jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Jianfeng Tan | Yuan Zhang
Source: Molecules (review, 2024-07-29)
Field: Materials Science — Materials Chemistry

Thermal Conductive Polymer Composites: Recent Progress and Applications As microelectronics technology advances towards miniaturization and higher integration, the imperative for developing high-performance thermal management materials has escalated. Thermal conductive polymer composites (TCPCs), which leverage the benefits of polymer matrices and the unique effects of nano-enhancers, are gaining focus as solutions to overheating due to their low density, ease of processing, and cost-effectiveness. However, these materials often face challenges such as thermal conductivities that are lower than expected, limiting their application in high-performance electronic devices. Despite these issues, TCPCs continue to demonstrate broad potential across various industrial sectors. This review comprehensively presents the progress in this field, detailing the mechanisms of thermal conductivity (TC) in these composites and discussing factors that influence thermal performance, such as the intrinsic properties of polymers, interfacial thermal resistance, and the thermal properties of fillers. Additionally, it categorizes and summarizes methods to enhance the TC of polymer composites. The review also highlights the applications of these materials in emerging areas such as flexible electronic devices, personal thermal management, and aerospace. Ultimately, by analyzing current challenges and opportunities, this review provides clear directions for future research and development. Materials science ; Thermal conductivity ; Overheating (electricity) ; Microelectronics ; Miniaturization ; Thermal management of electronic devices and systems ; Electronics ; Electrical conductor ; Nanotechnology ; Thermal ; Composite material ; Engineering physics ; Mechanical engineering ; Engineering ; Electrical engineering Thermal properties of materials ; Dielectric materials and actuators ; Ferroelectric and Piezoelectric Materials
Authors: B. Moses Abraham | M. V. Jyothirmai | Priyanka Sinha | Francesc Viñes | Jayant K. Singh | Francesc Illas
Source: Wiley Interdisciplinary Reviews Computational Molecular Science (article, 2024-09-01)
Field: Materials Science — Materials Chemistry

Catalysis in the digital age: Unlocking the power of data with machine learning Abstract The design and discovery of new and improved catalysts are driving forces for accelerating scientific and technological innovations in the fields of energy conversion, environmental remediation, and chemical industry. Recently, the use of machine learning (ML) in combination with experimental and/or theoretical data has emerged as a powerful tool for identifying optimal catalysts for various applications. This review focuses on how ML algorithms can be used in computational catalysis and materials science to gain a deeper understanding of the relationships between materials properties and their stability, activity, and selectivity. The development of scientific data repositories, data mining techniques, and ML tools that can navigate structural optimization problems are highlighted, leading to the discovery of highly efficient catalysts for a sustainable future. Several data‐driven ML models commonly used in catalysis research and their diverse applications in reaction prediction are discussed. The key challenges and limitations of using ML in catalysis research are presented, which arise from the catalyst's intrinsic complex nature. Finally, we conclude by summarizing the potential future directions in the area of ML‐guided catalyst development. This article is categorized under: Structure and Mechanism &gt; Reaction Mechanisms and Catalysis Data Science &gt; Artificial Intelligence/Machine Learning Electronic Structure Theory &gt; Density Functional Theory Computer science ; Data science ; Power (physics) ; Machine learning ; Physics Machine Learning in Materials Science ; Catalytic Processes in Materials Science ; Catalysis and Hydrodesulfurization Studies
Authors: Gaurav Gopal Naik | Vijay A. Jagtap
Source: Nano TransMed (article, 2024-07-08)
Field: Materials Science — Materials Chemistry

