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We respond to David Steigmann's discussion of our paper "A general theory for anisotropic Kirchhoff-Love shells with in-plane bending of embedded fibers, Math. Mech. Solids, 28(5):1274-1317" (arXiv:2101.03122). His discussion allows us to clarify two misleading statements in our original paper, and confirm that its formulation is fully consistent with the formulation of Steigmann. We also demonstrate that some of our original statements criticized by Steigmann are not wrong., Comment: 7 pages, 1 figure

Traditional design cycles for new materials and assemblies have two fundamental drawbacks. The underlying physical relationships are often too complex to be precisely calculated and described. Aside from that, many unknown uncertainties, such as exact manufacturing parameters or materials composition, dominate the real assembly behavior. Machine learning (ML) methods overcome these fundamental limitations through data-driven learning. In addition, modern approaches can specifically increase system knowledge. Representation Learning allows the physical, and if necessary, even symbolic interpretation of the learned solution. In this way, the most complex physical relationships can be considered and quickly described. Furthermore, generative ML approaches can synthesize possible morphologies of the materials based on defined conditions to visualize the effects of uncertainties. This modern approach accelerates the design process for new materials and enables the prediction and interpretation of realistic materials behavior., Comment: This paper has been accepted for publication at the AAAI 2024 Workshop on AI to Accelerate Science and Engineering

The state-of-the-art in paper mechanics calls for novel experimental data covering the full-field hygro-expansion of inter-fiber bonds in paper, i.e., the 3D morphological changes and inter-fiber interactions. Therefore, a recently developed full-field single fiber hygro-expansion measurement methodology based on global digital height correlation is extended to orthogonally bonded inter-fiber bonds, to investigate their full-field quasi-3D hygroscopic behavior. A sample holder has been developed which enables the quasi-3D characterization of the initial geometry of individual inter-fiber bonds, including the fiber thickness and width along the length of the fibers as well as the degree of wrap around and contact area of the bond, which are vital for understanding the inter-fiber bond hygro-mechanics. Full-field hygroscopic testing revealed novel insights on the inter-fiber interactions: (i) the transverse hygro-expansion of each fiber strongly reduces when approaching the bonded area, due to the significantly lower longitudinal hygro-expansion of the other bonded fiber. (ii) The relatively large transverse strain of one fiber stretches the other crossing fiber in its longitudinal direction, thereby significantly contributing to the sheet scale hygro-expansion. (iii) Out-of-plane bending is observed in the bonded region which is driven by the significant difference in transverse and longitudinal hygro-expansion of, respectively, the top and bottom fiber constituting the bond. A bi-layer laminate model is derived to rationalize the bending deformation and an adequate match is found with the experimental data. Under the assumption of zero bending, which represents constrained inter-fiber bonds inside a paper sheet, the model is able to predict the contribution of the transverse strain in the bonded regions to the sheet-scale hygro-expansion., Comment: 30 pages, 8 figures, 4 tables

There has been a growing effort to replace manual extraction of data from research papers with automated data extraction based on natural language processing, language models, and recently, large language models (LLMs). Although these methods enable efficient extraction of data from large sets of research papers, they require a significant amount of up-front effort, expertise, and coding. In this work we propose the ChatExtract method that can fully automate very accurate data extraction with minimal initial effort and background, using an advanced conversational LLM. ChatExtract consists of a set of engineered prompts applied to a conversational LLM that both identify sentences with data, extract that data, and assure the data's correctness through a series of follow-up questions. These follow-up questions largely overcome known issues with LLMs providing factually inaccurate responses. ChatExtract can be applied with any conversational LLMs and yields very high quality data extraction. In tests on materials data we find precision and recall both close to 90% from the best conversational LLMs, like ChatGPT-4. We demonstrate that the exceptional performance is enabled by the information retention in a conversational model combined with purposeful redundancy and introducing uncertainty through follow-up prompts. These results suggest that approaches similar to ChatExtract, due to their simplicity, transferability, and accuracy are likely to become powerful tools for data extraction in the near future. Finally, databases for critical cooling rates of metallic glasses and yield strengths of high entropy alloys are developed using ChatExtract., Comment: 7 pages, 3 figures, 1 table

Earlier works in literature on the hygro-expansion of paper state that the larger hygro-expansivity of freely compared to restrained dried handsheets is due to structural differences between the fibers inside the handsheet. To unravel this hypothesis, first, the hygro-expansion of freely and restrained dried, hardwood and softwood handsheets has been characterized. Subsequently, the transient full-field hygro-expansion (longitudinal, transverse, and shear strain) of fibers extracted from these handsheets was measured using global digital height correlation, from which the micro-fibril angle was deduced. The hygro-expansivity of each individual fiber was tested before and after a wetting period, during which the fiber's moisture content is maximized, to analyze if a restrained dried fiber can "transform" into a freely dried fiber. It was found that the longitudinal hygro-expansion of the freely dried fibers is significantly larger than the restrained dried fibers, consistent with the sheet-scale differences. The difference in micro-fibril angle between the freely and restrained dried fibers is a possible explanation for this difference, but merely for the hardwood fibers, which are able to "transform" to freely dried fibers after being soaked in water. In contrast, this "transformation" does not happen in softwood fibers, even after full immersion in water for a day. Various mechanisms have been studied to explain the observations on freely and restrained dried hardwood and softwood, fiber and handsheets including analysis of the fibers' lumen and cross-sectional shape. The presented results and discussion deepens the understanding of the differences between freely and restrained dried handsheets., Comment: 43 pages, 15 figures, 2 tables

Quasi-brittle materials endowed with (statistically) self-similar hierarcical microstructures show distinct failure patterns that deviate from the standard scenario of damage accumulation followed by crack nucleation-and-growth. Here we study the failure of paper sheets with hierarchical slice patterns as well as non-hierarchical and unpatterned reference samples, considering both uncracked samples and samples containing a macroscopic crack. Failure is studied under displacement-controlled tensile loading as well as under creep conditions. Acoustic emission records and surface strain patterns are recorded alongside stress-strain and creep curves. The measurements demonstrate that hierarchical patterning efficiently mitigates against strain localization and crack propagation. In tensile loading, this results in a significantly increased residual strength of cracked samples. Under creep conditions, for a given range of lifetimes hierarchically patterned samples are found to sustain larger creep strains at higher stress levels; their creep curves show unusual behavior characterized by multiple creep rate minima due to the repeated arrest of emergent localization bands.

