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At least 793 records · Page 44

Modulating Iron Crystals with Lattice Chalcophile‐Siderophile Elements for Selective Dechlorinations Over Hydrogen Evolution

Selective dechlorination of organic chlorides over hydrogen evolution reaction (HER) remains a challenge because of their coincidence. Nanoscale zerovalent iron (nFe 0 ) draws a promising picture of in situ groundwater dechlorination, but its indiscriminate reactivity limits the application. Here, nFe 0 crystals are designed with electron shuttles and improved hydrophobic nature based on elemental chalcophile-siderophile characteristics, where chalcophile-siderophile S served as a bridge to allow impregnating nFe 0 crystals with weakly siderophile and strongly chalcophile Cu. Even impregnations of lattice chalcophile-siderophile elements into the nFe 0 crystals are evidenced at both intraparticle and individual-particle levels. The modulated Fe microenvironment and physicochemical properties broke the reactivity-selectivity-longevity-stability trade-off. Compared to nFe 0 , superhydrophobic Cu─S─nFe 0 with lattice expansion promoted dechlorination by 20-fold but inhibited HER by 150-fold, utilizing ≈80–100% electrons from the Fe 0 reservoir. This work demonstrates the concept of engineering nFe 0 lattice with tunable structure-property relationships, mimicking reductive dehalogenases by selectively interacting with halocarbon functional groups for efficient dehalogenation and sustainable groundwater remediation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Emerging Opportunities in Manufacturing Bulk Soft-Magnetic Alloys for Energy Applications: A Review

Abstract Soft-magnetic alloys exhibit exceptional functional properties that are beneficial for a variety of electromagnetic applications. These alloys are conventionally manufactured into sheet or bar forms using well-established ingot metallurgy practices that involve hot- and cold-working steps. However, recent developments in process metallurgy have unlocked opportunities to directly produce bulk soft-magnetic alloys with improved, and often tailorable, structure–property relationships that are unachievable conventionally. The emergence of unconventional manufacturing routes for soft-magnetic alloys is largely motivated by the need to improve the energy efficiency of electromagnetic devices. In this review, literature that details emerging manufacturing approaches for soft-magnetic alloys is overviewed. This review covers (1) severe plastic deformation, (2) recent advances in melt spinning, (3) powder-based methods, and (4) additive manufacturing. These methods are discussed in comparison with conventional rolling and bar processing. Perspectives and recommended future research directions are also discussed.

36 MATERIALS SCIENCE↗

Solvent Transport in Disordered and Dynamic Membrane Pores: Implications for Reverse Osmosis and Nanofiltration Membranes

Pressure-driven separations with nanoporous membranes, such as reverse osmosis and nanofiltration, play a vital role in addressing water scarcity and enabling resource recovery. Understanding water or solvent transport in membrane pores is essential for advancing membrane separation technologies. A key question in transport modeling is to establish a relationship between solvent permeability and membrane porous structure properties, such as porosity or pore size. The nano- and subnanometer pores in polymeric membranes such as reverse osmosis and nanofiltration membranes are highly tortuous and dynamically connected, which challenges the conventional methods of transport modeling. This study addresses this challenge by developing a theoretical framework to describe solvent transport through membranes with dynamic and disordered porous structure. Specifically, we propose a lattice model to describe the pore network, while preserving the viscous nature of solvent permeation. We further establish a relationship between solvent permeability and membrane porosity or pore size, which is validated by molecular dynamics simulations and experimental data. By integrating this relationship into the solution-friction model, we define pore connectivity and local friction coefficient to quantify the impact of pore structure on solvent permeability. Our analysis highlights the dominant influence of pore connectivity on the permeability of reverse osmosis and nanofiltration membranes, particularly when the pore size approaches the dimensions of solvent molecules. Overall, this study provides critical insights into water and solvent transport mechanisms in nanoporous membranes, opening the door for strategies to substantially enhance membrane performance.

