Materials Science Research Articles

Uncertainty Based Machine Learning-DFT Hybrid Framework for Accelerating Geometry Optimization.

Geometry optimization is an important tool used for computational simulations in the fields of chemistry, physics, and material science. Developing more efficient and reliable algorithms to reduce the number of force evaluations would lead to accelerated computational modeling and materials discovery. Here, we present a delta method-based neural network-density functional theory (DFT) hybrid optimizer to improve the computational efficiency of geometry optimization. Compared to previous active learning approaches, our algorithm adds two key features: a modified delta method incorporating force information to enhance efficiency in uncertainty estimation, and a quasi-Newton approach based upon a Hessian matrix calculated from the neural network; the later improving stability of optimization near critical points. We benchmarked our optimizer against commonly used optimization algorithms using systems including bulk metal, metal surface, metal hydride, and an oxide cluster. The results demonstrate that our optimizer effectively reduces the number of DFT force calls by 2-3 times in all test systems.

Materials Science and Environmental Applicability

Materials Science and Environmental Applicability

Multi‐Color Optical Quasiparticle Laser Source Formed of a Pr3+ Doped Fiber Laser with a Dual‐Output Coupling Geometry

AbstractThe generation of multicolor (523, 605, 637, and 719 nm) optical quasiparticles (bimerons and skyrmions with topologically protected polarization textures) from a diode‐pumped Pr3+‐doped fluoro‐aluminate glass (Pr3+: WPFG) fiber simply with intra‐cavity plano‐convex lens and wedge‐plate and without any wavefront control elements, such as a spatial light modulator is demonstrated. This robust and cost‐saving system efficiently produces Bloch‐, Néel‐, and anti‐quasiparticles with high mode purity. In particular, the green optical quasiparticles will have the potential to explore many applications in materials science and biotechnologies.

Resolving Structures of Paramagnetic Systems in Chemistry and Materials Science by Solid‐State NMR: The Revolving Power of Ultra‐Fast MAS

AbstractUltra‐fast magic‐angle spinning (100+kHz) has revolutionized solid‐state NMR of biomolecular systems but has so far failed to gain ground for the analysis of paramagnetic organic and inorganic powders, despite the potential rewards from substantially improved spectral resolution. The principal blockages are that the smaller fast‐spinning rotors present significant barriers for sample preparation, particularly for air/moisture‐sensitive systems, and are associated with low sensitivity from the reduced sample volumes. Here, we demonstrate that the sensitivity penalty is less severe than expected for highly paramagnetic solids and is more than offset by the associated improved resolution. While previous approaches employing slower MAS are often unsuccessful in providing sufficient resolution, we show that ultra‐fast 100+kHz MAS allows site‐specific assignments of all resonances from complex paramagnetic solids. Combined with more reliable rotor materials and handling methods, this opens the way to the routine characterization of geometry and electronic structures of functional paramagnetic systems in chemistry, including catalysts and battery materials. We benchmark this approach on a hygroscopic luminescent Tb3+ complex, an air‐sensitive homogeneous high‐spin Fe2+ catalyst, and a series of mixed Fe2+/Mn2+/Mg2+ olivine‐type cathode materials.

Cobalt-Hydride-Catalyzed Alkene-Carboxylate Transposition (ACT) of Allyl Carboxylates.

The alkene-carboxylate transposition (ACT) of allyl carboxylates is one of the most atom-economic and synthetically reliable transformations in organic chemistry, as allyl carboxylates are versatile synthetic intermediates. Classic ACT transformations, including [3,3]-sigmatropic rearrangement and transition metal-catalyzed allylic rearrangement, typically yield 1,2-alkene/1,3-acyloxy shifted products through a two-electron process. However, position-altered ACT to produce distinct 1,3-alkene/1,2-acyloxy shifted products remains elusive. Here, we report the first cobalt-hydride-catalyzed ACT of allyl carboxylates, enabling access to these unprecedented 1,3-alkene/1,2-acyloxy shifted products via a 1,2-radical migration (RaM) strategy. This transformation demonstrates broad functional group tolerance, is suitable for late-stage modification of complex molecules, and is amenable to gram-scale synthesis. It also expands the reaction profiles of both allyl carboxylates and cobalt catalysis. Preliminary experimental and computational studies suggest a mechanism involving metal-hydride hydrogen atom transfer (MHAT) and the 1,2-RaM process. This reaction is expected to serve as the basis for the development of versatile Co-H-catalyzed transformations of allyl carboxylates, generating a wide array of valuable building blocks for synthetic, medicinal, and materials chemistry.

