Materials Science Research Articles

Dynamic Imaging of Electrochemically Induced Transformations in Layered Tin Chalcogenide Catalysts.

Understanding the dynamic transformation processes of electrocatalysts during electrochemical reactions is crucial for the development of advanced materials for energy conversion and storage, yet it remains a challenge. Herein, we report the real-time monitoring of the dynamic transformation of a series of layered Sn chalcogenides during electrochemical reduction using a plasmonic imaging method. Taking SnSe2 as an example, we observed a strong firework-like emission diffusing outward from SnSe2 to the surrounding solution under a negative potential. The diffusion coefficient of the observed species is indicative of Sn nanoclusters rather than smaller ions. This study also extends to SnSe and SnS2 nanosheets, demonstrating the general applicability of plasmonic imaging for probing the stability and transformation mechanism of heterogeneous catalysts in electrocatalytic reactions. These insights provide a foundational understanding for designing more stable and efficient electrocatalysts for industrial applications.

Latent Pitfalls in Microstructure-Based Modeling for Thermally Aged 9Cr-1Mo-V Steel (Grade 91)

Abstract A case study was conducted on a mechanistic model development that predicted tensile strength deterioration with thermal aging of 9Cr-1Mo-V steel in supporting the 60-year design life expected for advanced nuclear reactors. For property prediction beyond practical testing times, mechanistic modeling is highly desired, as it taps into the physics of structure-property relationships and therefore can generate reliable results for extrapolation. Meanwhile, as mechanistic models are often complicated, reflecting the intricacy of microstructure and strengthening mechanisms, pitfalls that are difficult to detect often exist. This paper discusses latent pitfalls that are common in mechanistic modeling or specific in this 9Cr-1Mo-V case development through using the ASME V&V 10 standard for evaluating credibility of modeling in materials engineering. Suggestions are also made for enhancing reliability of microstructure-based modeling.

Atomic-level Quantitative Analysis of Electronic Functional Materials in Aberration-corrected STEM

Abstract The stable sub-angstrom resolution of the aberration-corrected scanning transmission electron microscope (AC-STEM) makes it an advanced and practical characterization technique for all materials. Owing to the prosperous advancement in computational technology, specialized software and programs have emerged as potent facilitators across the entirety of electron microscopy characterization process. Utilizing advanced image processing algorithms promotes the rectification of image distortions, concurrently elevating the overall image quality to superior standards. Extracting high-resolution, pixel-level discrete information and converting it into atomic-scale, followed by performing statistical calculations on the physical matters of interest through quantitative analysis, represents an effective strategy to maximize the value of electron microscope images. The efficacious utilization of quantitative analysis of electron microscope images has become a progressively prominent consideration for materials scientists and electron microscopy researchers. This article offers a concise overview of the pivotal procedures in quantitative analysis and summarizes the computational methodologies involved from three perspectives: contrast, lattice and strain, as well as atomic displacements and polarization. It further elaborates on practical applications of these methods in electronic functional materials, notably in piezoelectrics/ferroelectrics and thermoelectrics. It emphasizes the indispensable role of quantitative analysis in fundamental theoretical research, elucidating the structure-property correlations in high-performance systems, and guiding synthesis strategies.

Cholesterol Based Organogelators in Environmental Remediation: Applications in Removal of Toxic Textile Dyes and Oil Spill Recovery.