membranes↗

Effect of Pressure on Crystal Structure and Phonon Density of States of FeSi

The strongly correlated material FeSi displays several unusual thermal, magnetic, and structural properties under varying pressure-temperature (P-T) conditions. It is a potential thermoelectric alloy and a material with several geochemical implications as a possible constituent at the Earth's core-mantle boundary (CMB). Previous theoretical studies predicted a pressure-induced B20-B2 transition at ambient temperature below 40 GPa; however, experimentally, the structural transition is observed only at high P-T conditions. In this study, we have performed high-pressure powder X-ray diffraction (XRD) up to 90 GPa and Nuclear Resonant Inelastic X-ray Scattering (NRIXS) measurements up to 120 GPa to understand the phase stability and lattice dynamics. Our study provides evidence for a non-hydrostatic stress-induced B20-B2 transition in FeSi at around 36 GPa. We deduced the Fe partial phonon density of states (PDOS) and thermal parameters from NRIXS measurements up to 120 GPa and compared them with density functional theory (DFT) calculations. Furthermore, the computations show pressure-induced metallization and the band gap closing around 12 GPa.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

TransPolymer: a Transformer-based language model for polymer property predictions

Accurate and efficient prediction of polymer properties is of great significance in polymer design. Conventionally, expensive and time-consuming experiments or simulations are required to evaluate polymer functions. Recently, Transformer models, equipped with self-attention mechanisms, have exhibited superior performance in natural language processing. However, such methods have not been investigated in polymer sciences. Herein, we report TransPolymer, a Transformer-based language model for polymer property prediction. Our proposed polymer tokenizer with chemical awareness enables learning representations from polymer sequences. Rigorous experiments on ten polymer property prediction benchmarks demonstrate the superior performance of TransPolymer. Moreover, we show that TransPolymer benefits from pretraining on large unlabeled dataset via Masked Language Modeling. Experimental results further manifest the important role of self-attention in modeling polymer sequences. We highlight this model as a promising computational tool for promoting rational polymer design and understanding structure-property relationships from a data science view.

36 MATERIALS SCIENCE↗

Rapid data acquisition and machine learning-assisted composition design of functionally graded alloys via wire arc additive manufacturing

Abstract The lack of high-quality datasets in materials science hinders artificial intelligence (AI)-driven alloy design. To address this challenge, wire arc additive manufacturing (WAAM) was employed to fabricate graded alloys, generating extensive data for machine learning (ML)-assisted property prediction. ML models were developed using high-throughput experiments, computational models, and genetic algorithm to optimize feature selection, successfully predicting hardness and porosity. The ML model demonstrated its efficacy by designing a gradient alloy with enhanced properties. However, scaling up revealed uncertainties in tensile property and porosity due to differences in size and thermal conditions between the designed alloy build and the gradient print used to construct the ML model. This underscores the need for uncertainty quantification and process optimization in WAAM-driven alloy design. Our work advances AI-integrated additive manufacturing, offering a rapid approach to exploring process–structure–property relationships and accelerating materials development.

Wang, Xin↗

Advanced Interactive 3D Visualization Tool for Customizable Analyses of Tomography Datasets in Material Science

Current methods for visualizing and analyzing 3D tomography datasets in materials science often lack the interactivity and depth required for detailed structural insights. This limitation restricts a researchers' ability to accurately interpret complex data, which is critical for advancing material innovations and understanding structural properties. To address this issue, we have developed a novel, web-based interactive 3D visualization and analysis tool from the Trame framework that offers customizable features to enhance data interpretability. The tool allows users to adjust parameters such as visible range, slice planes, data rotation, and layering, providing a more detailed and dynamic view of complex structures. Its user-friendly web interface increases the accessibility and ease of use for both novice and experienced researchers, to visualize large volumetric datasets. The tool supports a diverse range of data formats, making it versatile for various research applications. Unique capabilities include real-time data manipulation, automated feature detection, context-sensitive feedback, and real-time volume calculations and distributions per sliced region or layer, alongside the ability to quickly generate high-quality screenshots and videos for presentations and reports. These advancements offer a comprehensive solution for enhanced 3D data exploration, significantly improving the analysis process and communication of results in materials science.

36 - MATERIALS SCIENCE↗

Feedstock design for quality biomaterials

Feedstock design is crucial for lignocellulosic biomass use. Current strategies for feedstock design cannot be readily applied to improve the quality of biomass-based materials, limiting the sustainability and economics of lignocellulosic biorefineries. Recent studies have advanced the understanding of biomass structure–property relationships and discovered several characteristics, such as molecular weight, uniformity, linkage profile, and functional groups, that are critical for manufacturing diverse quality biomaterials. Further, these discoveries call for fundamentally different strategies for feedstock development. Such strategies need to rediscover the roles of monolignol biosynthesis enzymes and leverage lignin polymerization enzymes to achieve precise control of lignin molecular structure. These innovations could transform biomass into feedstock for high-quality biomaterials, addressing essential environmental challenges and empowering the bioeconomy.