Two heads are better than one: Unravelling the potential Impact of Artificial Intelligence in nanotechnology Artificial Intelligence (AI) and Nanotechnology are two cutting-edge fields that hold immense promise for revolutionizing various aspects of science, technology, and everyday life. This review delves into the intersection of these disciplines, highlighting the synergistic relationship between AI and Nanotechnology. It explores how AI techniques such as machine learning, deep learning, and neural networks are being employed to enhance the efficiency, precision, and scalability of nanotechnology applications. Furthermore, it discusses the challenges, opportunities, and future prospects of integrating AI with nanotechnology, paving the way for transformative advancements in diverse domains ranging from healthcare and materials science to environmental sustainability and beyond. Transformative learning ; Nanotechnology ; Artificial intelligence ; Societal impact of nanotechnology ; Computer science ; Engineering ; Materials science ; Sociology Machine Learning in Materials Science ; Nanotechnology research and applications
Authors: Yedluri Anil Kumar | Shanmugam Vignesh | Tholkappiyan Ramachandran | Ahmed M. Fouda | H.H. Hegazy | Md Moniruzzaman | Tae Hwan Oh
Source: Journal of Industrial and Engineering Chemistry (article, 2024-11-08)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Advancements in novel electrolyte materials: Pioneering the future of supercapacitive energy storage Energy storage ; Electrolyte ; Nanotechnology ; Computer science ; Materials science ; Chemical engineering ; Chemistry ; Engineering ; Physics ; Physical chemistry ; Thermodynamics ; Electrode Supercapacitor Materials and Fabrication ; Advanced battery technologies research ; Advanced Battery Materials and Technologies
Authors: Xueqing Wang | Fan Li | Lan Wei | Yun Huang | Wenguo Xiang | Dongmei Wang | Guiguang Cheng | Ruijuan Zhao | Yechun Lin | Hui Ying Yang | Meikun Fan
Source: Analytical Chemistry (article, 2024-03-07)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Rapid and Precise Differentiation and Authentication of Agricultural Products via Deep Learning-Assisted Multiplex SERS Fingerprinting Accurate and rapid differentiation and authentication of agricultural products based on their origin and quality are crucial to ensuring food safety and quality control. However, similar chemical compositions and complex matrices often hinder precise identification, particularly for adulterated samples. Herein, we propose a novel method combining multiplex surface-enhanced Raman scattering (SERS) fingerprinting with a one-dimensional convolutional neural network (1D-CNN), which enables the effective differentiation of the category, origin, and grade of agricultural products. This strategy leverages three different SERS-active nanoparticles as multiplex sensors, each tailored to selectively amplify the signals of preferentially adsorbed chemicals within the sample. By strategically combining SERS spectra from different NPs, a 'SERS super-fingerprint' is constructed, offering a more comprehensive representation of the characteristic information on agricultural products. Subsequently, utilizing a custom-designed 1D-CNN model for feature extraction from the 'super-fingerprint' significantly enhances the predictive accuracy for agricultural products. This strategy successfully identified various agricultural products and simulated adulterated samples with exceptional accuracy, reaching 97.7% and 94.8%, respectively. Notably, the entire identification process, encompassing sample preparation, SERS measurement, and deep learning analysis, takes only 35 min. This development of deep learning-assisted multiplex SERS fingerprinting establishes a rapid and reliable method for the identification and authentication of agricultural products. Multiplex ; Authentication (law) ; Chemistry ; Artificial intelligence ; Fingerprint (computing) ; Identification (biology) ; Pattern recognition (psychology) ; Convolutional neural network ; Deep learning ; Computer science ; Nanotechnology ; Computer security ; Materials science Gold and Silver Nanoparticles Synthesis and Applications ; Biosensors and Analytical Detection ; Identification and Quantification in Food
Authors: Dinara Sobola | Rashid Dallaev
Source: Energies (article, 2024-06-17)
Field: Materials Science — Metals and Alloys

Exploring Hydrogen Embrittlement: Mechanisms, Consequences, and Advances in Metal Science Hydrogen embrittlement (HE) remains a pressing issue in materials science and engineering, given its significant impact on the structural integrity of metals and alloys. This exhaustive review aims to thoroughly examine HE, covering a range of aspects that collectively enhance our understanding of this intricate phenomenon. It proceeds to investigate the varied effects of hydrogen on metals, illustrating its ability to profoundly alter mechanical properties, thereby increasing vulnerability to fractures and failures. A crucial section of the review delves into how different metals and their alloys exhibit unique responses to hydrogen exposure, shedding light on their distinct behaviors. This knowledge is essential for customizing materials to specific applications and ensuring structural dependability. Additionally, the paper explores a diverse array of models and classifications of HE, offering a structured framework for comprehending its complexities. These models play a crucial role in forecasting, preventing, and mitigating HE across various domains, ranging from industrial settings to critical infrastructure. Hydrogen embrittlement ; Embrittlement ; Materials science ; Metallurgy ; Corrosion Hydrogen embrittlement and corrosion behaviors in metals ; Nuclear Materials and Properties ; Corrosion Behavior and Inhibition
Authors: Jinho Chang | Jong Chul Ye
Source: Nature Communications (article, 2024-03-14)
Field: Materials Science — Materials Chemistry