Surface Nanopatterning and Structural Coloration of Liquid Metal Gallium Through Hypergravity Nanoimprinting

AbstractNanoscale structuring of gallium‐based liquid metals has emerged as a promising approach for generating unique properties and functionalities in advanced materials and devices. However, their exceptionally high surface tension presents significant challenges for achieving surface nanostructuring using conventional fabrication techniques. Here, a hypergravity nanoimprinting method is introduced, which harnesses horizontal centrifugation to generate hypergravity fields that drive liquid gallium into nanoscale cavities on an elastic polymer stamp surface at subzero temperatures, where it solidifies and preserves imprinted features down to 100 nm lateral resolution. This surpasses previous limits of gallium patterning, enabling phenomena such as iridescent structural colors with a wide range of hues and high saturation. Numerical simulations reveal the intricate fluid dynamic behaviors and interfacial interactions during the imprinting process, providing valuable insights for process optimization and control. By synergistically combining advanced soft lithography techniques with the reversible solid‐liquid phase transition properties of liquid metals, hypergravity nanoimprinting offers a practical nanofabrication approach, facilitating the development of next‐generation nanoscale gallium devices with finely structured nanofeatures across diverse application domains, such as nanoelectronics and photonic metamaterials.

Abstract Su1107: Online educational film depiction of opioid overdose causing cardiac arrest

Introduction: Opioid overdose (OD) is a growing cause of cardiac arrest in the US, spurred by the rise of illegally manufactured fentanyl and analogs. Naloxone is a reversal agent that can be administered by bystanders. Intra-nasal (IN) naloxone is now widely available in pharmacies across the US. Despite increasing access, minority populations remain disproportionately affected by drug overdose deaths. There are many free online opioid OD educational videos. Digital media can be a powerful tool for mass education, but the effectiveness is unknown. Research Question and Aims: The goal of this study was to evaluate online opioid overdose videos for content and gender/racial representation. Methods: We performed an online search with the query “how to give Narcan” (popular term for IN naloxone). Results were limited to the first 52 Google, 50 YouTube, and 60 TikTok videos. Exclusion criteria included: animal victim, duplicate, or no mention of naloxone. For each video, 2 reviewers evaluated content and identified the race and gender of featured characters. Disagreements were resolved through consensus. The race and gender of featured characters was compared using a two proportion z-test. Inter-rater reliability (IRR) for each data point was calculated using the arithmetic mean of Cohen's kappa. Results: Of 121 videos, the majority (87.6%) mentioned naloxone as a treatment for opioid OD; 62.8% provided instruction on how to administer IN naloxone, and 4.1% featured a testimonial. Only 43.0% provided a realistic visual demonstration of IN naloxone administration; 25.6% showed a realistic re-enactment of opioid overdose, and even fewer (19.0%) showed the dramatic response to naloxone. IRR was high for all categories. Videos predominantly featured white compared to non-white-appearing characters in both the victim (75.5 v. 17.8%, p< 0.00001) and rescuer roles (72.5 v 21.6%, p<0.00001). The rescuer gender was evenly distributed male v. female; however, the victim was more often male (77.8% v. 22.2%, p<0.00001). Conclusion: Most online opioid OD videos provide instructions on how to use IN naloxone, but do not feature realistic depictions of cardiac arrest caused by opioid OD, naloxone treatment, or response. There is a significant lack of racial diversity in these videos. Digital materials are needed with improved diversity and which teach learners how to RECOGNIZE and respond to opioid OD.