09 BIOMASS FUELS↗

Ferroelectric phase transition in group-IV monochalcogenides from an equivariant machine learned force field

Group-IV monochalcogenides are a class of layered ferroelectric semiconductors that have demonstrated spontaneous intrinsic polarization above room temperature. Here, in this study, we use the multi-atomic cluster expansion (MACE) machine learning architecture to train and test a force field capable of modeling the structural properties and second-order ferroelectric-to-paraelectric phase transition in a Group-IV monochalcogenide, GeSe. The model captures the double-well potential energy surface associated with the onset of macroscopic polarization in bulk GeSe within 12.5 meV/atom, as well as near-equilibrium properties like the phonon dispersion. The development of this quantitatively accurate force field enables long-time molecular dynamics simulations, which predict the critical temperature of the ferroelectric-to-paraelectric phase transition in bulk GeSe to be T c = 600 K. This study demonstrates the capabilities of equivariant force-fields to accurately describe phenomena associated with structural symmetry breaking.

ferroelectricity↗

Convergence of micro-geochemistry and micro-geomechanics towards understanding proppant shale rock interaction: A Caney shale case study in southern Oklahoma, USA

As a direct outcome of economic development coupled with an increase in population, global energy demand will continue to rise in the coming decades. Although renewable energy sources are increasingly investigated for optimal production, the immediate needs require focus on energy sources that are currently available and reliable, with a minimal environmental impact; the efficient exploration and production of unconventional hydrocarbon resources is bridging the energy needs and energy aspirations, during the current energy transition period. The main challenges are related to the accurate quantification of the critical rock properties that influence production, their heterogeneity and the multiscale driven physico-chemical nature of rock–fluid interactions. A key feature of shale reservoirs is their low permeability due to dominating nanoporosity of the clay-rich matrix. As a means of producing these reservoirs in a cost-effective manner, a prerequisite is creation of hydraulic fracture networks capable of the highest level of continued conductivity. Fracturing fluid chemical design, formation brine geochemical composition, and rock mineralogy all contribute to swelling-induced conductivity damage. The Caney Shale is an organic-rich, often calcareous mudrock. Many studies have examined the impact that clay has on different kinds of shale productivity but there is currently no data reported on the Caney Shale in relation to horizontal drilling; all reported data on the Caney Shale is on vertical wells which are shallow, compared to an emerging play that is at double the depth. Here, in this work we develop geochemical–geomechanical integration of rock properties at micro-and nanoscales that can provide insights into the potential proppant embedment and its mitigation. The novel methodology amalgamates the following: computed X-ray tomography, scanning electron microscopy, energy dispersive spectroscopy, micro-indentation, and Raman spectroscopy techniques. Here, our results show that due to the multiscale heterogeneity in the Caney Shale, these geochemical and structural properties translate into a variation in mechanical properties that will impact interaction between the proppant and the host shale rock.

03 NATURAL GAS↗

Nucleation and growth of blue phase liquid crystals on chemically-patterned surfaces: a surface anchoring assisted blue phase correlation length

In condensed matter, the correlation length is an essential parameter which describes the distance over which a material maintains its structural properties. In liquid crystals, for the orientational order parameter this characteristic length is of the order of nanometers, while in solid crystals it can extend to macroscopic length scales. Here, we report the measurement of the correlation length, or persistence length, of the crystallographic orientation of blue phases (BPs)—chiral liquid crystals with long-range 3D-crystalline structures and submicron-sized lattice-parameters. These materials exhibit phase transformations that have been identified as the liquid analog of crystal-crystal martensitic transformations. In this work, we use liquid epitaxial growth to achieve spontaneous BP-crystal nucleation and subsequent growth. Specifically, we design patterned substrates made of a binary array of regions with different liquid crystal anchoring, which facilitate a uniform nucleation and growth of BP-crystals with (100)-lattice orientation and a simple cubic symmetry. Furthermore, our results indicate that this simple cubic BP, the so-called blue phase II (BPII), forms first on the patterned surface, thereby propagating the growth of domains in directions parallel or perpendicular to the patterned regions. These results are used to understand the emergence of a surface anchoring assisted BPII-correlation length, taken as the distance over which the BP preserves its lattice orientation, as a function of time and pattern characteristics. We found that BPII single crystals can be achieved on patterned regions whose lateral dimensions are equal to or larger than 10 μm, consistent with our measurements of the BPII-correlation length. This newly acquired understanding of the role of surfaces on the formation of BPs is then used to design processes that permit formation of macroscopically large mono-domain, single-crystal BPs by relying on significantly reduced patterned areas (only part of the area is patterned), a feature that could benefit the applications of this intriguing class of materials.