The transient dimensional changes during \textit{hygro}-expansion and \textit{hydro}-expansion of freely and restrained dried, softwood and hardwood sheets and fibers is monitored, to unravel the governing micro-mechanisms occurring during gradual water saturation. The response of individual fibers is measured using a full-field global digital height correlation method, which has been extended to monitor the transient \textit{hydro}-expansion of fibers from dry to fully saturated. The \textit{hygro}- and \textit{hydro}-expansion is larger for freely versus restrained dried and softwood versus hardwood handsheets. The transient sheet-scale \textit{hydro}-expansion reveals a sudden strain and moisture content step. It is postulated that the driving mechanism is the moisture-induced softening of the so-called "dislocated regions" in the fiber's cellulose micro-fibrils, unlocking further fiber swelling. The strain step is negligible for restrained dried handsheets, which is attributed to the "dislocated cellulose regions" being locked in their stretched configuration during restrained drying, which is supported by the single fiber \textit{hydro}-expansion measurements. Finally, an inter-fiber bond model is exploited and adapted to predict the sheet-scale \textit{hygro}-expansion from the fiber level characteristics. The model correctly predicts the qualitative differences between freely versus restrained dried and softwood versus hardwood handsheets, yet, its simplified geometry does not allow for more quantitative predictions of the sheet-scale \textit{hydro}-expansion., Comment: 37 pages; 12 figures; 5 tables

Paper offers a low-cost and widely available substrate for electronics. It posses alternative characteristics to silicon, as it shows low density and high-flexibility, together with biodegradability. Solution processable materials, such as hybrid perovskites, also present light and flexible features, together with a huge tunability of the material composition with varying optical properties. In this study, we combine paper substrates with halide-mixed perovskites for the creation of low-cost and easy-to-fabricate perovskite-on-paper photodetectors with a broadband-tunable spectral response. From the bandgap tunability of halide-mixed perovskites we create photodetectors with a cut-off spectral onset that ranges from the NIR to the green, by increasing the bromide content on MAPb(I$_{1-x}$Br$_x$)$_3$ perovskite alloys. The devices show a fast and efficient response. The best performances are observed for the pure I and Br perovskite compositions, with a maximum responsivity of 376 mA/W on the MAPbBr$_3$ device. This study provides an example of the wide range of possibilities that the combination of solution processable materials with paper substrates offer for the development of low-cost, biodegradable and easy-to-fabricate devices., Comment: 3 main text figures, 8 supp info figures

We investigate a prototype application for machine-readable literature. The program is called "pyDataRecognition" and serves as an example of a data-driven literature search, where the literature search query is an experimental data-set provided by the user. The user uploads a powder pattern together with the radiation wavelength. The program compares the user data to a database of existing powder patterns associated with published papers and produces a rank ordered according to their similarity score. The program returns the digital object identifier (doi) and full reference of top ranked papers together with a stack plot of the user data alongside the top five database entries. The paper describes the approach and explores successes and challenges., Comment: 27 pages, 4 figures

Direct detection experiments for light (sub-GeV) dark matter are making enormous leaps in reaching previously unexplored theory space. The need for accurate characterizations of target responses has led to a growing interplay between particle and condensed matter physics. This white paper summarizes recent progress on direct detection calculations that utilize state-of-the-art numerical tools in condensed matter physics and effective field theory techniques. These new results provide the theoretical framework for interpreting ongoing and planned experiments using electronic and collective excitations, and for optimizing future searches., Comment: contribution to Snowmass 2021; 11 pages, 3 figures

Plasmonic modes offer the potential to achieve PetaVolts per meter fields, that would transform the current paradigm in collider development in addition to non-collider searches in fundamental physics. PetaVolts per meter plasmonics relies on collective oscillations of the free electron Fermi gas inherent in the conduction band of materials that have a suitable combination of constituent atoms and ionic lattice structure. As the conduction band free electron density, at equilibrium, can be as high as $\rm 10^{24}cm^{-3}$, electromagnetic fields of the order of $\rm 0.1 \sqrt{\rm n_0(10^{24}cm^{-3})} ~ PVm^{-1}$ can be sustained by plasmonic modes. Engineered materials not only allow highly tunable material properties but quite critically make it possible to overcome disruptive instabilities that dominate the interactions in bulk media. Due to rapid shielding by the free electron Fermi gas, dielectric effects are strongly suppressed. Because the ionic lattice, the corresponding electronic energy bands and the free electron gas are governed by quantum mechanical effects, comparisons with plasmas are merely notional. Based on this framework, it is critical to address various challenges that underlie PetaVolts per meter plasmonics including stable excitation of plasmonic modes while accounting for their effects on the ionic lattice and the electronic energy band structure over femtosecond timescales. We summarize the ongoing theoretical and experimental efforts as well as map out strategies for the future. Extreme plasmonic fields can shape the future by not only bringing tens of TeV to multi-PeV center-of-mass-energies within reach but also by opening novel pathways in non-collider HEP. In view of this promise, we invite the scientific community to help realize the immense potential of PV/m plasmonics and call for significant expansion of the US and international R\&D program., Comment: contribution to Snowmass 2021

Paper holds the promise to replace silicon substrates in applications like internet of things or disposable electronics that require ultra-low-cost electronic components and an environmentally friendly electronic waste management. In the last years, spurred by the abovementioned properties of paper as a substrate and the exceptional electronic, mechanical and optical properties of van der Waals (vdW) materials, many research groups have worked towards the integration of vdW materials-based devices on paper. Recently, a method to deposit a continuous film of densely packed interconnects of vdW materials on paper by simply rubbing the vdW crystals against the rough surface of paper has been presented. This method utilizes the weak interlayer vdW interactions and allows cleaving of the crystals into micro platelets through the abrasion against the paper. Here, we aim to illustrate the general character and the potential of this technique by fabricating films of 39 different vdW materials (including superconductors, semi-metals, semiconductors, and insulators) on standard copier paper. We have thoroughly characterized their optical properties showing their high optical quality: one can easily resolve the absorption band edge of semiconducting vdW materials and even the excitonic features present in some vdW materials with high exciton binding energy. We also measured the electrical resistivity for several vdW materials films on paper finding exceptionally low values, which are in some cases, orders of magnitude lower than those reported for analogous films produced by inkjet printing. We finally demonstrate the fabrication of field-effect devices with vdW materials on paper using the paper substrate as an ionic gate., Comment: 4 figures in main text, 21 figures in Supp. Info

Paper has the potential to dramatically reduce the cost of electronic components. In fact, paper is 10 000 times cheaper than crystalline silicon, motivating the research to integrate electronic materials on paper substrates. Among the different electronic materials, van der Waals materials are attracting the interest of the scientific community working on paper-based electronics because of the combination of high electrical performance and mechanical flexibility. Up to now, different methods have been developed to pattern conducting, semiconducting and insulating van der Waals materials on paper but the integration of superconductors remains elusive. Here, the deposition of NbSe2, an illustrative van der Waals superconductor, on standard copy paper is demonstrated. The deposited NbSe2 films on paper display superconducting properties (e.g. observation of Meissner effect and resistance drop to zero-resistance state when cooled down below its critical temperature) similar to those of bulk NbSe2., Comment: 6 figures in main text, 8 figures in Supp. Info