Semantic Features of the Word Qonyr (Brown): Conceptual Analysis of Two Separate Works

It is known that the Aesopian language was used in the works of many writers to convey the parable. This article shows how and why Kazakh writers used the Aesopian language during the Soviet era. The study analyzes the contextual and symbolic meanings of the word qonyr, one of the most important concepts of Kazakh cognition. The research material was taken from O. Bokey’s novel Kajdasyn, Kaska Kulynym? (Where Are You, My Foal with a Star on His Forehead?), and a poem by Zhumeken Nazhimedenov titled “Kyran-Kiya” (“Mountain Eagle”). A conceptual research method in modern linguistics was chosen for data analysis. As a result, new implicit meanings of the word qonyr (“brown”) were revealed, such as “longing”, “sadness”, and “nobility”. The juxtaposition of these meanings with Soviet ideology is presented. The results and conclusions of the study are a kind of contribution to studies in cognitive linguistics and decolonization.

Reductive Photocatalytic Proton-Coupled Electron Transfer by a Zirconium-Based Molecular Platform.

Reductive proton-coupled electron transfer (PCET) has important energetic implications in numerous synthetic and natural redox processes. The development of catalytic systems that can mediate such transformations has become an attractive target, especially when light is used to generate the reactive species towards solar-to-chemicals conversion. However, such approach becomes challenged by kinetic competition with H2 evolution. Here we describe the excited state reactivity of a molecular Zr-based platform under visible light irradiation for the efficient reduction of multiple bonds. Mechanistic investigations shine light on a charge separation process that colocalizes an excited electron and an acidic proton to promote selective PCET. We further leveraged this reactivity for the photocatalytic reduction of a variety of organic substrates. Our results demonstrate the promise of this molecular platform to design strong photocatalytic PCET mediators for reductive transformations. More broadly, we also show the potential relevance of PCET mechanisms in the (photo)redox chemistry of Zr-based molecular materials.

Ethnic fermented foods of the world: an overview

AbstractThe origins of traditional fermented foods and the types and characteristics of fermented foods by region are reviewed. Fermented foods are classified into alcohol fermentation, acid fermentation, carbon dioxide (bread) fermentation, and amino acid/peptide fermentation, and related fermentation technologies for each region are introduced. The raw materials, microorganisms involved, and usage of ethnic fermented foods are reviewed and compared one another. The beginning of food fermentation technology is related to the invention and use of earthenware, and Northeast Asia is presumed to be one of the birth places. During the period of primitive pottery culture (8000–3000 BCE) on the Korean Peninsula and the coastal region of Korea Strait, boiling technology of food materials using pottery and salt manufacturing technology from seawater were developed, and at the same time, alcohol fermentation using grains and salt-fermentation of fish and vegetables emerged. In the West, where people were nomads, a roasting/grilling culture was continued for a long time, and technologies for fermenting fruit wine and milk products such as cheese and yogurt were developed. As a result, fermentation was mainly used for enhancing the taste of plant foods in the East, while for extending the shelf life of animal foods in the West. The production of salty and meaty flavors from soybeans and marine products by fermentation in East Asia is a technology that increases the value of low-quality proteins.

Achieving a framework of the circular economy in urban transport infrastructure projects: a meso-scale perspective

Urban infrastructure development is one principal way people are transforming the natural world and their living conditions. It is important for humanity, but it can also cause major impacts to the environment, such as huge amounts of solid waste and CO2 emissions. Considering this, the circular economy (CE) is a promising alternative to the traditional “make, use, and dispose” linear economy model. However, as a strategy for sustainable development (SD), the CE is still in its infancy in the urban transport infrastructure sector. Therefore, this article aims to guide the implementation of CE during transport infrastructure projects. To achieve this goal, a literature review and case study were adopted as the research methods. After reviewing existing well-established CE frameworks, the iReSOLVE (implement, Regenerate, Share, Optimize, Loop, Virtualize, Exchange) framework is recognized as the most comprehensive one. Upon it, an analytical framework containing specific-related aspects of CE in urban transport infrastructure projects (which belongs to meso-scale) is proposed (coined as the 4Wh-iReSOLVE framework). The 4Wh means Who, When, Where, and What. The proposed framework offers insight into potential CE activities for transport infrastructure projects and assists in assessing the performance and impacts of CE of these projects to cover the gap of the neglected meso-scale. Ten circular viaduct project initiatives in the Netherlands are used as case analyses with the 4Wh-iReSOLVE framework. The results present the highlights of the circular viaduct initiatives in the Netherlands, with CE activities categorized into five groups (design-related strategies, general CE strategies, implementation, management, and related digital technologies and materials, as well as environmental sustainability). As verified by several experts of the projects studied, it can be concluded that the 4Wh-iReSOLVE framework is suitable for transport infrastructure project CE analyses and implementations. It can potentially be a suggested guideline in future policy documents.