correlation length↗

Quasiparticle electronic structure of phthalocyanine:TMD interfaces from first-principles GW

Interfaces formed between monolayer transition metal dichalcogenides and (metallo)phthalocyanine molecules are promising in energy applications and provide a platform for studying mixed-dimensional molecule-semiconductor heterostructures in general. An accurate characterization of the frontier energy level alignment at these interfaces is key in the fundamental understanding of the charge transfer dynamics between the two photon absorbers. Here, we employ the first-principles substrate screening GW approach to quantitatively characterize the quasiparticle electronic structure of a series of interfaces: metal-free phthalocyanine (H 2 Pc) adsorbed on monolayer MX 2 (M = Mo, W; X = S, Se) and zinc phthalocyanine (ZnPc) adsorbed on MoX 2 (X = S, Se). Furthermore, we reveal the dielectric screening effect of the commonly used α-quartz (SiO 2 ) substrate on the H 2 Pc:MoS 2 interface using the dielectric embedding GW approach. Our calculations furnish a systematic set of GW results for these interfaces, providing the structure–property relationship across a series of similar systems and benchmarks for future experimental and theoretical studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploring solvation structure and transport behavior for rational design of advanced electrolytes for next generation of lithium batteries

The efficacy of electrolytes significantly affects battery performance, leading to the development of several strategies to enhance them. Despite this, the understanding of solvation structure remains inadequate. It is imperative to understand the structure–property–performance relationship of electrolytes using diverse techniques. Here, this review explores the recent advancements in electrolyte design strategies for high capacity, high-voltage, wide-temperature, fast-charging, and safe applications. To begin, the current state-of-the-art electrolyte design directions are comprehensively reviewed. Subsequently, advanced techniques and computational methods used to understand the solvation structure are discussed. Additionally, the importance of high-throughput screening and advanced computation of electrolytes with the help of machine learning is emphasized. Finally, future horizons for studying electrolytes are proposed, aimed at improving battery performance and promoting their application in various fields by enhancing the microscopic understanding of electrolytes.

25 ENERGY STORAGE↗

Supramolecular and Hybrid Bonding Polymers

Staudinger established a century ago the existence of covalent macromolecules, work that led to the development of transformative materials of great benefit to society and a “quantum leap” in our understanding of biological systems. Over the past few decades the concept of supramolecular polymers has emerged–chemical systems in which structural units bond strongly to each other non-covalently. Herein, we discuss how these dynamic systems actually exist in the natural world and can create soft materials with structures, properties, and functions beyond the ones we know in Staudinger polymers. We reflect here on the potential of novel systems in which covalent and supramolecular polymers are chemically integrated and describe them as hybrid bonding polymers. This paper describes the concept with recent examples from the Stupp laboratory, and discusses their potential functions as robotic materials that mimic living matter and structures that offer new ideas on how to recycle and reuse soft materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural validation of a thermoplastic composite wind turbine blade with comparison to a thermoset composite blade

Reactive infusible thermoplastics have the potential to be advantageous for wind turbine blade composites because they are recyclable at end of life, can have reduced manufacturing costs, enable thermal joining and have similar, and in some cases better, structural properties than traditional thermoset epoxy composites. However, these materials are new to the wind industry and there is risk to investing in a material that has not been validated at a blade scale. Industry cannot adopt a new material such as this without large-scale validation and demonstration of system-level advantages in cost and/or performance. This paper presents structural characterization of a 13-m thermoplastic composite wind turbine blade compared to an identical geometry thermoset epoxy blade. In this work, the results of this comparison showed that the flatwise structural static performance and the fatigue performance of the two blades were similar, but the thermoplastic composite blade had increased damping compared to the epoxy blade, which may result in reduced operational loads.