Using density functional theory, we carried out systematic calculations for a series of ultrathin iron layers with thicknesses ranging from one atomic monolayer to eleven monolayers (up to about 1.5 nm). We considered three cases: (1) iron layers both on a gold substrate and coated with gold, (2) iron layers on a gold substrate but without coverage, and (3) freestanding iron layers adjacent to a vacuum. For our models, we chose initial bcc Fe(001) surfaces and fcc Au(001) substrates. Based on the calculations, we determined the details of the geometry and magnetic properties of the systems. We calculate lattice parameters, magnetic moments, Curie temperatures and magnetocrystalline anisotropy energies. From the thickness dependence, we determined the volume and surface contributions to the magnetic anisotropy constant. The further analysis allowed us to determine the thickness ranges of the occurrence of perpendicular magnetic anisotropy, as well as the effect of thickness and the presence of a substrate and cap layer on the direction of the magnetization easy axis., Comment: Conference: 2023 IEEE International Magnetic Conference - Short Papers (INTERMAG Short Papers), Sendai, Japan, 2023

The advent of natural language processing and large language models (LLMs) has revolutionized the extraction of data from unstructured scholarly papers. However, ensuring data trustworthiness remains a significant challenge. In this paper, we introduce PropertyExtractor, an open-source tool that leverages advanced conversational LLMs like Google Gemini-Pro and OpenAI GPT-4, blends zero-shot with few-shot in-context learning, and employs engineered prompts for the dynamic refinement of structured information hierarchies, enabling autonomous, efficient, scalable, and accurate identification, extraction, and verification of material property data. Our tests on material data demonstrate precision and recall exceeding 93% with an error rate of approximately 10%, highlighting the effectiveness and versatility of the toolkit. We apply PropertyExtractor to generate a database of 2D material thicknesses, a critical parameter for device integration. The rapid evolution of the field has outpaced both experimental measurements and computational methods, creating a significant data gap. Our work addresses this gap and showcases the potential of PropertyExtractor as a reliable and efficient tool for the autonomous generation of diverse material property databases, advancing the field.

In this paper, a synergistic computational/experimental approach is presented for the rapid discovery and characterization of novel alloys within the compositionally complex (i.e., "medium/high entropy") refractory alloy space of Ti-V-Nb-Mo-Hf-Ta-W. This was demonstrated via a material design cycle aimed at simultaneously maximizing the objective properties of high specific hardness (hardness normalized by density) and high specific elastic modulus (elastic modulus normalized by density). This framework utilizes high-throughput computational thermodynamics and intelligent filtering to first reduce the untenably large alloy space to a feasible size, followed by an iterative design cycle comprised of high-throughput synthesis, processing, and characterization in batch sizes of 24 alloys. After the first iteration, Bayesian optimization was utilized to inform selection of the next batch of 24 alloys. This paper demonstrates the benefit of using batch Bayesian optimization (BBO) in material design, as significant gains in the objective properties were observed after only two iterations or "shots" of the design cycle without using any prior knowledge or physical models of how the objective properties relate to the design inputs (i.e., composition). Specifically, the hypervolume of the Pareto front increased by 54% between the first and second iterations. Furthermore, 10 of the 24 alloys in the second iteration dominated all alloys from the first iteration.

Experimental design techniques such as active search and Bayesian optimization are widely used in the natural sciences for data collection and discovery. However, existing techniques tend to favor exploitation over exploration of the search space, which causes them to get stuck in local optima. This ``collapse" problem prevents experimental design algorithms from yielding diverse high-quality data. In this paper, we extend the Vendi scores -- a family of interpretable similarity-based diversity metrics -- to account for quality. We then leverage these quality-weighted Vendi scores to tackle experimental design problems across various applications, including drug discovery, materials discovery, and reinforcement learning. We found that quality-weighted Vendi scores allow us to construct policies for experimental design that flexibly balance quality and diversity, and ultimately assemble rich and diverse sets of high-performing data points. Our algorithms led to a 70%-170% increase in the number of effective discoveries compared to baselines., Comment: Published in International Conference on Machine Learning, ICML 2024. Code can be found in the Vertaix GitHub: https://github.com/vertaix/Quality-Weighted-Vendi-Score. Paper dedicated to Kwame Nkrumah

Crystal structures are characterized by atomic bases within a primitive unit cell that repeats along a regular lattice throughout 3D space. The periodic and infinite nature of crystals poses unique challenges for geometric graph representation learning. Specifically, constructing graphs that effectively capture the complete geometric information of crystals and handle chiral crystals remains an unsolved and challenging problem. In this paper, we introduce a novel approach that utilizes the periodic patterns of unit cells to establish the lattice-based representation for each atom, enabling efficient and expressive graph representations of crystals. Furthermore, we propose ComFormer, a SE(3) transformer designed specifically for crystalline materials. ComFormer includes two variants; namely, iComFormer that employs invariant geometric descriptors of Euclidean distances and angles, and eComFormer that utilizes equivariant vector representations. Experimental results demonstrate the state-of-the-art predictive accuracy of ComFormer variants on various tasks across three widely-used crystal benchmarks. Our code is publicly available as part of the AIRS library (https://github.com/divelab/AIRS)., Comment: This paper has been accepted by ICLR 2024

In this paper, we theoretically analyse wave propagation in two canonical problems of interest: fluid-filled thermo-visco-elastic slits and fluid-loaded thermo-visco-elastic plates. We show that these two configurations can be studied via the same pair of dispersion equations with the aid of the framework developed in [https://doi.org/10.1098/rspa.2022.0193], which incoporates thermal effects. These two problems are further interrelated, since in the short wavelength limit (relative to the slit/plate width) the respective modes are governed by the same dispersion equation, commonly known as the Scholte--Stoneley equation. It is the Scholte-type modes that are mainly analyzed in this paper. We illustrate results when the fluid is water, although the theory is valid for any Newtonian fluid. Both `hard' and `soft' solids are compared, with the emphasis being placed on the importance of thermo-viscoelastic effects, particularly when stress relaxation is considered. Two main recent works are discussed extensively, namely [https://doi.org/10.1121/1.5078528] for slits and [https://doi.org/10.1103/PhysRevE.103.063002] for loaded plates, both of which do not incorporate viscoelastic mechanisms. We show how the consideration of viscoelasticity can extend the results discussed therein, and explain the circumstances under which they arise.

