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npj Computational Materials 2023年第1期9卷 1661-1674页

作者： G.Vazquez S.Chakravarty r.Gurrola r.arróyave Department of Materials Science and Engineering Texas A&M UniversityCollege Station 77843 TXUSA Department of Mechanical Engineering Texas A&M UniversityCollege Station 77843 TXUSA Department of Industrial and Systems Engineering Texas A&M UniversityCollege Station 77843 TXUSA

High Entropy Alloys(HEAs)are composed of more than one principal element and constitute a major paradigm in metals *** HEA space is vast and an exhaustive exploration is ***,a thorough estimation of the phases present in the HEA is of paramount importance for alloy *** Learning presents a feasible and non-expensive method for predicting possible new HEAs on-the-fly.A deep neural network(DNN)model for the elemental system of:Mn,Ni,Fe,Al,Cr,Nb,and Co is developed using a dataset generated by high-throughput computational thermodynamic calculations using *** features list used for the neural network is developed based on literature and freely available databases.A feature significance analysis matches the reported HEAs phase constitution trends on elemental properties and further expands it by providing so far-overlooked *** final regressor has a coefficient of determination(r^(2))greater than 0.96 for identifying the most recurrent phases and the functionality is tested by running optimization tasks that simulate those required in alloy *** DNN developed constitutes an example of an emulator that can be used in fast,real-time materials discovery/design tasks.

关键词： alloy neural network

Bayesian optimization with active learning of design constraints using an entropy-based approach

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npj Computational Materials 2023年第1期9卷 1866-1879页

作者： Danial Khatamsaz Brent Vela Prashant Singh Duane D.Johnson Douglas Allaire raymundo arróyave J.Mike Walker’66 Department of Mechanical Engineering Texas A&M UniversityCollege StationTX 77843USA Department of Materials Science and Engineering Texas A&M UniversityCollege StationTX 77843USA Ames Laboratory U.S.Department of EnergyIowa State UniversityAmesIA 50011USA Department of Materials Science&Engineering Iowa State UniversityAmesIA 50011USA Department of Industrial and Systems Engineering Texas A&M UniversityCollege StationTX 77843USA

The design of alloys for use in gas turbine engine blades is a complex task that involves balancing multiple objectives and *** alloys must be ductile at room temperature and retain their yield strength at high temperatures,as well as possess low density,high thermal conductivity,narrow solidification range,high solidus temperature,and a small linear thermal expansion *** Integrated Computational Materials Engineering(ICME)methods are not sufficient for exploring combinatorially-vast alloy design spaces,optimizing for multiple objectives,nor ensuring that multiple constraints are *** this work,we propose an approach for solving a constrained multi-objective materials design problem over a large composition space,specifically focusing on the Mo-Nb-Ti-V-W system as a representative Multi-Principal Element Alloy(MPEA)for potential use in next-generation gas turbine *** approach is able to learn and adapt to unknown constraints in the design space,making decisions about the best course of action at each stage of the *** a result,we identify 21 Pareto-optimal alloys that satisfy all *** proposed framework is significantly more efficient and faster than a brute force approach.

关键词： alloys solidification alloy

A physics informed bayesian optimization approach for material design: application to NiTi shape memory alloys

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npj Computational Materials 2023年第1期9卷 85-95页

作者： Danial Khatamsaz raymond Neuberger Arunabha M.roy Sina Hossein Zadeh richard Otis raymundo arróyave Materials Science and Engineering Department Texas A&M UniversityCollege StationTX 77843USA Engineering and Science Directorate Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCA 91109USA Mechanical Engineering Department Texas A&M UniversityCollege StationTX 77843USA Department of Industrial&Systems Engineering Texas A&M UniversityCollege StationTX 77843USA

The design of materials and identification of optimal processing parameters constitute a complex and challenging task,necessitating efficient utilization of available *** Optimization(BO)has gained popularity in materials design due to its ability to work with minimal ***,many BO-based frameworks predominantly rely on statistical information,in the form of input-output data,and assume black-box objective *** practice,designers often possess knowledge of the underlying physical laws governing a material system,rendering the objective function not entirely black-box,as some information is partially *** this study,we propose a physics-informed BO approach that integrates physics-infused kernels to effectively leverage both statistical and physical information in the decision-making *** demonstrate that this method significantly improves decision-making efficiency and enables more data-efficient *** applicability of this approach is showcased through the design of NiTi shape memory alloys,where the optimal processing parameters are identified to maximize the transformation temperature.