17 WIND ENERGY↗

Correlating hidden local structural distortion with antiferroelectric-ferroelectric transition in PbZrO 3 -based perovskites

Externally stimulated antiferroelectric-ferroelectric (AFE-FE) transition makes AFE materials attractive for many applications ranging from energy storage to sensing. This transition-mediated macroscopic electrical characteristics have been extensively investigated, yet the underlying structural evolution remains poorly understood. Herein, we study the local- and long-range structural evolutions in the Nb-doped Pb(Zr,Sn,Ti)O 3 perovskites by in-situ X-ray total scattering and diffraction, which show three different types of AFE-FE transitions. The evolution of long-range structure from diffraction and local structure identified by atomic pair distribution function (PDF) are consistent well with the phase transition behavior indicated by macroscopic polarization/strain measurements, while discrepancies exist. Interestingly, frequently employed long-range structure picture that the uniform AFE pseudo-tetragonal to FE rhombohedral transformation is insufficient to understand the distinct composition-dependent AFE-FE transition behaviours. Instead, the reversibility of this transition correlates with the chemically sensitive local atomic displacements revealed by newly developed in-situ PDF. The critical electric field of transition is associated with the local structural differences between the AFE and FE state. The macroscopic electrostrains can be well estimated by the phase transition associated lattice strain and domain alignment from in-situ synchrotron XRD data, while the local strains calculated from in-situ PDFs are found to be much lower. Finally, these results provide a fresh insight into the AFE-FE transition, and advance the understanding of structure-property relationships in AFE materials.

36 MATERIALS SCIENCE↗

Opportunities in electrically tunable 2D materials beyond graphene: Recent progress and future outlook

The interest in two-dimensional and layered materials continues to expand, driven by the compelling properties of individual atomic layers that can be stacked and/or twisted into synthetic heterostructures. The plethora of electronic properties as well as the emergence of many different quasiparticles, including plasmons, polaritons, trions, and excitons with large, tunable binding energies that all can be controlled and modulated through electrical means, has given rise to many device applications. In addition, these materials exhibit both room-temperature spin and valley polarization, magnetism, superconductivity, piezoelectricity that are intricately dependent on the composition, crystal structure, stacking, twist angle, layer number, and phases of these materials. Initial results on graphene exfoliated from single bulk crystals motivated the development of wide-area, high purity synthesis and heterojunctions with atomically clean interfaces. Now by opening this design space to new synthetic two-dimensional materials “beyond graphene,” it is possible to explore uncharted opportunities in designing novel heterostructures for electrically tunable devices. To fully reveal the emerging functionalities and opportunities of these atomically thin materials in practical applications, this review highlights several representative and noteworthy research directions in the use of electrical means to tune these aforementioned physical and structural properties, with an emphasis on discussing major applications of beyond graphene 2D materials in tunable devices in recent years and an outlook of what is to come in the next decade.

Vincent, Tom (ORCID:0000000159749137)↗

Effect of Water Concentration in LiPF 6 -Based Electrolytes on the Formation, Evolution, and Properties of the Solid Electrolyte Interphase on Si Anodes

A trace amount of water in an electrolyte is one of the factors detrimental to the electrochemical performance of silicon (Si)-based lithium-ion batteries that adversely affect the formation and evolution of the solid electrolyte interphase (SEI) on Si-based anodes and change its properties. Thus far, a lack of fundamental and mechanistic understanding of SEI formation, evolution, and properties in the presence of water has inhibited efforts to stabilize the SEI for improved electrochemical performance. As such, we investigated the SEI formed in a Gen2 electrolyte (1.2 M LiPF6 in ethylene carbonate/ethyl methyl carbonate, 3:7 wt %, water content: <10 ppm) with and without additional water (50 ppm) at varying potentials (1.0, 0.5, 0.2, and 0.01 V vs Li/Li + ). The impact of additional water on the morphological, (electro)chemical, and structural properties of SEI was studied using microscopic (atomic force microscopy and scanning spreading resistance microscopy) and spectroscopic (X-ray photoelectron spectroscopy, attenuated total reflection Fourier-transform infrared spectroscopy, and time-of-flight secondary ion mass spectrometry) techniques. The SEI exhibits both potential- and water concentration-dependent trends in its morphology and chemical composition. The presence of additional water in the electrolyte causes parasitic reactions, which onset at ~1.0 V, resulting in a reduction of electrolyte components and result in the formation of an insulating, fluorophosphate-rich SEI. In addition, hydrolysis of LiPF 6 creates hydrofluoric acid, which reacts with the surface oxide layer on the Si electrode, leading to a pitted and inhomogeneous SEI structure.

36 MATERIALS SCIENCE↗