jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Rony Aad | Ivana Dragojlov | Simone Vesentini
Source: Journal of Functional Biomaterials (review, 2024-10-29)
Field: Materials Science — Biomaterials

Sericin Protein: Structure, Properties, and Applications Silk sericin, the glue protein binding fibroin fibers together, is present in the <i>Bombyx mori</i> silkworms' cocoons. In recent years, sericin has gained attention for its wide range of properties and possible opportunities for various applications, as evidenced by the meta-analysis conducted in this review. Sericin extraction methods have evolved over the years to become more efficient and environmentally friendly, preserving its structure. Due to its biocompatibility, biodegradability, anti-inflammatory, antibacterial, antioxidant, UV-protective, anti-tyrosinase, anti-aging, and anti-cancer properties, sericin is increasingly used in biomedical fields like drug delivery, tissue engineering, and serum-free cell culture media. Beyond healthcare, sericin shows promise in industries such as textiles, cosmetics, and food packaging. This review aims to highlight recent advancements in sericin extraction, research, and applications, while also summarizing key findings from earlier studies. Sericin ; Materials science ; Nanotechnology ; Composite material ; SILK Silk-based biomaterials and applications ; Insect Utilization and Effects ; Insect and Arachnid Ecology and Behavior
Authors: Md. Zobair Al Mahmud | S. M. Fazle Rabbi | Md. Didarul Islam | Nayem Hossain
Source: SPE Polymers (review, 2024-09-26)
Field: Materials Science — Polymers and Plastics

Synthesis and applications of natural fiber‐reinforced epoxy composites: A comprehensive review Abstract This review aims to provide a detailed analysis of the synthesis methods, properties, and applications of natural fiber‐reinforced epoxy composites, highlighting their potential as sustainable materials for various industries. The objective of the study is to examine how different natural fibers such as jute, flax, hemp, and sisal impact the mechanical performance of epoxy composites. The synthesis of these composites involves fiber selection, surface treatments, and epoxy matrix formulation, with processing techniques like hand lay‐up, vacuum infusion, and compression molding playing critical roles. Quantitative results show that tensile strengths of these fibers range from 12 MPa (abaca) to 1627 MPa (pineapple), and densities range from 295 kg/m 3 (kenaf) to 1560 kg/m 3 (pineapple), reflecting their variability and influence on composite performance. The review finds that fiber‐matrix compatibility, fiber orientation, and interfacial adhesion significantly affect the mechanical properties, such as tensile strength and thermal stability. The composites demonstrate potential applications in the automotive, aerospace, and construction industries, where they can be used for interior components, structural elements, and non‐load‐bearing parts. The study concludes that natural fiber‐reinforced epoxy composites offer a promising solution for reducing environmental impact while maintaining material performance in various structural applications. Highlights Epoxy‐reinforced natural fiber composites synthesis and applications. Synthesis involves fiber selection, treatment, and epoxy matrix formulation. Natural fibers like jute, flax, hemp, and sisal used due to their renewable nature and biodegradability. Applications include automotive and furniture industries. Epoxy ; Composite material ; Materials science ; Natural fiber ; Synthetic fiber ; Fiber ; Fiber-reinforced composite Natural Fiber Reinforced Composites ; Epoxy Resin Curing Processes ; Tribology and Wear Analysis
Authors: Ding Luo | Shuo Yang | Yuying Yan | Jin Cao | Bing Cao
Source: Energy Conversion and Management (article, 2024-04-27)
Field: Materials Science — Materials Chemistry

Performance improvement of the automotive thermoelectric generator by extending the hot side area of the heat exchanger through heat pipes Heat exchanger ; Thermoelectric generator ; Automotive industry ; Thermoelectric effect ; Generator (circuit theory) ; Automotive engineering ; Mechanical engineering ; Materials science ; Engineering ; Environmental science ; Nuclear engineering ; Thermodynamics ; Physics ; Power (physics) ; Aerospace engineering Advanced Thermoelectric Materials and Devices ; Heat Transfer and Optimization ; Refrigeration and Air Conditioning Technologies
Authors: Qiao Wu | Jun Liang | Dan Wang | Ruihu Wang | Christoph Janiak
Source: Chemical Society Reviews (review, 2024-11-26)
Field: Chemistry — Inorganic Chemistry