This paper introduces the HEX (High-pressure Elemental Xstals) database, a complete database of the ground-state crystal structures of the first 57 elements of the periodic table, from H to La, at 0, 100, 200 and 300 GPa. HEX aims to provide a unified reference for high-pressure research, by compiling all available experimental information on elements at high pressure, and complementing it with the results of accurate evolutionary crystal structure prediction runs based on Density Functional Theory. Besides offering a much-needed reference, our work also serves as a benchmark of the accuracy of current ab-initio methods for crystal structure prediction. We find that, in 98 % of the cases in which experimental information is available, ab-initio crystal structure prediction yields structures which either coincide or are degenerate in enthalpy to within 300 K with experimental ones. The main manuscript contains synthetic tables and figures, while the Crystallographic Information File (cif) for all structures will be available on a figshare online repository when the paper will be published., Comment: 22 pages, 3 figures, 10 tables

The efforts of this Note are aimed at understanding various phenomena in digital space that are incomplete and difficult to define, and to translate them into language from research fields that are based on existing large-scale experimental data. Information diffusion and user behavior patterns in digital space are often hard to intuitively capture, and the principles and mechanisms behind them are difficult to articulate. To address this challenge, we have drawn on first-principles methods in physics, particularly solid state physics. This approach is known to be effective in analyzing the behavior of real physical materials at the atomic level and in understanding the electronic properties and bonding structures of materials. We have attempted to apply physical concepts based on first-principles calculations, in particular concepts such as first Brillouin zones, band gaps, and reciprocal lattice vectors, to digital space as a metaphor. This theoretical framework allows us to quantitatively and logically infer the behavior and trends of incomplete and ambiguous digital data and phenomena. For example, the "first Brillouin zone" of information in digital media indicates the potential sphere of influence of that information, and the band gap defines the threshold of influence for the information to be widely accepted. In addition, the reciprocal lattice vector serves as a boundary that indicates the limits of information characteristics and is an indicator of the degree to which a particular piece of information resonates with users. With this theoretical supplement, our research goes beyond the mere analysis of phenomena in the digital space and provides new methods for understanding and predicting the behavior of imperfect data and uncertain digital media., Comment: There are significant errors in the graphs of the simulations in the Brillouin Zone paper, and there are a number of incorrect graphs, so I would like to withdraw and resubmit the paper. The author and others in the experimental physics field have pointed out that we need to verify the calculations again

Large Language Models (LLMs) have garnered considerable interest due to their impressive natural language capabilities, which in conjunction with various emergent properties make them versatile tools in workflows ranging from complex code generation to heuristic finding for combinatorial problems. In this paper we offer a perspective on their applicability to materials science research, arguing their ability to handle ambiguous requirements across a range of tasks and disciplines mean they could be a powerful tool to aid researchers. We qualitatively examine basic LLM theory, connecting it to relevant properties and techniques in the literature before providing two case studies that demonstrate their use in task automation and knowledge extraction at-scale. At their current stage of development, we argue LLMs should be viewed less as oracles of novel insight, and more as tireless workers that can accelerate and unify exploration across domains. It is our hope that this paper can familiarise material science researchers with the concepts needed to leverage these tools in their own research.

Decades ago, Gurzhi proposed that if momentum-conserving collisions prevail among heat-carrying phonons in insulators and charge-carrying electrons in metals, hydrodynamic features will become detectable. In this paper, we will review the experimental evidence emerging in the last few years supporting this viewpoint and raising new questions. The focus of the paper will be bulk crystals without (or with a very dilute concentration) of mobile electrons and steady-state thermal transport. We will also discuss the possible link between this field of investigation and other phenomena, such as the hybridization of phonon modes and the phonon thermal Hall effect., Comment: A contribution to the special issue of Fizika Nizkikh Temperatur commemorating Radii Gurzhi; 10 pages, 6 figures

The paper analyzes theoretically the influence of fullerenes on the characteristics of $\mathrm{Al/C}_{60}$ composites. The molecular dynamics method is used to study the dependences of density and stiffness constants on the concentration of inclusions, and to calculate the values of the bulk and shear moduli for isotropic polycrystalline nanocomposites. The analysis shows that interfacial interaction significantly affects the properties of nanocomposites. This effect can be taken into account within the framework of the theory of heterogeneous media using the interphase layer model. The properties of the interphase layer are determined by interfacial interaction and can be calculated by approximating the results of molecular dynamics calculations. Using assumptions about the simplified form of the two-particle distribution function allows the interfacial interaction energy to be calculated and the interphase layer properties to be assessed analytically. The paper compares numerical results and analytical estimates, and discusses the validity of the approximations used. The analysis performed on the example of an $\mathrm{Al/C}_{60}$ composite material demonstrates the feasibility of using the analytical model of the interphase layer to estimate the effective density and elastic moduli of heterogeneous media with nano-inhomogeneities., Comment: 12 pages, 4 figures, 2 tables

This paper introduces a novel method for characterizing fracture mechanisms in composite materials using 3D image data gained by computed tomography (CT) measurements. In mineral liberation, the understanding of these mechanisms is crucial, particularly whether fractures occur along the boundaries of mineral phases (intergranular fracture) and/or within mineral phases (transgranular fracture). Conventional techniques for analyzing fracture mechanisms are focused on globally comparing the surface exposure of mineral phases extracted from image measurements before and after fracture. Instead, we present a virtual reassembling algorithm based on image registration techniques, which is applied to 3D data of composite materials before and after fracture in order to determine and characterize the individual fracture surfaces. This enables us to conduct a local quantitative analysis of fracture mechanisms by voxelwise comparing adjacent regions at fracture surfaces. A quantitative analysis of fracture mechanisms is especially important in the context of geometallurgical recycling processes. As primary deposits are decreasing worldwide, the focus is shifting to secondary raw materials containing low concentrations of valuable elements such as lithium. To extract these elements, they can be enriched as engineered artificial minerals in the slag phase of appropriately designed cooling processes. The subsequent liberation through comminution processes, such as crushing, is essential for the extraction of valuable minerals. A better understanding of crushing processes, especially fracture mechanisms in slags, is crucial for the success of recycling. The reassembling algorithm presented in this paper is evaluated through a simulation study, followed by an application to a naturally occurring ore and a slag resulting from a recycling process.