Evaluating and improving the predictive accuracy of mixing enthalpies and volumes in disordered alloys from universal pretrained machine learning potentials

The advent of machine learning in materials science opens the way for exciting and ambitious simulations of large systems and long time scales with the accuracy of calculations. Recently, several pretrained universal machine learned interatomic potentials (UPMLIPs) have been published, i.e., potentials distributed with a single set of weights trained to target systems across a very wide range of chemistries and atomic arrangements. These potentials raise the hope of reducing the computational cost and methodological complexity of performing simulations compared to models that require for-purpose training. However, the application of these models needs critical evaluation to assess their usability across material types and properties. In this work, we investigate the application of the following UPMLIPs: MACE, CHGNET, and M3GNET to the context of alloy theory. We calculate the mixing enthalpies and volumes of 21 binary alloy systems and compare the results with DFT calculations to assess the performance of these potentials over different properties and types of materials. We find that the small relative energies necessary to correctly predict mixing energies are generally not reproduced by these methods with sufficient accuracy to describe correct mixing behaviors. However, the performance can be significantly improved by supplementing the training data with relevant training data. The potentials can also be used to partially accelerate these calculations by replacing the structural relaxation step. Published by the American Physical Society 2024

Structural Modifications of CdS/Graphene Oxide with Ionic Dopants of Fe/Ag for Degradation of Methylene Blue

AbstractGlobal demand for pollution removal agents requires advanced materials to provide a good protocol to keep clean water resources. The composition of CdS was modified with ionic dopants including iron (Fe) and silver (Ag) and is incorporated into graphene oxide (GO) nanoparticles. The obtained compositions are CdS, Fe-CdS, Ag-CdS, CdS@GO, Fe-CdS@GO, and Ag-CdS@GO that have been fabricated by the co-precipitation method and examined by several techniques to estimate the morphological, optical, and structural properties using TEM, SEM, UV–Vis analysis, and XRD. The crystallite size of the CdS@Go was measured using the Williamson-Hall (W–H) method and was found to be around 28.6 nm. Furthermore, the a-axis was found to be 5.78 Å and 5.80 Å for cubic crystals and the a-axis achieved 14.28 to 14.24 Å for an orthorhombic crystal of CdS, respectively. The average roughness varied from 32.30 ± 3.3 to 66.65 ± 10.9 nm for CdS and Ag-CdS@GO. The degradation of methylene blue (MB) is increased from 75.56, 73.87, 76.01, 81.53, 89.34, and 91.68% for CdS, Fe-CdS, Ag-CdS, CdS@GO, Fe-CdS@GO, and Ag-CdS@GO after 60 min of exposure under visible light irradiation. The pseudo-first-order constant (Kapp) is increased from 4.4 × 10−3 to 39.4 × 10−3 min−1 for CdS and Ag-CdS@GO.

Optimizing Computation: A Biomimicry Design Spiral Approach to Algorithm Development

The increasing focus on biomimicry in the built environment shows that designers are becoming more conscious of the opportunities that nature presents for enhancing human and systemic functions. The field of advanced material technology has extensively used biomimicry. Nevertheless, there has been little in-depth discussion of its possibilities in environmentally conscious building practices. Numerous branches of the social and natural sciences have had an impact on the field of architecture; at the present time, biological principles are finding their way into design processes. From the earliest days of bio-architectural movements to the most recent ones, bioinspiration has shaped architectural practices towards a wide range of new methods. Nevertheless, the line between architectural bioinspiration that just mimics natural forms and the genuine comprehension of biological principles—the bedrock of sustainable development—is blurry when it comes to biomimicry. One of the biggest obstacles is the lack of cross-disciplinary cooperation between architects and biologists, which is exacerbated by the vast knowledge gap that exists between the creative process of building design and the scientific disciplines that pertain to biology. All sorts of spiral pathways, their properties, and how to use them to build and enhance other optimisation methods are described in great detail.