Host molecules inside metal–organic frameworks: host@MOF and guest@host@MOF (Matrjoschka) materials The controllable encapsulation of host molecules (such as porphyrin, phthalocyanine, crown ether, calixarene or cucurbituril organic macrocycles, cages, metal-organic polyhedrons and enzymes) into the pores of metal-organic frameworks (MOFs) to form host-in-host (host@MOF) materials has attracted increasing research interest in various fields. These host@MOF materials combine the merits of MOFs as a host matrix and functional host molecules to exhibit synergistic functionalities for the formation of guest@host@MOF materials in sorption and separation, ion capture, catalysis, proton/ion conduction and biosensors. (This guest@host@MOF construction is reminiscent of Russian (Matrjoschka) dolls which are nested dolls of decreasing size placed one inside another.) In this tutorial review, the advantages of MOFs as a host matrix are presented; the encapsulation approaches and general important considerations for the preparation of host@MOF materials are introduced. The state-of-the-art examples of these materials based on different host molecules are shown, and representative applications and general characterization of these materials are discussed. This review will guide researchers attempting to design functional host@MOF and guest@host@MOF materials for various applications. Metal-organic framework ; Host (biology) ; Nanotechnology ; Organic molecules ; Chemistry ; Molecule ; Materials science ; Organic chemistry ; Ecology ; Biology ; Adsorption Metal-Organic Frameworks: Synthesis and Applications ; Metal complexes synthesis and properties ; Nanocluster Synthesis and Applications
Authors: Qian He | Meiyiming Wang | Zhao Li | Bin Xu | Wenjing Tian | Liyun Zhang
Source: Aggregate (article, 2024-01-31)
Field: Materials Science — Materials Chemistry

Near‐infrared aggregation‐induced emission materials: Bibliometric analysis and their application in biomedical field Abstract Aggregation‐induced emission (AIE) is an intriguing photophysical phenomenon, where specific materials exhibit a remarkable surge in luminescence when brought together in non‐ideal solvents or within a solid matrix. Since the concept of AIE was first introduced in 2001, numerous advanced applications have been gradually explored across various domains, including optics, electronics, energy, and the life sciences. Of particular note is the growing interest in the application of AIE systems with near‐infrared (NIR) emissive feature in the field of biomedicine, encompassing detection, imaging, and therapeutic interventions. Notably, bibliometric analysis serves as a valuable tool to provide researchers with a comprehensive understanding of research achievements and developmental trends in specific fields, which is crucial for academic research. Herein, we present a general bibliometric overview spanning two decades of NIR‐AIE development. With the assistance of core scientific databases and various bibliometric software tools, we conducted a systematic analysis of annual publications and citations, the most influential countries/regions, leading authors, journals, and institutions, as well as the hot topics related to NIR applications and forward‐looking predictions. Furthermore, the application of AIE with NIR properties in the biomedical field is also systematically reviewed. Biomedicine ; Aggregation-induced emission ; Data science ; Computer science ; Nanotechnology ; Field (mathematics) ; Scientific literature ; Materials science ; Physics ; Bioinformatics Luminescence and Fluorescent Materials ; Nanoplatforms for cancer theranostics ; Carbon and Quantum Dots Applications
Authors: Xiao You | Huiying Ouyang | Ruixiang Deng | Qiuqi Zhang | Zhenzhong Xing | Xiaowu Chen | Qingliang Shan | Jinshan Yang | Shaoming Dong
Source: Nano-Micro Letters (article, 2024-10-20)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Graphene Aerogel Composites with Self-Organized Nanowires-Packed Honeycomb Structure for Highly Efficient Electromagnetic Wave Absorption With vigorous developments in nanotechnology, the elaborate regulation of microstructure shows attractive potential in the design of electromagnetic wave absorbers. Herein, a hierarchical porous structure and composite heterogeneous interface are constructed successfully to optimize the electromagnetic loss capacity. The macro-micro-synergistic graphene aerogel formed by the ice template‑assisted 3D printing strategy is cut by silicon carbide nanowires (SiC<sub>nws</sub>) grown in situ, while boron nitride (BN) interfacial structure is introduced on graphene nanoplates. The unique composite structure forces multiple scattering of incident EMWs, ensuring the combined effects of interfacial polarization, conduction networks, and magnetic-dielectric synergy. Therefore, the as-prepared composites present a minimum reflection loss value of - 37.8 dB and a wide effective absorption bandwidth (EAB) of 9.2 GHz (from 8.8 to 18.0 GHz) at 2.5 mm. Besides, relying on the intrinsic high-temperature resistance of SiC<sub>nws</sub> and BN, the EAB also remains above 5.0 GHz after annealing in air environment at 600 °C for 10 h. Materials science ; Aerogel ; Reflection loss ; Nanowire ; Graphene ; Microstructure ; Composite material ; Composite number ; Dielectric ; Dielectric loss ; Boron nitride ; Scattering ; Honeycomb structure ; Optoelectronics ; Nanotechnology ; Optics Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies ; Metamaterials and Metasurfaces Applications
Authors: Simon Stier | Christoph Kreisbeck | H. Ihssen | Matthias Popp | Jens Hauch | Kourosh Malek | Marine Reynaud | T. P. M. Goumans | Johan M. Carlsson | Ilian T. Todorov | Lukas Gold | Andreas Räder | Wolfgang Wenzel | Shahbaz Tareq Bandesha | Philippe Jacques | Francisco García‐Moreno | Oier Arcelus | Pascal Friederich | Simon Clark | Mario Maglione | Anssi Laukkanen | Ivano E. Castelli | Javier Carrasco | Montse Casas‐Cabanas | Helge S. Stein | Ozlem Ozcan | David C. Elbert | Karsten Reuter | Christoph Scheurer | Masahiko Demura | Sang Soo Han | Tejs Vegge | Sawako Nakamae | M. Fabrizio | Mark Kozdras
Source: Advanced Materials (article, 2024-09-06)
Field: Materials Science — Materials Chemistry