Oil spills in the ocean and textile dyes have a catastrophic impact on the environment, economy, and ecosystem. Phase-selective organic gelator dye sorption and oil separation for oil adsorption should meet certain criteria such as facile synthesis, low cost, effective gelation, and recyclability. This study has discovered that an aliphatic chain synthetic amphiphile based on cholesterol can produce organogels in a variety of organic solvents. Numerous methods, such as X-ray diffraction, Fourier-transform infrared spectroscopy, high-resolution scanning electron microscopy, and rheology, have been used extensively to examine and describe these organogels. An environmentally acceptable technique for achieving hazardous dye separation is presented here. For the sustainable filtration of dye-contaminated water, a new, straightforward, one-step method driven by gravitational force has been employed by using a gel column. This approach has shown excellent stability and reusability with repeated use, and it is easily scalable for the effective removal of a wide range of hazardous dyes. Furthermore, because the oil fraction was absorbed in the gel, the study showed how well it might be used to apply phase selectivity to separate the oil-water mixture from marine accidents. Furthermore, a straightforward distillation method can be used to quantitatively recover the oils contained in the gel and gelator molecules in phase-selective gelation. This low-tech, ecofriendly, and highly effective method also offers valuable insights into the development of advanced materials for separating toxic dyes and oil from water.

Codoped germanene with 3p and 4p elements elements.

The relentless need for new materials to be used in electronic devices has opened new research directions in materials science. One of them involves using two-dimensional materials, among which there is current interest in using germanene. The heteroatom doping of germanene has been proposed as a possible approach to fine-tuning its electronic properties. However, this procedure is complicated because locating the dopants with a specific arrangement is challenging, thus achieving reproducibility. To avoid this problem, we propose the codoping of germanene to understand if dopants prefer to be agglomerated as observed for graphene or if they prefer to adopt a random disposition. Herein, we employed first-principles calculations to study 21 codoped germanene systems with one 3p (Al, Si, P, and S) and one 4p (Ga, As, and Se) element. Our results indicate that in the cases of AlP, AlS, GaP, GaS, GaAs, and GaSe codoped germanene, the dopants show a tendency to be located in specific lattice positions. The ortho disposition of dopants is preferred for AlP, AlS, GaP and GaS codoped germanene and their 4p counterparts GaAs and GaSe codoped germanene, and the materials showed interesting electronic propertiesmaking them suitable to develop germanene-based electronic materials. We utilized the M06-L, HSE06 methods accompanied by the 6-31G* basis sets to perform periodic boundary conditions calculations as implemented in Gaussian 09. The unit cells were sampled employing 100k-points for geometry optimizations and 2000k-points for electronic properties The ultrafine grid was employed. Results were visualized employing Gaussview 5.0.1. In addition to this, we performed B3LYP-D3 periodic calculations as implemented in CRYSTAL17.

Click metamaterials: Fast acquisition of thermal conductivity and functionality diversities

In material science, the development of metamaterials is crucial for advancing various technological applications. However, most metamaterial designs are still case by case due to lacking a fundamental mechanism for achieving reconfigurable thermal conductivities, largely hindering design flexibility and functional diversity. Inspired by the principles of click chemistry, known for its modular and efficient approach to creating molecular diversity, here we propose a universal concept of click metamaterials for fast realizing various thermal conductivities and functionalities. Tunable hollow-filled unit cells are constructed as the modified building blocks to change the thermal conductivity locally. Different configurations of unit cells with variable fill fractions can generate convertible thermal conductivities from isotropy to anisotropy, allowing click metamaterials to exhibit environment-free and reconfigurable thermal functionalities. The straightforward structures enable full-parameter regulation and simplify engineering preparation, making click metamaterials a promising candidate for practical use in other diffusion and wave systems.

Elucidating correlation-driven insulating state in an effective spin - ½ antiferromagnet NdVO4.

The Jeff = ½ state: a result of interplay of strong electronic correlations (U) with spin-orbit coupling (SOC) and crystal field splitting, offers a platform in the research of quantum materials. In this context, 4f rare-earth based materials offer a fertile playground. Here, strong experimental and theoretical evidences for a Jeff = ½ state is established in a 3D spin system NdVO4. Magnetic measurements show the signatures of a SOC driven Jeff = ½ state along with the presence of antiferromagnetic (AFM) interaction between Nd3+ moments, whereas, heat capacity reveals the presence of an AFM ordering around 0.8 K, within this state. An entropy of Rln2 (equivalent to J = ½) is released around 4 K which implies the presence of Jeff = ½ state at low temperatures. Total energy calculations within the DFT framework reflect the central role of SOC in driving the Nd3+ ions to host such a state with AFM correlations between them, which is in agreement with experimental results. Further, DFT + SOC calculations with and without the inclusion of U, points that electron-electron correlations give rise to the insulating state making NdVO4 a potential candidate for U-driven correlated Mott insulator.