关键词： alloys shape approach

Coarse to Fine: The role of Severe Plastic Deformation in Advancing Titanium-Based Medical Implants - A Comprehensive review

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Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 295-306页

作者： Dragana r Mihajlović Bojan I Međo Ivana Lj Cvijović-Alagić Veljko r Djokić Faculty of Technology and Metallurgy University of BelgradeKarnegijeva 411120 BelgradeSerbia Vinča Institute of Nuclear Sci-ences-National Institute of the republic of Serbia University of Belgrade11001BeogradSerbia Innovation Centre of the Faculty of Technology and Metallurgy Karnegijeva 411120 BelgradeSerbia

This paper describes severe plastic deformation(SPD)procedures,which are utilized to form an ultrafine-grained structure in metallic *** the SPD process,a solid material sample is subjected to very high loads without a significant change in sample *** the present work,the high-pressure torsion(HPT)process,as one of the SPD techniques,which achieves a high degree of deformation and ensures refinement of the microstructure,will be discussed in more *** that grain size control is accepted as a method to obtain materials with desired characteristics,an overview of the properties of ultrafine-grained titanium-based biomaterials to be used in medicine is ***,particular attention is dedicated to the influences of HPT process parameters,primarily hydrostatic pressure,and number of revolutions during torsion,on the grain size and physical and mechanical characteristics(modulus of elasticity,microhardness,and tensile properties),corrosion resistance,and biocompatibility of the titanium-based biomaterials.A review of the literature indicates that titanium-based materials obtained by the SPD process show improved mechanical and physical properties without losing biocompatibility and corrosion resistance,which suggests that these methods of obtaining implants are something that should be further developed in the future.

关键词： high-pressure torsion process ultrafine-grained titanium-based materials electrochemical anodization physical properties mechanical properties

Emerging potential of progranulin-dependent SorCS2 signaling in healthy and diseased nervous systems

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Neural regeneration research 2025年第9期20卷 2591-2593页

作者： Alena Salasova Anders Nykjær Danish research Institute of Translational Neuroscience DANDrITE-Nordic EMBL Partnership for Molecular Medicine and Centre of Excellence PROMEMODepartment of BiomedicineAarhus UniversityAarhusDenmark

The formation of the mammalian nervous system and its maturation into sensory,motor,cognitive,and behavioral circuits is a complex process that begins during early embryogenesis and lasts until young *** neurodevelopm... 详细信息

关键词： progr jointly CS2

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Security Strategy of Digital Medical Contents Based on Blockchain in Generative AI Model

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Computers, Materials & Continua 2025年第1期82卷 259-278页

作者： Hoon Ko Marek r.Ogiela Division of Computer Science and Engineering Sunmoon UniversityAsan31460Republic of Korea AGH University of Krakow Cryptography and Cognitive Informatics LaboratoryKrakow30-059Poland

This study presents an innovative approach to enhancing the security of visual medical data in the generative AI environment through the integration of blockchain *** combining the strengths of blockchain and generative AI,the research team aimed to address the timely challenge of safeguarding visual medical *** participating researchers conducted a comprehensive analysis,examining the vulnerabilities of medical AI services,personal information protection issues,and overall security *** multi faceted exploration led to an indepth evaluation of the model’s performance and ***,the correlation between accuracy,detection rate,and error rate was *** analysis revealed insights into the model’s strengths and limitations,while the consideration of standard deviation shed light on the model’s stability and performance *** study proposed practical improvements,emphasizing the reduction of false negatives to enhance detection rate and leveraging blockchain technology to ensure visual data integrity in medical *** blockchain to generative AI-created medical content addresses key personal information protection *** utilizing the distributed ledger system of blockchain,the research team aimed to protect the privacy and integrity of medical data especially medical *** approach not only enhances security but also enables transparent and tamperproof ***,the use of generative AI models ensures the creation of novel medical content without compromising personal information,further safeguarding patient *** conclusion,this study showcases the potential of blockchain-based solutions in the medical field,particularly in securing sensitive medical data and protecting patient *** proposed approach,combining blockchain and generative AI,offers a promising direction toward more robust and secure medical content *** research and advancements

关键词： Digitalmedical content medical diagnostic visualization security analysis generativeAI blockchain vulnerability pattern recognition

A comprehensive investigation on nonlinear vibration and bending characteristics of bio-inspired helicoidal laminated composite structures

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Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 81-100页

作者： S.SAUrABH r.KIrAN D.SINGH r.VAISH V.S.CHAUHAN School of Mechanical and Materials Engineering Indian Institute of Technology Mandi

Bio-inspired helicoidal composite laminates, inspired by the intricate helical structures found in nature, present a promising frontier for enhancing the mechanical properties of structural designs. Hence, this study provides a comprehensive investigation into the nonlinear free vibration and nonlinear bending behavior of bio-inspired composite plates. The inverse hyperbolic shear deformation theory(IHSDT) of plates is employed to characterize the displacement field, with the incorporation of Green-Lagrange nonlinearity. The problem is modeled using the C0finite element method(FEM), and an in-house code is developed in the MATLAB environment to solve it numerically. Various helicoidal layup configurations including helicoidal recursive(Hr), helicoidal exponential(HE), helicoidal semi-circular(HS), linear helicoidal(LH), and Fibonacci helicoidal(FH)with different layup sequences and quasi-isotropic configurations are studied. The model is validated, and parametric studies are conducted. These studies investigate the effects of layup configurations, side-to-thickness ratio, modulus ratios, boundary conditions, and loading conditions at different load amplitudes on the nonlinear vibration and nonlinear bending behaviors of bio-inspired composite plates. The results show that the laminate sequence exerts a substantial impact on both nonlinear natural frequencies and nonlinear bending behaviors. Moreover, this influence varies across different side-to-thickness ratios and boundary conditions of the bio-inspired composite plate.