Materials Acceleration Platforms (MAPs): Accelerating Materials Research and Development to Meet Urgent Societal Challenges Climate Change and Materials Criticality challenges are driving urgent responses from global governments. These global responses drive policy to achieve sustainable, resilient, clean solutions with Advanced Materials (AdMats) for industrial supply chains and economic prosperity. The research landscape comprising industry, academe, and government identified a critical path to accelerate the Green Transition far beyond slow conventional research through Digital Technologies that harness Artificial Intelligence, Smart Automation and High Performance Computing through Materials Acceleration Platforms, MAPs. In this perspective, following the short paper, a broad overview about the challenges addressed, existing projects and building blocks of MAPs will be provided while concluding with a review of the remaining gaps and measures to overcome them. Materials science ; Acceleration ; Nanotechnology ; Systems engineering ; Engineering physics ; Construction engineering ; Engineering ethics ; Engineering ; Physics Machine Learning in Materials Science ; Advanced Semiconductor Detectors and Materials ; Technology Assessment and Management
Authors: Manu Suvarna | Tangsheng Zou | Sok Ho Chong | Yuzhen Ge | Antonio J. Martín | Javier Pérez‐Ramírez
Source: Nature Communications (article, 2024-07-11)
Field: Materials Science — Materials Chemistry