Bidirectional generation of structure and properties through a single molecular foundation model Recent successes of foundation models in artificial intelligence have prompted the emergence of large-scale chemical pre-trained models. Despite the growing interest in large molecular pre-trained models that provide informative representations for downstream tasks, attempts for multimodal pre-training approaches on the molecule domain were limited. To address this, here we present a multimodal molecular pre-trained model that incorporates the modalities of structure and biochemical properties, drawing inspiration from recent advances in multimodal learning techniques. Our proposed model pipeline of data handling and training objectives aligns the structure/property features in a common embedding space, which enables the model to regard bidirectional information between the molecules' structure and properties. These contributions emerge synergistic knowledge, allowing us to tackle both multimodal and unimodal downstream tasks through a single model. Through extensive experiments, we demonstrate that our model has the capabilities to solve various meaningful chemical challenges, including conditional molecule generation, property prediction, molecule classification, and reaction prediction. Computer science ; Chemical space ; Embedding ; Artificial intelligence ; Machine learning ; Property (philosophy) ; Foundation (evidence) ; Pipeline (software) ; Drug discovery ; Bioinformatics ; Biology Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Machine Learning in Bioinformatics
Authors: Artemis Kontiza | Ioannis Α. Kartsonakis
Source: Polymers (review, 2024-07-25)
Field: Materials Science — Polymers and Plastics

Smart Composite Materials with Self-Healing Properties: A Review on Design and Applications Research on self-healing materials spans multiple academic disciplines and employs a variety of methodologies. Nature has been a major source of inspiration for developing self-healing materials and will likely continue to inspire innovative ideas in this field. This review article covers the principles of self-healing mechanisms, focusing on both autonomous and non-autonomous procedures. It explores both intrinsic and extrinsic self-healing abilities by considering their components, structures, and design. Additionally, a detailed analysis of the application of these materials across various sectors is provided, including aerospace, automotive, marine, energy, medical and healthcare, military, and construction. Finally, the review paper highlights the advancements in encapsulation technologies for microcapsules, their thermal stability, their mechanical properties, and the compatibility of healing agents with the matrix, which play a crucial role in the effectiveness of self-healing processes. Self-healing ; Aerospace ; Compatibility (geochemistry) ; Automotive industry ; Nanotechnology ; Computer science ; Smart material ; Systems engineering ; Materials science ; Engineering ; Medicine ; Composite material ; Aerospace engineering Polymer composites and self-healing ; Electrospun Nanofibers in Biomedical Applications ; Surface Modification and Superhydrophobicity
Authors: Ayyaz Mahmood | Fouzia Perveen | Shenggui Chen | Tayyaba Akram | Ahmad Irfan
Source: Molecules (review, 2024-01-09)
Field: Materials Science — Polymers and Plastics

Polymer Composites in 3D/4D Printing: Materials, Advances, and Prospects Additive manufacturing (AM), commonly referred to as 3D printing, has revolutionized the manufacturing landscape by enabling the intricate layer-by-layer construction of three-dimensional objects. In contrast to traditional methods relying on molds and tools, AM provides the flexibility to fabricate diverse components directly from digital models without the need for physical alterations to machinery. Four-dimensional printing is a revolutionary extension of 3D printing that introduces the dimension of time, enabling dynamic transformations in printed structures over predetermined periods. This comprehensive review focuses on polymeric materials in 3D printing, exploring their versatile processing capabilities, environmental adaptability, and applications across thermoplastics, thermosetting materials, elastomers, polymer composites, shape memory polymers (SMPs), including liquid crystal elastomer (LCE), and self-healing polymers for 4D printing. This review also examines recent advancements in microvascular and encapsulation self-healing mechanisms, explores the potential of supramolecular polymers, and highlights the latest progress in hybrid printing using polymer-metal and polymer-ceramic composites. Finally, this paper offers insights into potential challenges faced in the additive manufacturing of polymer composites and suggests avenues for future research in this dynamic and rapidly evolving field. Materials science ; 3D printing ; Thermosetting polymer ; Stereolithography ; Elastomer ; Polymer ; Flexibility (engineering) ; Ceramic ; Nanotechnology ; Composite material Polymer composites and self-healing ; Advanced Materials and Mechanics ; Additive Manufacturing and 3D Printing Technologies
Authors: Evmorfia Athanasopoulou | Francesco Bigi | Enrico Maurizzi | Eva Iris Eleftheria Karellou | Christos Pappas | Andrea Quartieri | Theofania Tsironi
Source: Scientific Reports (article, 2024-01-04)
Field: Materials Science — Biomaterials

