study underscores the significance of pressure in inducing structural transformations and exploring novel phases in two-dimensional materials, including b-As x P 1–x alloys.

36 MATERIALS SCIENCE↗