Active learning streamlines development of high performance catalysts for higher alcohol synthesis Developing efficient catalysts for syngas-based higher alcohol synthesis (HAS) remains a formidable research challenge. The chain growth and CO insertion requirements demand multicomponent materials, whose complex reaction dynamics and extensive chemical space defy catalyst design norms. We present an alternative strategy by integrating active learning into experimental workflows, exemplified via the FeCoCuZr catalyst family. Our data-aided framework streamlines navigation of the extensive composition and reaction condition space in 86 experiments, offering >90% reduction in environmental footprint and costs over traditional programs. It identifies the Fe<sub>65</sub>Co<sub>19</sub>Cu<sub>5</sub>Zr<sub>11</sub> catalyst with optimized reaction conditions to attain higher alcohol productivities of 1.1 g<sub>HA</sub> h<sup>-1</sup> g<sub>cat</sub><sup>-1</sup> under stable operation for 150 h on stream, a 5-fold improvement over typically reported yields. Characterization reveals catalytic properties linked to superior activities despite moderate higher alcohol selectivities. To better reflect catalyst demands, we devise multi-objective optimization to maximize higher alcohol productivity while minimizing undesired CO<sub>2</sub> and CH<sub>4</sub> selectivities. An intrinsic trade-off between these metrics is uncovered, identifying Pareto-optimal catalysts not readily discernible by human experts. Finally, based on feature-importance analysis, we formulate data-informed guidelines to develop performance-specific FeCoCuZr systems. This approach goes beyond existing HAS catalyst design strategies, is adaptable to broader catalytic transformations, and fosters laboratory sustainability. Catalysis ; Workflow ; Alcohol ; Biochemical engineering ; Computer science ; Streamlines, streaklines, and pathlines ; Process engineering ; Chemistry ; Organic chemistry ; Engineering Machine Learning in Materials Science ; Innovative Microfluidic and Catalytic Techniques Innovation ; CO2 Reduction Techniques and Catalysts
Authors: Benjamin Decardi‐Nelson | Abdulelah S. Alshehri | Akshay Ajagekar | Fengqi You
Source: Computers & Chemical Engineering (preprint, 2024-05-09)
Field: Materials Science — Materials Chemistry

Generative AI and process systems engineering: The next frontier Computer science ; Process (computing) ; Adaptability ; Key (lock) ; Domain (mathematical analysis) ; Systems engineering ; Data science ; Management science ; Artificial intelligence ; Process management ; Engineering Machine Learning in Materials Science ; Manufacturing Process and Optimization ; Business Process Modeling and Analysis
Authors: Xinyu Fan | Letian Chen | Dulin Huang | Yun Tian | Xu Zhang | Menggai Jiao | Zhen Zhou
Source: Advanced Functional Materials (article, 2024-04-25)
Field: Materials Science — Materials Chemistry

From Single Metals to High‐Entropy Alloys: How Machine Learning Accelerates the Development of Metal Electrocatalysts Abstract The rapid advancement of high‐performance computing and artificial intelligence technology has opened up novel avenues for the development of various metal electrocatalysts. In particular, dilute and high‐entropy alloys have garnered significant attention owing to their unique electronic and spatial structures, as well as their exceptional electrocatalytic performance. Commencing with the exploration of single‐atom alloy catalysts, the latest advancements in machine learning (ML) techniques are presented for the efficient screening of a broad spectrum of metal spaces. Subsequently, the review delves into the prevailing trend in alloy research, focusing specifically on rare‐metal alloy electrocatalysts, and offers an overview of the progress and outcomes achieved through the application of ML in these domains. Finally, high‐entropy alloys are highlighted as a promising category of electrocatalysts and underscore the importance and potential applications of ML in addressing complex and challenging research issues are underscored. Alloy ; Materials science ; High entropy alloys ; Nanotechnology ; Metal ; Artificial intelligence ; Computer science ; Metallurgy Machine Learning in Materials Science ; Electrocatalysts for Energy Conversion ; Fuel Cells and Related Materials
Authors: Chunhua Li | Luqian Bao | Yixin Ji | Zhehang Tian | Mengyao Cui | Yubo Shi | Zhilei Zhao | Xianyou Wang
Source: Coordination Chemistry Reviews (article, 2024-05-08)
Field: Chemistry — Inorganic Chemistry

Combining machine learning and metal–organic frameworks research: Novel modeling, performance prediction, and materials discovery Chemistry ; Metal-organic framework ; Nanotechnology ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Machine Learning in Materials Science ; X-ray Diffraction in Crystallography
Authors: Jing Wu | E Zhou | An Huang | Hongbin Zhang | Ming Hu | Guangzhao Qin
Source: Nature Communications (article, 2024-03-25)
Field: Materials Science — Materials Chemistry