Synthesis and characterization of polysaccharide- and protein-based edible films and application as packaging materials for fresh fish fillets The rising packaging industry together with global demand for sustainable production has increased the interest in developing biodegradable packaging materials. The aim of the study was to develop edible films based on pectin, gelatin, and hydroxypropyl methylcellulose and evaluate their applicability as biodegradable packaging materials for gilthead seabream fillets. Mechanical properties, water barriers, wettability of the films through contact angle measurement, optical, and UV-Vis barrier properties were evaluated for food packaging applications. The effective blend of polysaccharide and protein film-forming solutions was confirmed by the produced films with excellent optical properties, acceptable mechanical properties and adequate barriers to water vapor. The contact angle for pectin based and gelatin based films were higher than 90° indicating the hydrophobic films, while HPMC based films had contact angle lower than 90°. The produced films were tested as alternative and environmentally friendly packaging materials for gilthead seabream fillets during refrigerated storage. All tested packaging conditions resulted in similar shelf-life in packed gilthead seabream fillets (i.e. 7-8 days at 2 °C). The results showed that the developed films may reduce the use of conventional petroleum-based food packaging materials without affecting the shelf-life of fish. Gelatin ; Food packaging ; Contact angle ; Pectin ; Shelf life ; Food science ; Materials science ; Wetting ; Active packaging ; Fish <Actinopterygii> ; Chemical engineering ; Chemistry ; Composite material ; Fishery ; Organic chemistry Nanocomposite Films for Food Packaging ; Meat and Animal Product Quality ; biodegradable polymer synthesis and properties
Authors: Ajay Vikram Singh | Preeti Bhardwaj | Aditya Kumar Upadhyay | Anselmo Pagani | Jyoti Upadhyay | Jolly Bhadra | Veronica Tisato | M.S. Thakur | Donato Gemmati | Rudresh Mishra | Paolo Zamboni
Source: Exploration of BioMat-X (article, 2024-04-25)
Field: Materials Science — Biomaterials

Navigating regulatory challenges in molecularly tailored nanomedicine Nanomedicine, a convergence of nanotechnology and medical sciences, has unleashed transformative potential in healthcare. However, harnessing the benefits of nanomedicine requires a thorough understanding of its regulatory landscape. An in-depth discussion of regulatory considerations, including molecular safety assessment, harmonization of the regulatory landscape, and shaping the future of innovation, is presented in this discourse. The molecular safety assessment entails evaluating interactions between nanoparticles and biomolecules, ensuring compatibility at the molecular level. Harmonization involves developing international standards and guidelines for a consistent regulatory approach, while shaping innovations emphasizes integrating molecular safety assessments into early stages of development. Challenges encompass the need for standardized assessment methods, balancing innovation with safety, and addressing unique features of novel molecular designs. As the nanomedicine landscape evolves, effective regulatory strategies must navigate the intricate interplay of molecules and technologies, ensuring both patient access and product safety. Nanomedicine ; Business ; Nanotechnology ; Materials science ; Nanoparticle Nanoparticle-Based Drug Delivery ; Graphene and Nanomaterials Applications ; Nanoparticles: synthesis and applications
Authors: Naiara Lima Costa | Carlos Toshiyuki Hiranobe | Henrique Pina Cardim | Guilherme Dognani | Juan C. Sánchez | Jaime A. Jaramillo Carvalho | Giovanni Barrera Torres | Leonardo Lataro Paim | Leandro Ferreira‐Pinto | Guilherme Pina Cardim | Flávio Camargo Cabrera | Renivaldo José dos Santos | Michael Jones da Silva
Source: Polymers (review, 2024-06-17)
Field: Materials Science — Polymers and Plastics