关键词： Inverse problems

Machine Learning Techniques in Predicting Hot Deformation Behavior of Metallic Materials

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 713-732页

作者： Petr Opela Josef Walek Jaromír Kopecek Department of Metallurgical Technologies Faculty of Materials Science and TechnologyVSB–Technical University of OstravaOstrava70800Czech Republic FZU—Institute of Physics of the Czech Academy of Sciences Prague18200Czech Republic

In engineering practice,it is often necessary to determine functional relationships between dependent and independent *** relationships can be highly nonlinear,and classical regression approaches cannot always provide sufficiently reliable ***,Machine Learning(ML)techniques,which offer advanced regression tools to address complicated engineering issues,have been developed and widely *** study investigates the selected ML techniques to evaluate their suitability for application in the hot deformation behavior of metallic *** ML-based regression methods of Artificial Neural Networks(ANNs),Support Vector Machine(SVM),Decision Tree regression(DTr),and Gaussian Process regression(GPr)are applied to mathematically describe hot flow stress curve datasets acquired experimentally for a medium-carbon *** the GPr method has not been used for such a regression task before,the results showed that its performance is the most favorable and practically unrivaled;neither the ANN method nor the other studied ML techniques provide such precise results of the solved regression analysis.

关键词： Machine learning Gaussian process regression artificial neural networks support vector machine hot deformation behavior

Antisense oligonucleotides provide optimism to the therapeutic landscape for tauopathies

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Neural regeneration research 2025年第3期20卷 803-804页

作者： Glenn A.Harris Lauren r.Hirschfeld rainwater Charitable Foundation Fort WorthTXUSA

Tauopathies are a group of neurodegenerative diseases characterized by abnormal metabolism of the misfolded tau protein. Tau is encoded by the microtubule-associated protein tau gene(MAPT) and can be classified as either 3-repeat(3r) or 4-repeat(4r) based on the number of repeat domains from alternative splicing of exon 10 of the MAPT gene.

关键词： tau metabolism diseases

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Heterogeneity of mature oligodendrocytes in the central nervous system

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Neural regeneration research 2025年第5期20卷 1336-1349页

作者： Chao Weng Adam M.r.Groh Moein Yaqubi Qiao-Ling Cui Jo Anne Stratton G.r.Wayne Moore Jack P.Antel Neuroimmunology Unit Montreal Neurological Institute-HospitalDepartment of Neurology and NeurosurgeryMcGill UniversityMontrealQCCanada Department of Neurology Renmin Hospital of Wuhan UniversityWuhanHubei ProvinceChina

Mature oligodendrocytes form myelin sheaths that are crucial for the insulation of axons and efficient signal transmission in the central nervous *** evidence has challenged the classical view of the functionally static mature oligodendrocyte and revealed a gamut of dynamic functions such as the ability to modulate neuronal circuitry and provide metabolic support to *** the recognition of potential heterogeneity in mature oligodendrocyte function,a comprehensive summary of mature oligodendrocyte diversity is *** delve into early 20th-century studies by robertson and río-Hortega that laid the foundation for the modern identification of regional and morphological heterogeneity in mature ***,recent morphologic and functional studies call into question the long-assumed homogeneity of mature oligodendrocyte function through the identification of distinct subtypes with varying myelination ***,modern molecular investigations,employing techniques such as single cell/nucleus rNA sequencing,consistently unveil at least six mature oligodendrocyte subpopulations in the human central nervous system that are highly transcriptomically diverse and vary with central nervous system *** and disease related mature oligodendrocyte variation denotes the impact of pathological conditions such as multiple sclerosis,Alzheimer's disease,and psychiatric ***,caution is warranted when subclassifying mature oligodendrocytes because of the simplification needed to make conclusions about cell identity from temporally confined *** studies leveraging advanced techniques like spatial transcriptomics and single-cell proteomics promise a more nuanced understanding of mature oligodendrocyte *** research avenues that precisely evaluate mature oligodendrocyte heterogeneity with care to understand the mitigating influence of species,sex,central nervous system region,age,and disease,

关键词： aging central nervous system diseases electron microscopy heterogeneity immunohistochemistry myelin sheath natural history neuroglia oligodendroglia single-cell gene expression analysis

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