Utilizing Machine Learning for Predictive Maintenance of Climate-Resilient Highways through Integration of Advanced Asphalt Binders and Permeable Pavement Systems with IoT Technology

This review provides a comprehensive examination of the application of advanced technologies in enhancing the climate resilience of highway infrastructure. The focus is on the integration of machine learning for predictive maintenance, the use of Internet of Things (IoT) devices for real-time monitoring, and the deployment of advanced materials, specifically permeable pavements and modified asphalt binders. The review explores how these technologies work synergistically to create durable, low-maintenance highway systems capable of withstanding extreme environmental conditions. Advanced asphalt binders, such as those modified with styrene-butadiene-styrene (SBS) and nanomaterials, are discussed for their enhanced flexibility, thermal stability, and load-bearing capacity. Additionally, the environmental and structural benefits of permeable pavements are highlighted, particularly their role in stormwater management and reduction of urban heat island effects. Several case studies highlight the successful implementation of these technologies in diverse geographical and climatic conditions, including North Carolina, Australia, and Raipur, India. These cases illustrate the adaptability and environmental benefits of permeable pavements in managing stormwater, recharging groundwater, and mitigating the urban heat island effect. By synthesizing recent advancements and practical implementations, this review emphasizes the importance of integrating predictive technologies and resilient materials to develop sustainable, climate- adaptive highway systems. These insights offer a foundation for future infrastructure policies and technological innovations aimed at enhancing the durability and environmental sustainability of highway networks.

Application of Product of Vitrification of Asbestos-Cement Waste and CRT Glass Cullet as Reinforcing Phase in Surface Composites Produced by FSP Method

In this study, the vitrification of asbestos-cement waste (ACW) and glass cullet from cathode-ray tubes (CRTs) was performed. The resulting product of vitrification from the abovementioned waste was used as the reinforcing phase in a composite with the AA7075 alloy matrix. The composite was made by means of the FSP (friction stir processing) method. The main aim of this work was to determine whether the product of the vitrification can be utilized as the reinforcing phase in the composite. The tests show that introducing the vitrification product into the composite matrix increases both the hardness of the material and its wear resistance. The composite was characterized by a 39% higher hardness and 30.4% higher wear resistance compared to the initial AA7075 alloy. The changes in the properties were caused by strong refinement of the grains, but primarily by the presence of the hard particles of the reinforcing phase in the composite matrix. This research demonstrates that vitrified material, thanks to its properties, can constitute a full-value reinforcing material that can ultimately replace more expensive engineering materials in composites.

Parameter Optimization for Dissimilar Aluminum Alloys Joined Using Friction Stir Additive Manufacturing: A Screening Study

ABSTRACTDue to the requirement for better strength‐to‐weight ratios, the utilisation of aluminum alloys is rapidly expanding. Lightweight components are of utmost importance in most industries, particularly in transportation, aviation, maritime, automotive, and other industries. These lightweight engineering materials are hard to be joined utilising traditional fusion joining techniques, necessitating the development of alternative joining techniques. The novel friction‐stir additive manufacturing (FSAM) technique, based on the concept of friction stir welding (FSW), can be used to combine aluminum alloys additively in their solid state. This work examines the effects of several process parameters (tool rotational speed, tool tilt angle, and tool transverse speed) on tensile strength and hardness using a 3‐factor L9 Taguchi designed experiment. Three cases were explored, one were AL 6061 was welded to AL 7075, one where AL 7075 was welded to AL 6061, and one where the data were mixed to get an “average” effect representative of large additively manufactured parts. A detailed ANOVA (including both main effects and interactions analyses) provided clear guidance on the optimization of the parameters for several objectives. This work will contribute to the development and wider use of FSAM in both industrial and academic research settings by providing a useful dataset and clear parameter selection guidance. The results of this research indicate that the FSAM methodology could be utilized to fabricate large defect‐free structures, which can be a suitable replacement for the traditional Al6061 material used in automotive and aerospace sectors.