Enhanced electro-optical properties of polymer dispersed liquid crystals doped with functional nanofibers for applications of efficient smart windows and advanced anti-counterfeiting

The development of polymer-dispersed liquid crystal (PDLC) capable of infrared smart tuning and displaying distinct information under ultraviolet, visible, and infrared light presents significant challenges. These challenges include the tuning of electro-optical properties and IR reflectivity, the preparation of complex patterns, and the display of different display states under various stimuli. In this work, nanofibers doped with alumina-zinc oxide nanoparticles (AZO NPs) and loaded with cesium tungstate nanoparticles (Cs0.33WO3 NPs) into PDLC not only enhanced their electro-optical properties but also added infrared shielding. Temperature regulation tests demonstrate that PDLC films can intelligently modulate infrared light reflection, offering superior shading and temperature regulation capabilities. PDLC smart windows integrated with nanofibers achieve a temperature coordination function, maintaining a temperature differential of 12.1 °C compared to standard PDLC. This significant enhancement underscores their potential for applications in thermally regulated smart windows. In addition, a full-wavelength anti-counterfeiting mode for PDLC was developed using a screen-printing strategy to display different information under various wavelengths of light. Noteworthily, the anti-counterfeiting system exhibits a bright fluorescent pattern under UV light, a scattering pattern under visible light, and an infrared-modulated pattern when viewed with an infrared detector. Furthermore, an advanced dynamic anti-counterfeiting mode with time response was created using nanofibers loaded with different concentrations of Cs0.33WO3 NPs. This advanced anti-counterfeiting material can be used as multimodal and dynamic anti-counterfeiting label, which greatly facilitates the development of novel anti-counterfeiting and optical sensing materials.

Multicomponent alloys designed to sinter

Powder sintering is a low-energy, net-shape processing route for many new products in the additive manufacturing space. We advance the viewpoint that for future manufacturing, alloys should be designed from materials science principles to sinter quickly at lower temperatures and with controlled final microstructures. Specifically, we illustrate the computational design of multinary Ni-base alloys, whose chemistries permit a low-temperature solid-state sintering scheme without any pressure- or field-assistance, as well as heat-treatability after sintering. The strategy is based on sequential phase evolutions designed to occur during sintering. The reactions involve rapid reorganization of matter to full density in cycles up to just 1200 °C, while conventional Ni alloys sintered in the solid-state require about ten times longer, or more than 250 °C degrees higher temperature. Our approach yields an alloy that benefits from precipitation hardening, has an increased strength ~\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim$$\\end{document}50% higher than solid-state processed commercial Ni alloys, and yet exhibits extensive plasticity beyond 35% uniaxial strain. The results point to a generalizable design scheme for many other alloys designed for solid-state powder processing that can enable greater value from additive manufacturing.

Applying the Techniques of Materials Science towards an Understanding of the Process of Canine Intervertebral Disc Degeneration

Applying the Techniques of Materials Science towards an Understanding of the Process of Canine Intervertebral Disc Degeneration

Two-Fold Oxidative Coupling of Furan with Indole Provides Modular Access to a New Class of Tetra-(hetero)arylated Furans with up to Four Different Substituents.