The classical variational approach to brittle fracture propagation does not distinguish between strain energy accumulation in tension versus compression and consequently results in physically unrealistic cracking under compression. A variety of energy splits have been proposed as a possible remedy. However, a unique energy split that can describe this asymmetry for general loading conditions has not been found. The main objective of this paper is to show that a complete phase-field theory of brittle fracture nucleation and propagation, one that accounts for the material strength at large, can naturally capture the tension-compression asymmetry without an energy split. One such theory has been recently proposed by Kumar et al. (2018). Over the past few years, several studies have shown that this theory is capable of accurately describing fracture nucleation and propagation for materials soft and hard under arbitrary monotonic loading conditions. However, a systematic study of the tension-compression asymmetry that emerges from this theory has not yet been reported. This paper does precisely that. In particular, this paper reports a comprehensive study of crack propagation in two problems, one involving a symmetric tension-compression state and the other involving larger compressive stresses at the crack tip. The results are compared with popular energy splits used in literature. The results show that, remarkably, for the second problem, only the complete theory is able to produce experimentally consistent results.

This paper presents a modeling effort to explore the underlying physics of temperature evolution during additive friction stir deposition (AFSD) by a human-AI teaming approach. AFSD is an emerging solid-state additive manufacturing technology that deposits materials without melting. However, both process modeling and modeling of the AFSD tool are at an early stage. In this paper, a human-AI teaming approach is proposed to combine models based on first principles with AI. The resulting human-informed machine learning method, denoted as AFSD-Physics, can effectively learn the governing equations of temperature evolution at the tool and the build from in-process measurements. Experiments are designed and conducted to collect in-process measurements for the deposition of aluminum 7075 with a total of 30 layers. The acquired governing equations are physically interpretable models with low computational cost and high accuracy. Model predictions show good agreement with the measurements. Experimental validation with new process parameters demonstrates the model's generalizability and potential for use in tool temperature control and process optimization.

Froth flotation predominantly separates particles according to their differences in wettability. However, other particle properties such as size, shape or density significantly influence the separation outcome as well. Froth flotation is most efficient for particles within a size range of about $20-200\mu m$, but challenges arise for very fine or coarse particles that are accompanied by low recoveries and poor selectivity. While the impact of particle size on the separation behavior in flotation is well-known by now, the effect of particle shape is less studied and varies based on the investigated zone (suspension or froth) and the separation apparatus used. A multidimensional perspective on the separation process, considering multiple particle properties, enhances the understanding of their collective influence. In this paper the two-dimensional case is studied, i.e., a parametric modeling approach is applied to determine bivariate Tromp functions from scanning electron microscopy-based image data of the feed and the separated fractions. With these functions it is possible to characterize the separation behavior of particle systems. Using a model system of ultrafine ($<10\mu m$) particles, consisting of differently shaped glass particles with different wettability states as the floatable and magnetite as the non-floatable fraction, allows for investigating the influence of particle size, shape and wettability, on the separation. In this way, the present paper contributes to a better understanding of the complex interplay between certain property vectors for the case of ultrafine particles. Furthermore, it demonstrates the benefits of using multivariate Tromp functions for evaluating separation processes, and points out the limitations of SEM based image measurements by means of mineral liberation analysis (MLA) for the studied particle size fraction.

Wrinkling, creasing and folding are frequent phenomena encountered in biological and man-made bilayers made by thin films bonded to thicker and softer substrates often containing fibers. Paradigmatic examples of the latter are the skin, the brain, and arterial walls, for which wiggly cross-sections are detected. Although experimental investigations on corrugation of these and analog bilayers would greatly benefit from scaling laws for prompt comparison of the wrinkling features, neither are they available nor have systematic approaches yielding to such laws ever been provided before. This gap is filled in this paper, where a uniaxially compressed bilayer formed by a thin elastic film bonded on a hyperelastic fiber-reinforced substrate is considered. The force balance at the film-substrate interface is here analytically and numerically investigated for highly mismatched film-substrates. The onset of wrinkling is then characterized in terms of both the critical strain and its corresponding wavenumber. Inspired by the asymptotic laws available for neo-Hookean bilayers, the paper then provides a systematic way to achieve novel scaling laws for the wrinkling features for fiber-reinforced highly mismatched hyperelastic bilayers. Such novel scaling laws shed light on the key contributions defining the response of the bilayer, as it is characterized by a fiber-induced complex anisotropy. Results are compared with Finite Element Analyses and also with outcomes of both existing linear models and available adhoc scalings. Furthermore, the amplitude, the global maximum and minimum of ruga occurring under increasing compression spanning the wrinkling, period doubling and folding regimes are also obtained.

We have carefully examined the above-referenced paper and find the claims of stacking fault formation and transonic dislocation propagation in diamond to be not valid. Additionally, it is quite puzzling that 14 authors on this paper are also co-authors on another recent paper that directly conflicts with the dislocation claims in the Science paper., Comment: 11 pages, 3 figures

When ultrasonic wave is irradiated on materials, a small static stress is required to get materials yielding and flowing. This is called acoustic softening effect, also known as Blaha effect for a long time. In the past, this effect was explained by several continuum scale or meso-scale solid mechanics theories such as stress superposition or energy superposition theory, or crystal/dislocation plasticity. Due to a lot of microscopic complexities happening inside the materials during ultrasonic vibration, fully understanding of acoustic softening effect is not easy. In this paper, traditional solid mechanics theory is expanded by introducing several concepts in semi-conductor physics. Four new aspects were introduced to understand acoustic softening effect. Firstly, contrary to most existed work in acoustic softening research area which treats ultrasound as waves, it was treated as particles. Secondly, crystal/dislocation plastic theory was simplified to a single equation. Thirdly, concepts of photoelectric effect or photo-voltaic effect were introduced. Analogy of electron movement due to light wave and defect movement due to ultrasonic wave was illustrated. Particularly, as light wave is treated as photon, ultrasonic wave is treated as phonon in this paper. Fourthly, defects such as point defects or line defects are assumed to have certain bonding energy. Their bonding energies are assumed to be quantized or discontinuous. The band gap theory used in photo-voltaic theory is embraced to understand defects movements in solid mechanics due to ultrasonic phonon., Comment: 16 pages, 6 figures

Structural modelling of $operando$ pair distribution function (PDF) data of functional materials can be highly complex. To aid the understanding of complex operando PDF data, we here demonstrate a toolbox for PDF analysis. The tools include the structureMining, similarityMapping, nmfMapping apps available through the online service 'PDF in the cloud' (PDFitc, www.pdfitc.org), as well as noise-filtering using principal component analysis (PCA). The tools are applied to both ex situ and operando PDF data for 3 nm $\mathrm{TiO_{2}}$-bronze nanocrystals, which function as the active electrode material in a Li-ion battery. The tools enable structural modelling of the ex situ and operando PDF data, revealing two pristine $\mathrm{TiO_{2}}$ phases (bronze and anatase) and two lithiated $\mathrm{Li_{x}TiO_{2}}$ phases (lithiated versions of bronze and anatase), and the phase evolution during Galvanostatic cycling is characterized., Comment: Preprint, 82 pages in total (front page: 1 page, abstract: 1 page, paper: 34 pages, supporting information: 40 pages, references: 5 pages, synopsis: 1 page), 35 figures in total (frontpage: 1 figure, paper: 8 figures, supporting information: 26 figures)