Shape design optimization of a flat endmill tool

AbstractAmong the many possible metal‐cutting processes, milling is regarded as one of the most widely applied processes to machine different engineering materials productively. During the milling process, there is relative motion between the endmill tool and the workpiece. Energy is required to drive the cutting force used by the tool in separating the chips from the workpiece. Several studies have focused on the effects of milling process parameters on the cutting force, for instance by varying the cutting parameters, machining properties and the extent of cooling/lubrication. Other studies have explored the influence of tool geometry and material properties on the cutting force. Results from these studies have brought about improvements in the design of milling machinery and tools. The current study presents a novel automated approach for tool geometry optimization which is fully coded in Matlab. An automated and parametrized endmill design procedure was created featuring input parameters such as rake angle, relief angle, clearance angle and helix angle, all of which have been shown, through numerous studies, to influence cutting forces. The parameters were here used to generate the shape profile for one cutting edge of a flat endmill. This cutting edge profile is next copied and rotated, as per the design's pitch angle, to form the complete set of cutting flutes for the flat endmill. Next, the surface defined by the completed profile is meshed using quadrilateral elements. The 3D endmill design is then formed by extruding, and twisting as per the helix angle, this quadrilateral mesh to form a solid hexahedral mesh. Finally, an automated iterative optimization process was defined, featuring the above parametrized design process coupled with Abaqus‐based finite element simulation of the milling process. The expected result is that the proposed optimization procedure will be able to identify the endmill design parameters which minimize the cutting force. At the completion of the optimization, a minimized maximum resultant cutting force value is obtained from using the newly optimized endmill. The resultant cutting force was reduced by 17.6%. It is anticipated that the automated design, meshing and simulation‐driven optimization approach is generalizable to other tool design variations.

Comparative Analysis of Mechanical and Morphological Properties of Cordenka and Ramie Fiber-Reinforced Polypropylene Composites

The depletion of conventional materials and their adverse environmental impacts have prompted a shift toward sustainable alternatives in composite materials engineering. In pursuit of this objective, this study investigated the mechanical properties of polypropylene matrix composites reinforced with Cordenka, an artificial cellulose fiber, and compared them to those reinforced with ramie, a natural cellulose fiber. Continuous strand composites were developed using the Multi-Pin-assisted Resin Infiltration (M-PaRI) process. The strands were subsequently sectioned into 15 mm lengths and injection-molded into dumbbell and strip specimens for mechanical characterization. The results showed that 20 wt% Cordenka/PP composites exhibited a tensile strength of 68.7 MPa, 2.04 times higher than neat PP and 1.66 times greater than the 20 wt% ramie/PP composites. Impact testing further demonstrated that Cordenka/PP composites absorbed 2 to 2.5 times more impact energy than ramie/PP composites, regardless of the presence of notches. Fiber length analysis indicated that Cordenka fibers maintained their length beyond the critical fiber length, allowing for efficient stress transfer and acting as a more effective reinforcement compared to ramie fibers, which were below this threshold. Consequently, the Cordenka/PP composites exhibited significantly enhanced mechanical performance. Scanning electron microscopy (SEM) analysis revealed fewer fiber pullouts in ramie-reinforced composites, suggesting superior interfacial adhesion to the PP matrix, although it did not translate to higher mechanical properties. These findings underscore the potential of Cordenka as a sustainable alternative to synthetic, non-biodegradable fibers in PP composites, providing improved mechanical properties and promising prospects for advanced composite applications.

Advances in machine learning methods in copper alloys: a review.

Advanced copper and copper alloys, as significant engineering structural materials, have recently been extensively used in energy, electron, transportation, and aviation domains. Higher requirements urge the emergence of high-performance copper alloys. However, the traditional trial-and-error experimental observations and computational simulation research used to design and develop novel materials are time-consuming and costly. With the accumulation of material research and rapid development of computational ability, the thorough application of material genome engineering has sped up the development of novel materials and facilitates the process of systematic engineering application. This review summarizes the benefits of data-driven machine learning techniques and the state of the art of machine learning research in the area of copper alloys. It also displays the widely used computational simulation approaches (e.g., the first-principles calculation, molecular dynamics simulation, phase-field simulations, and finite element analysis) and their combined applications in material design and property prediction. Finally, the limitations of machine learning research methods are outlined, and future development directions are proposed.