Highly arylated propeller-shaped heteroarenes constitute an intriguing class of molecular scaffolds for material science applications. Among these, tetraarylated furans demonstrate differentiated properties as compared to other similar heterocyclic cores. The synthetic complexity to access tetraarylated furans increases significantly with increasing number of different peripheral aryl groups. There are only a very limited number of methodologies available to access furans with four different (hetero)aryl substituents. Notably, none of these involve direct oxidative coupling on the furan core as the method of choice. Herein, we report the first methodology based on a sequential two-fold oxidative C-C coupling of furans with indoles to access bis(indolyl)furans (BIFs) - a new class of 'extremely congested' tetra-(hetero)arylated furans with up to four different substituents. The reaction is mediated by inexpensive, earth-abundant FeCl3.6H2O and displays high efficiency, wide substrate scope, modularity and aqueous compatibility. Moreover, we also present the first validation of the distinct aggregation-caused quenching (ACQ) property of the tetraarylated furans beyond only phenyls as peripheral groups and disclose new mechanistic underpinnings for the same.

Facile photopatterning of perfusable microchannels in hydrogels for microphysiological systems.

Perfusable hydrogels have garnered substantial attention in recent years for the fabrication of microphysiological systems. However, current methodologies to fabricate microchannels in hydrogel platforms involve sophisticated equipment and techniques, which hinder progress of the field. In this protocol, we present a cost-effective, simple, versatile and ultrafast method to create perfusable microchannels of complex shapes in photopolymerizable hydrogels. Our method uses one-step UV photocross-linking and a photomask printed on inexpensive transparent films, to photopattern both synthetic (PEG-norbornene) and natural (hyaluronic acid-norbornene) hydrogels in just 0.8 s. Moreover, these perfusable hydrogels are fully integrated into a custom-made microfluidic device that allows continuous fluid perfusion when connected to an external pump system. This methodology can be easily reproduced by professionals with basic laboratory skills and a fundamental knowledge of polymers and materials science. In this protocol, we demonstrate the functionality of our photopatterned hydrogels by seeding human endothelial cells into the microchannels, culturing them under dynamic conditions for 7 d, and exposing them to inflammatory stimuli to elicit cellular responses. This highlights the versatility of our platform in fabricating microphysiological systems and different microenvironments. The fabrication of perfusable channels within the hydrogels, including the fabrication of the microfluidic devices, requires ~3 d. The development of the cell-seeded microphysiological system, including the stimulation of cells, takes ~7 d. In conclusion, our approach provides a straightforward and widely applicable solution to simplify and reduce the cost of biofabrication techniques for developing functional in vitro models using perfusable three-dimensional hydrogels.

A comprehensive data network for data-driven study of battery materials

ABSTRACT Data-driven material research for property prediction and material design using machine learning methods requires a large quantity, wide variety, and high-quality materials data. For battery materials, which are commonly polycrystalline, ceramics, and composites, multiscale data on substances, materials, and batteries are required. In this work, we develop a data network composed of three interlinked databases, from which we can obtain comprehensive data on substances such as crystal structures and electronic structures, data on materials such as chemical composition, structure, and properties, and data on batteries such as battery composition, operation conditions, and capacity. The data are extracted from research papers on solid electrolytes and cathode materials, selected by screening more than 330 thousand papers using natural language processing tools. Data extraction and curation are carried out by editors specialized in material science and trained in data standardization.

A General Enantioselective α-Alkyl Amino Acid Derivatives Synthesis Enabled by Cobalt-Catalyzed Reductive Addition.

Enantioenriched unnatural amino acids represent a prevalent motif in organic chemistry, with profound applications in biochemistry, medicinal chemistry, and materials science. Herein, we report a cobalt-catalyzed aza-Barbier reaction of dehydroglycines with unactivated alkyl halides to afford unnatural α-amino esters with high enantioselectivity. This catalytic reductive alkylative addition protocol circumvents the use of moisture-, air-sensitive organometallic reagents, and stoichiometric chiral auxiliaries, enabling the conversion of a variety of primary, secondary, and even tertiary unactivated alkyl halides to α-alkyl-amino esters under mild conditions, thus leading to broad functional group tolerance. The expedient access to biologically active motifs demonstrates the practicality of this protocol by reducing the number of synthetic steps and enhancing the reaction efficiency.