Data science and artificial intelligence have become an indispensable part of scientific research. While such methods rely on high-quality and large quantities of machine-readable scientific data, the current scientific data infrastructure faces significant challenges that limit effective data curation and sharing. These challenges include insufficient return on investment for researchers to share quality data, logistical difficulties in maintaining long-term data repositories, and the absence of standardized methods for evaluating the relative importance of various datasets. To address these issues, this paper presents the Lennard Jones Token, a blockchain-based proof-of-concept solution implemented on the Ethereum network. The token system incentivizes users to submit optimized structures of Lennard Jones particles by offering token rewards, while also charging for access to these valuable structures. Utilizing smart contracts, the system automates the evaluation of submitted data, ensuring that only structures with energies lower than those in the existing database for a given cluster size are rewarded. The paper explores the details of the Lennard Jones Token as a proof of concept and proposes future blockchain-based tokens aimed at enhancing the curation and sharing of scientific data.

The electronic structure and interactions of kagome materials such as 1:1 (FeGe class) and 1:6:6 (MgFe$_6$Ge$_6$ class) are complicated and involve many orbitals and bands at the Fermi level. Current theoretical models treat the systems in an $s$-orbital kagome representation, unsuited and incorrect both quantitatively and qualitatively to the material realities. In this work, we lay the basis of a faithful framework of the electronic model for this large class of materials. We show that the complicated ``spaghetti" of electronic bands near the Fermi level can be decomposed into three groups of $d$-Fe orbitals coupled to specific Ge orbitals. Such decomposition allows for a clear analytical understanding (leading to different results than the simple $s$-orbital kagome models) of the flat bands in the system based on the $S$-matrix formalism of generalized bipartite lattices. Our three minimal Hamiltonians can reproduce the quasi-flat bands, van Hove singularities, topology, and Dirac points close to the Fermi level, which we prove by extensive ab initio studies. We also obtain the interacting Hamiltonian of $d$ orbitals in FeGe using the constraint random phase approximation (cRPA) method. We then use this as a fundamental ``LEGO"-like building block for a large family of 1:6:6 kagome materials, which can be obtained by doubling and perturbing the FeGe Hamiltonian. We applied the model to its kagome siblings FeSn and CoSn, and also MgFe$_6$Ge$_6$. Our work serves as the first complete framework for the study of the interacting phase diagram of kagome compounds., Comment: 5+50 pages, 3+16 figures, previously submitted. This is the second paper of a series on kagome materials. See also the first paper: arXiv:2305.15469

The development of new materials is a core aspect of advancement in synthesis and application for industry. There is a vast number of possible chemical permutations of the basic elements that can be explored to synthesize materials that possess attractive catalytic, mechanical and electrical properties that may not be easily accessible to traditional experimental methods for various reasons, including cost and time considerations. Nitrides, as examples, require very stringent and precise conditions to successfully synthesize making their experimental exploration very slow. In this paper, we employ the use of machine learning algorithms to predict the bulk properties of Ternary Metal Nitrides (TMN), specifically their bulk modulus which is correlated with the hardness of the material. We were able to develop a consistent model with encouraging accuracy, that was able to predict the bulk moduli of materials that previously did not have computed values. The model was trained on $10^3$ ternary materials with known elastic properties and defined structures, and was able to predict the bulk modulus of $\thickapprox 1,000$ Ternary Metal Nitrides (TMNs) to $\thickapprox 80\%$ accuracy. This approach is orders of magnitude faster than the traditional computational approaches like density functional theory (DFT)\cite{dft-paper} which makes exploratory identification of materials with promising properties fast. We propose that such models be used to select interesting candidates for high throughput computation from first principles., Comment: 5 Pages, 5 Figures, 1 Table

We observe significant, 6.5 - 12%, differences between skyrmion and antiskyrmion Hall angles in existing experimental data. To account for them, the Thiele equation is generalized with the transverse velocity component in the collective coordinate of magnetization vector. The corresponding generalized Hall angle is formulated, and its consequences are compared to the data. A plausible physical origin is provided for explaining the Hall angle differences., Comment: 2 pages, 3 figures

This paper presents an innovative hierarchical meta-modelling approach for predicting the effective elastic properties of stone injected with composite cement grouts containing Carbon NanoTubes (CNTs) for structural rehabilitation purposes. The study first addresses the homogenization of the nano- and micro-scales through numerical representative volume elements. The first numerical model focuses on the cement matrix doped with randomly oriented CNTs, while the second model represents the porous stone with CNT/cement grout filling the pores. However, the computational burden associated with these models poses a significant limitation when analysing large-scale macrostructural elements. To overcome this challenge, a hierarchical meta-modelling approach based on two nested Kriging surrogate models is proposed. This approach offers a fast and accurate alternative to bypass the time-consuming numerical homogenization process. The first surrogate model establishes a connection between the microstructural characteristics of the CNTs and cement and the effective elastic properties of the composite grout. Subsequently, a second meta-model expands over the first one by introducing two additional variables: the elastic modulus of the stone and the porosity, allowing for estimation of the overall elastic properties of CNT/cement/stone composites. The accuracy and efficiency of the proposed hierarchical meta-model is demonstrated through detailed parametric analyses. To showcase its potential for optimizing rehabilitation interventions, the paper is closed with its application to a benchmark case study of a stone column injected with CNT/cement grout.