A Review of EPDM (Ethylene Propylene Diene Monomer) Rubber-Based Nanocomposites: Properties and Progress Ethylene propylene diene monomer (EPDM) is a synthetic rubber widely used in industry and commerce due to its high thermal and chemical resistance. Nanotechnology has enabled the incorporation of nanomaterials into polymeric matrixes that maintain their flexibility and conformation, allowing them to achieve properties previously unattainable, such as improved tensile and chemical resistance. In this work, we summarize the influence of different nanostructures on the mechanical, thermal, and electrical properties of EPDM-based materials to keep up with current research and support future research into synthetic rubber nanocomposites. Materials science ; Natural rubber ; Ethylene propylene rubber ; Nanocomposite ; EPDM rubber ; Monomer ; Nanomaterials ; Copolymer ; Ultimate tensile strength ; Synthetic rubber ; Hevea brasiliensis ; Flexibility (engineering) ; Diene ; Polymer ; Composite material ; Nanotechnology Polymer Nanocomposites and Properties ; Polymer Nanocomposite Synthesis and Irradiation ; Advanced Battery Materials and Technologies
Authors: Evert Njomen | Rachel E. Hayward | Kristen E. DeMeester | Daisuke Ogasawara | Melissa M. Dix | Tracey Nguyen | Paige Ashby | Gabriel M. Simon | Stuart L. Schreiber | Bruno Melillo | Benjamin F. Cravatt
Source: Nature Chemistry (article, 2024-08-13)
Field: Chemistry — Organic Chemistry

Multi-tiered chemical proteomic maps of tryptoline acrylamide–protein interactions in cancer cells Chemistry ; Proteome ; Cysteine ; Chemical biology ; Electrophile ; Protein–protein interaction ; Human proteome project ; Biochemistry ; Covalent bond ; Computational biology ; Proteomics ; Cancer cell ; Combinatorial chemistry ; Gene ; Enzyme ; Cancer ; Biology ; Genetics ; Organic chemistry Click Chemistry and Applications ; Ubiquitin and proteasome pathways ; Protein Degradation and Inhibitors
Authors: Hong Gao | Satoshi Imamura | Akihiko Kasagi | Eiji Yoshida
Source: Journal of Chemical Theory and Computation (article, 2024-02-05)
Field: Materials Science — Materials Chemistry

Distributed Implementation of Full Configuration Interaction for One Trillion Determinants Full configuration interaction (FCI) can provide an exact molecular ground-state energy within a given basis set and serve as a benchmark for approximate methods in quantum chemical calculations, including the emerging variational quantum eigensolver. However, its exponential computational and memory requirements easily exceed the capability of a single server and limit its applicability to large molecules. In this paper, we present a distributed FCI implementation employing a hybrid parallelization scheme with multithreading and multiprocessing to expand FCI's applicability. We optimize this scheme to minimize the bottlenecks arising from interprocess communications and interthread data management. Our implementation achieves higher scalability than the naive combination of prior works and successfully calculates the exact energy of C<sub>3</sub>H<sub>8</sub>/STO-3G with 1.31 trillion determinants, which is the largest FCI calculation to the best of our knowledge. Furthermore, we provide a comprehensive list of FCI results with 136 combinations of molecules and basis sets for future evaluation and development of approximate methods. Computer science ; Scalability ; Scheme (mathematics) ; Benchmark (surveying) ; Distributed computing ; Multithreading ; Set (abstract data type) ; Basis (linear algebra) ; Multiprocessing ; Computational science ; Parallel computing ; Operating system ; Mathematics Machine Learning in Materials Science ; Spectroscopy and Quantum Chemical Studies ; Advanced Chemical Physics Studies
Authors: Tingting Liu | Qi Zheng | Wen‐Qiang Cao | Yuze Wang | Min Zhang | Quanliang Zhao | Mao‐Sheng Cao
Source: Advanced Composites and Hybrid Materials (article, 2024-04-25)
Field: Materials Science — Materials Chemistry

Dielectric genes editing MXene to switch electromagnetic functions Dielectric ; Computer science ; Optoelectronics ; Physics MXene and MAX Phase Materials ; Energy Harvesting in Wireless Networks ; Advanced biosensing and bioanalysis techniques