Molecular dynamics simulation of interaction between NaOH solution and AgCo/C electrode

Using carbon-supported silver-cobalt (AgCo/C) electrode as the electrocatalyst in fuel cell (FC), it has good electrocatalytic performance for NaOH solution (aq), however, the mechanism of the interaction between aq and AgCo/C electrode is not clear. In this work, layered models (L1, L2, L3) of the interaction between them were constructed, and molecular dynamics (MD) simulation was carried out using Materials Studio (MS) software to explore their interaction rule and reveal the interaction mechanism. At 298 K, the results showed that the interaction force between aq and AgCo/C electrode is mutually attracted, and the order of the absolute value of the interaction energy is L3 ≫ L2 > L1, indicating that the electrocatalytic effect of the composite electrode with 4 carbon-supporter layers is obviously stronger than that of the composite electrode with 3 and 2 carbon-supporter layers, which is consistent with the experimental conclusion. Their interaction inhibits the diffusion of Na+ ions and water molecules− in aq. There is no bonding between AgCo(AgCo/C)-OH−(aq) and AgCo(AgCo/C)-Na+(aq) in the short-range region, while there is non-bonding in the long-range region. Bond formation is a common occurrence between H2O(aq)-OH−(aq) in the short-range region, but it is weak in the long-range region. Research and development of cathode materials for fuel cells will be supported by these theoretical results.

A triple-mode strategy combining low-temperature photothermal, photodynamic, and chemodynamic therapies for treating infectious skin wounds.

The skin is the first natural barrier of the human body. Bacterial infections severely hinder the healing process of skin wounds and pose a great threat to human health. Therefore, it is particularly urgent to develop new antimicrobial strategies for bacterial pathogen clearance and wound healing. In this study, a metal-organic framework (MOF), Fe-MIL88B-NH2, was incorporated with the photosensitizer indocyanine green (ICG) to construct composite nanoparticles (MOF@ICG NPs) with multiple antibacterial activities. Under mild near-infrared (NIR) irradiation, the photosensitizer ICG in the MOF@ICG NPs undergoes photothermal conversion (∼45 °C) and photodynamic reactions to generate heat and singlet oxygen (1O2). In addition, the Fenton reaction of the NPs with hydrogen peroxide (H2O2) in the bacterial infection microenvironment resulted in the generation of hydroxyl radicals (˙OH), thus achieving the three-mode combination of low-temperature photothermal therapy (PTT)/photodynamic therapy (PDT)/chemodynamic therapy (CDT). The in vitro experimental results showed that MOF@ICG MPs had excellent antibacterial properties and good cytocompatibility, with some ability to promote the migration of L-929 fibroblasts. Furthermore, under NIR irradiation, MOF@ICG NPs could significantly kill bacteria and promote skin wound healing according to the results of animal experiments. The wound healing rate reached 87.1% after 7 days of treatment. The research results break through the limitations of single-mode antibacterial technology and provide certain theoretical guidance and technical support for the research and development of new antibacterial materials.

Effect of alkali treatment and fungal degradation on the nanostructure and cellulose arrangement in Scots pine cell walls – A neutron and X-ray scattering study

Research on new conservation treatments for historical wood requires considerable amounts of appropriate wood material, which is hard to acquire. Thus, we produced biologically and chemically degraded model wood that could be used as a representative material in future research on consolidating agents. Using chemical composition determinations, we found that fungal decay targeted mainly polysaccharides, while alkaline treatment mostly reduced hemicelluloses and lignin content. X-ray and neutron scattering showed that all decayed samples had increased disorder in microfibril alignment and larger elementary fibril cross-sections, and alkaline-treated samples had much larger elementary fibril spacing compared to those decayed by fungi. These nanoscale and chemical differences correlate with physical property changes. For example, decreased cellulose crystallinity and increased disorder of the microfibrils in degraded cell walls likely contribute to the lower elastic moduli measured for these cell walls. The obtained data improves understanding of how degradation alters wood structures and properties across length scales and will be valuable for future studies focusing on archeological wood. Moreover, it leads to the conclusion that it is more appropriate to develop treatments that consider not only spatial variability and degree of wood degradation but also the corresponding molecular and nanoscale changes in the cell walls.