We present a brief review of experimental and theoretical papers on studies of electron transport and magnetic properties in manganese-based compounds Mn$_2$YZ and Mn$_3$Z (Y = V, Cr, Fe, Co, Ni, etc.; Z = Al, Ge, Sn, Si, Pt, etc.). It has been shown that in the electronic subsystem of Mn$_2$YZ compounds, the states of a half-metallic ferromagnet and a spin gapless semiconductor can arise with the realization of various magnetic states, such as a ferromagnet, a compensated ferrimagnet, and a frustrated antiferromagnet. Binary compounds Mn$_3$Z have the properties of a half-metallic ferromagnet and a topological semimetal with a large anomalous Hall effect, spin Hall effect, spin Nernst effect, and thermal Hall effect. Their magnetic states are also very diverse: from a ferrimagnet and an antiferromagnet to a compensated ferrimagnet and a frustrated antiferromagnet, as well as an antiferromagnet with a kagome-type lattice. It has been demonstrated that the electronic and magnetic properties of such materials are very sensitive to external influences (temperature, magnetic field, external pressure), as well as the processing method (cast, rapidly quenched, nanostructured, etc.). Knowledge of the regularities in the behavior of the electronic and magnetic characteristics of Mn$_2$YAl and Mn$_3$Z compounds can be used for applications in micro- and nanoelectronics and spintronics., Comment: Review paper, 27 pages

Two-dimensional materials and their heterostructures have enormous applications in Electrochemical Energy Storage Systems (EESS) such as batteries. A comprehensive and solid understanding of these materials' thermal transport and mechanism is essential for the practical design of EESS. Experiments have challenges in providing improved control and characterization of complex structures, especially for low dimensional materials. Theoretical and simulation tools such as first-principles calculations, boltzmann transport equations, molecular dynamics simulations, lattice dynamics simulation, and non-equilibrium Green's function provide reliable predictions of thermal conductivity and physical insights to understand the underlying thermal transport mechanism in materials. However, doing these calculations require high computational resources. The development of new materials synthesis technology and fast-growing demand for rapid and accurate prediction of physical properties require novel computational approaches. The machine learning (ML) method provides a promising solution to address such needs. This review details the recent development in atomistic/molecular studies and ML of thermal transport in EESS. The paper also addresses the latest significant experimental advances. However, designing the best low-dimensional materials-based heterostructures is like a multivariate optimization problem. For example, a particular heterostructure may be suitable for thermal transport but can have lower mechanical strength/stability. For bi/multilayer structures, the interlayer distance may influence the thermal transport properties and interlayer strength. Therefore, the last part addresses the future research direction in low-dimensional materials-based heterostructure design for thermal transport in EESS., Comment: 48 pages, 16 figures, Perspective Review Paper

The significant advancements in perovskite solar cell (PSC) research and development have reignited optimism for the practicality of solar energy. A deeper comprehension of the fundamental mechanisms is essential for enhancing the current solar technology. Impedance spectroscopy (IS) characterization, in conjunction with other analytical methods, stands out as the primary approach for gaining insights into the internal workings of solar cells. The continuous analysis and refinement of electrochemical spectroscopy data for PSCs have unveiled intricate operational details. Despite the ongoing improvements, the absence of a centralized repository for this information poses challenges for tracking progress effectively. This review paper aims to consolidate the physical phenomena behind the development of PSC research, aiming to establish a comprehensive knowledge base on impedance plots, equivalent circuits, and related processes.

The kagome metal CsV$_3$Sb$_5$ is an ideal platform to study the interplay between topology and electron correlation. To understand the fermiology of CsV$_3$Sb$_5$, intensive quantum oscillation (QO) studies at ambient pressure have been conducted. However, due to the Fermi surface reconstruction by the complicated charge density wave (CDW) order, the QO spectrum is exceedingly complex, hindering a complete understanding of the fermiology. Here, we directly map the Fermi surface of the pristine CsV$_3$Sb$_5$ by measuring Shubnikov-de Haas QOs up to 29 T under pressure, where the CDW order is completely suppressed. The QO spectrum of the pristine CsV$_3$Sb$_5$ is significantly simpler than the one in the CDW phase, and the detected oscillation frequencies agree well with our density functional theory calculations. In particular, a frequency as large as 8,200 T is detected. Pressure-dependent QO studies further reveal a weak but noticeable enhancement of the quasiparticle effective masses on approaching the critical pressure where the CDW order disappears, hinting at the presence of quantum fluctuations. Our high-pressure QO results reveal the large, unreconstructed Fermi surface of CsV$_3$Sb$_5$, paving the way to understanding the parent state of this intriguing metal in which the electrons can be organized into different ordered states., Comment: 4 figures, 1 table. This is the preprint of a published paper in PNAS

Indium selenide, In2Se3, has recently attracted growing interest due to its novel properties, including room temperature ferroelectricity, outstanding photoresponsivity, and exotic in-plane ferroelectricity, which open up new regimes for next generation electronics. In2Se3 also provides the important advantage of tuning the electrical properties of ultra-thin layers with an external electrical and magnetic field, making it a potential platform to study novel two-dimensional physics. Yet, In2Se3 has many different polymorphs, and it has been challenging to synthesize single-phase material, especially using scalable growth methods, as needed for technological applications. In this paper, we use aberration-corrected scanning transmission electron microscopy to characterize the microstructure of twin-free single-phase ultra-thin layers of beta-In2Se3, prepared by a unique molecular beam epitaxy approach. We emphasize features of the In2Se3 layer and In2Se3/InP interface which provide evidence for understanding the growth mechanism of the single-phase In2Se3. This novel approach for forming high-quality twin-free single phase two-dimensional crystals on InP substrates is likely to be applicable to other technologically important substrates., Comment: 19 pages, 4 figures

To utilize half-metallic Heusler alloys in practical spintronic devices, such as magnetic sensors and magnetic memories, the key is to realize highly textured and structurally ordered polycrystalline thin films. In this study, we fabricated polycrystalline Co2FeGa0.5Ge0.5 (CFGG) Heusler alloy films deposited on a [001]-oriented Ag buffer layer, which was achieved by introducing N2 into Ar during the sputtering process, on a thermally oxidized Si substrate. We obtained strongly [001]-oriented CFGG films with B2 ordering and a high saturation magnetization close to the theoretical value, which can provide highly spin-polarized electric and spin current sources in spintronic devices with industrial viability., Comment: 16 papers, 5 figures

Nitride ferroelectrics have recently emerged as promising alternatives to oxide ferroelectrics due to their compatibility with mainstream semiconductor processing. ScAlN, in particular, has exhibited remarkable piezoelectric coupling strength ($K^2$) comparable to that of lithium niobate (LN), making it a valuable choice for RF filters in wireless communications. Recently, ScAlN has sparked interest in its use for nanophotonic devices, chiefly due to its large bandgap facilitating operation in blue wavelengths coupled with promises of enhanced nonlinear optical properties such as a large second-order susceptibility ($\chi^{(2)}$). It is still an open question whether ScAlN can outperform oxide ferroelectrics concerning the Pockels effect -- an electro-optic coupling extensively utilized in optical communications devices. In this paper, we present a comprehensive theoretical analysis and experimental demonstration of ScAlN's Pockels effect. Our findings reveal that the electro-optic coupling of ScAlN, despite being weak at low Sc concentration, may be significantly enhanced at high levels of Sc doping, which points the direction of continued research efforts to unlock the full potential of ScAlN.