Microbial Mineralization with Lysinibacillus sphaericus for Selective Lithium Nanoparticle Extraction.

Lithium is a critical mineral in a wide range of current technologies, and demand continues to grow with the transition to a green economy. Current lithium mining and extraction practices are often highly ecologically damaging, in part due to the large amount of water and energy they consume. Biomineralization is a natural process that transforms inorganic precursors to minerals. Microbial biomineralization has potential as an ecofriendly alternative to current lithium extraction techniques. This work demonstrates Lysinibacillus sphaericus biomineralization of lithium chloride to lithium hydroxide. Quantitative analysis of biomineralized lithium via the 2-(2-hydroxyphenyl)-benzoxazole fluorescence assay reveals significantly greater recovery with L. sphaericus than without. Furthermore, L. sphaericus biomineralization is specific to lithium over sodium. The nanoparticles produced were further characterized via Fourier transform infrared and transmission electron microscopy analysis as crystalline lithium hydroxide, which is an advanced functional material. Finally, ESI-LC/MS was used to identify several proteins involved in this microbial biomineralization process, including the S-layer protein. Through the isolation of L. sphaericus ghosts, this work shows that the S-layer protein alone plays a critical role in the biomineralization of crystalline lithium hydroxide nanoparticles. Through this study of microbial biomineralization of lithium with L. sphaericus, there is potential to develop innovative and environmentally friendly extraction techniques.

Fabrication of novel metal oxide nanosheets-decorated carbon nanofibers for highly efficient removal of ultra-small nanoplastics

The extensive use of plastic products leads to white pollution and the formation of nanoplastics (NPs) through physicochemical processes. Due to their large specific surface area and small size, NPs can easily enter the human body, posing significant health risks. In this work, we prepared NiFe2O4 nanosheets-decorated carbon nanofibers (NiFe2O4@CNF) via electrospinning, carbonization, hydrothermal growth, and low-temperature calcination for NPs removal. Characterization techniques, including SEM, FTIR, XRD, XPS, and zeta potential analysis, assessed the surface morphology, functional groups, crystal structure, chemical composition, and surface charge of the NiFe2O4@CNF adsorbent. Adsorption kinetics, isotherms, and thermodynamics studies demonstrated that the adsorption process follows pseudo-second-order kinetics and the Langmuir model, indicating chemisorption and monolayer adsorption with a maximum adsorption capacity of 147.842 mg/g. Thermodynamic data confirmed that the reaction is spontaneous and endothermic. Additionally, the practical application of the adsorbent was evaluated by studying the effects of pH, competing ions, and different water bodies on adsorption behavior, all showing high removal efficiency and robust performance. Computer simulations further provided understanding into the driving forces and the binding sites of adsorption. These results underscore the efficacy of NiFe2O4@CNF for NPs removal and provide critical insights for designing advanced environmental remediation materials.

Learning macroscopic equations of motion from dissipative particle dynamics simulations of fluids

Macroscopic descriptions of both natural and engineered materials usually include a number of phenomenological parameters that have to be estimated from experiments or large-scale microscopic simulations. When dealing with advanced complex materials, these descriptions are sometimes not a priori available or not even known. Using sparsity-promoting techniques one can extract macroscopic dynamic models directly from particle-based simulations. In this work, we showcase such an approach on a simple fluid and test its robustness. We introduce a novel measure for automatic macroscopic model selection that combines stability and accuracy of a model. Using this measure and employing only a few physics-based assumptions, we are able to infer both the mass continuity equation and an equation for the conservation of linear momentum. Moreover, the extracted phenomenological and non-phenomenological parameters agree well with their numerically measured values and the well-known semi-empirical estimates. The presented model selection framework can be applied to simulations or experimental data of more complex systems, described in general by a rich set of coupled nonlinear macroscopic equations.