Superconducting circuits based on hybrid InAs Josephson Junctions (JJs) play a starring role in the design of fast and ultra-low power consumption solid-state quantum electronics and exploring novel physical phenomena. Conventionally, 3D substrates, 2D quantum wells (QWs), and 1D nanowires (NWs) made of InAs are employed to create superconductive circuits with hybrid JJs. Each platform has its advantages and disadvantages. Here, we proposed the InAs-on-insulator (InAsOI) as a groundbreaking platform for developing superconducting electronics. An epilayer of semiconductive InAs with different electron densities was grown onto an InAlAs metamorphic buffer layer, efficiently used as a cryogenic insulator to decouple adjacent devices electrically. JJs with various lengths and widths were fabricated employing Al as a superconductor and InAs with different electron densities. We achieved a switching current density of 7.3 uA/um, a critical voltage of 50-to-80 uV, and a critical temperature equal to that of the superconductor used. For all the JJs, the switching current follows a characteristic Fraunhofer pattern with an out-of-plane magnetic field. These achievements enable the use of InAsOI to design and fabricate surface-exposed Josephson Field Effect Transistors with high critical current densities and superior gating properties., Comment: 19 pages, 4 figures, supporting information at the end of the paper

We investigate the effect of structural deformation on the magnetic properties of orthorhombic CePdAl$_3$ in relation to its tetragonal polymorph. Utilizing x-ray and neutron diffraction we establish that the crystal structure has the $Cmcm$ space group symmetry and exhibits pseudo-tetragonal twinning. According to density-functional calculations the tetragonal-orthorhombic deformation mechanism has its grounds in relatively small free enthalpy difference between the polymorphs, allowing either phase to be quenched and fully accounts for the twinned microstructure of the orthorhombic phase. Neutron diffraction measurements show that orthorhombic CePdAl$_3$ establishes long-range magnetic order below $T_\mathrm{N}$=5.29 (5) K characterized by a collinear, antiferromagnetic arrangement of magnetic moments. Magnetic anisotropies of orthorhombic CePdAl$_3$ arise from strong spin-orbit coupling as evidenced by the crystal-field splitting of the $4f$ multiplet, fully characterised with neutron spectroscopy. We discuss the potential mechanism of frustration posed by antiferromagnetic interactions between nearest neighbours in the tetragonal phase, which hinders the formation of long-range magnetic order in tetragonal CePdAl$_3$. We propose that orthorhombic deformation releases the frustration and allows for long-range magnetic order., Comment: Finalized paper from the splitting of arxiv.org/abs/2106.08194v1

Ultralow dimensionality of 2D layers magnifies their sensitivity to adjacent charges enabling even postprocessing electric control of multifunctional structures. However, functionalizing 2D layers remains an important challenge for on-demand device property exploitation. Here we report that an electrical and even fully optical way to control and write modifications to the magnetoresistive response of CVD-deposited graphene is achievable through the electrostatics of the photoferroelectric substrate. For electrical control, the ferroelectric polarization switch modifies graphene magnetoresistance by 67% due to a Fermi level shift with related modification in charge mobility. A similar function is also attained entirely by the bandgap light due to the substrate photovoltaic effect. Moreover, an all-optical way to imprint and recover graphene magnetoresistance by light is reported as well as magnetic control of graphene transconductance. These findings extend photoferroelectric control in 2D structures to new a magnetic dimension and advance wireless operation for sensors and field-effect transistors., Comment: 7 pages, 6 figures, journal paper

Understanding the nature of irradiation damage often requires a multi-scale and multi-physics approach, i.e. it requires a significant amount of information from experiments, simulations and phenomenological models. This paper focuses on the initial stages of irradiation damage, namely neutron-induced displacement cascades in zirconium, as nuclear-grade zirconium alloys are widely used in fuel assemblies. We provide results of large-scale molecular dynamics (MD) simulations based on existing inter-atomic potentials and the two-temperature model to include the effect of electron-phonon coupling. Our data can be used directly in higher scale methods. Furthermore, we analysed summary statistics associated with defect production, such as the number of defects produced, their distribution and the size of clusters. As a result, we have developed a generative model of collision cascades. The model is hierarchical, as well as stochastic, i.e. it includes the variance of the considered features. This development had three main objectives: to establish a sufficient descriptor of a cascade, to develop an interpolator of data obtained from high-fidelity simulations, and to demonstrate that the statistical model of the data can generate representative distributions of primary irradiation defects. The results can be used to generate synthetic inputs for longer length- and time-scale models, as well as to build fast approximations relating dose, damage and irradiation conditions.

This paper is concerned with $\textit{ab initio}$ crystal structure relaxation under a fixed unit cell volume, which is a step in calculating the static equations of state and forms the basis of thermodynamic property calculations for materials. The task can be formulated as an energy minimization with a determinant constraint. Widely used line minimization-based methods (e.g., conjugate gradient method) lack both efficiency and convergence guarantees due to the nonconvex nature of the feasible region as well as the significant differences in the curvatures of the potential energy surface with respect to atomic and lattice components. To this end, we propose a projected gradient descent algorithm named PANBB. It is equipped with (i) search direction projections onto the tangent spaces of the nonconvex feasible region for lattice vectors, (ii) distinct curvature-aware initial trial step sizes for atomic and lattice updates, and (iii) a nonrestrictive line minimization criterion as the stopping rule for the inner loop. It can be proved that PANBB favors theoretical convergence to equilibrium states. Across a benchmark set containing 223 structures from various categories, PANBB achieves average speedup factors of approximately 1.41 and 1.45 over the conjugate gradient method and direct inversion in the iterative subspace implemented in off-the-shelf simulation software, respectively. Moreover, it normally converges on all the systems, manifesting its unparalleled robustness. As an application, we calculate the static equations of state for the high-entropy alloy AlCoCrFeNi, which remains elusive owing to 160 atoms representing both chemical and magnetic disorder and the strong local lattice distortion. The results are consistent with the previous calculations and are further validated by experimental thermodynamic data., Comment: 13 pages, 10 figures, 1 table

A numerical parameter, referred to as a topological index, is used to represent the molecular structure of a compound by analyzing its graph-theoretical characteristics. Topological indices are predictive methods for the physicochemical properties of chemical compounds in the context of quantitative structure-activity relationship (QSAR) and quantitative structure-property relationship (QSPR) analysis. Graph entropies have evolved into information-theoretic tools for exploring the structural information of molecular graphs. In this paper, we compute the Nirmala index, as well as the first and second inverse Nirmala index, for the diamond structure using its M-polynomial. Furthermore, entropy measures based on Nirmala indices are derived for the diamond structure. The comparison of the Nirmala indices and corresponding entropy measures is presented through numerical computation and 2D line plots. A regression model is built to investigate the relationship between the Nirmala indices and corresponding entropy measures., Comment: 22 pages, 7 figures