Deep-potential enabled multiscale simulation of gallium nitride devices on boron arsenide cooling substrates High-efficient heat dissipation plays critical role for high-power-density electronics. Experimental synthesis of ultrahigh thermal conductivity boron arsenide (BAs, 1300 W m<sup>-1</sup>K<sup>-1</sup>) cooling substrates into the wide-bandgap semiconductor of gallium nitride (GaN) devices has been realized. However, the lack of systematic analysis on the heat transfer across the GaN-BAs interface hampers the practical applications. In this study, by constructing the accurate and high-efficient machine learning interatomic potentials, we perform multiscale simulations of the GaN-BAs heterostructures. Ultrahigh interfacial thermal conductance of 260 MW m<sup>-2</sup>K<sup>-1</sup> is achieved, which lies in the well-matched lattice vibrations of BAs and GaN. The strong temperature dependence of interfacial thermal conductance is found between 300 to 450 K. Moreover, the competition between grain size and boundary resistance is revealed with size increasing from 1 nm to 1000 μm. Such deep-potential equipped multiscale simulations not only promote the practical applications of BAs cooling substrates in electronics, but also offer approach for designing advanced thermal management systems. Materials science ; Thermal conductivity ; Gallium arsenide ; Boron nitride ; Gallium nitride ; Optoelectronics ; Wide-bandgap semiconductor ; Interfacial thermal resistance ; Heat sink ; Semiconductor ; Heterojunction ; Band gap ; Phonon ; Thermal resistance ; Nanotechnology ; Heat transfer ; Condensed matter physics ; Thermodynamics ; Physics ; Composite material Thermal properties of materials ; Advanced Thermoelectric Materials and Devices ; Thermal Radiation and Cooling Technologies
Authors: Andrei Ştefancu | Javier Aizpurua | Ivano Alessandri | Ilko Bald | Jeremy J. Baumberg | Lucas V. Besteiro | Phillip Christopher | Miguel A. Correa‐Duarte | Bart de Nijs | Angela Demetriadou | Renee R. Frontiera | Tomohiro Fukushima | Naomi J. Halas | Prashant K. Jain | Zee Hwan Kim | Dmitry Kurouski | Holger Lange | Jian‐Feng Li | Luis M. Liz‐Marzán | Ivan T. Lucas | Alfred J. Meixner | Kei Murakoshi | Peter Nordlander | William J. Peveler | Raúl Quesada-Cabrera | Emilie Ringe | George C. Schatz | Sebastian Schlücker | Zachary D. Schultz | Emily Xi Tan | Zhong‐Qun Tian | Lingzhi Wang | Bert M. Weckhuysen | Wei Xie | Xing Yi Ling | Jinlong Zhang | Zhigang Zhao | Ru-Yu Zhou | Emiliano Cortés
Source: ACS Nano (review, 2024-10-14)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Impact of Surface Enhanced Raman Spectroscopy in Catalysis Catalysis stands as an indispensable cornerstone of modern society, underpinning the production of over 80% of manufactured goods and driving over 90% of industrial chemical processes. As the demand for more efficient and sustainable processes grows, better catalysts are needed. Understanding the working principles of catalysts is key, and over the last 50 years, surface-enhanced Raman Spectroscopy (SERS) has become essential. Discovered in 1974, SERS has evolved into a mature and powerful analytical tool, transforming the way in which we detect molecules across disciplines. In catalysis, SERS has enabled insights into dynamic surface phenomena, facilitating the monitoring of the catalyst structure, adsorbate interactions, and reaction kinetics at very high spatial and temporal resolutions. This review explores the achievements as well as the future potential of SERS in the field of catalysis and energy conversion, thereby highlighting its role in advancing these critical areas of research. Nanotechnology ; Catalysis ; Raman spectroscopy ; Surface-enhanced Raman spectroscopy ; Cornerstone ; Underpinning ; Materials science ; Biochemical engineering ; Chemistry ; Raman scattering ; Engineering ; Physics ; Organic chemistry Gold and Silver Nanoparticles Synthesis and Applications ; Quantum Dots Synthesis And Properties ; Nanocluster Synthesis and Applications
Authors: Siyang Gao | Binhan Xu | Jianwei Sun | Zhihui Zhang
Source: Frontiers in Bioengineering and Biotechnology (review, 2024-03-06)
Field: Materials Science — Materials Chemistry

Nanotechnological advances in cancer: therapy a comprehensive review of carbon nanotube applications Nanotechnology is revolutionising different areas from manufacturing to therapeutics in the health field. Carbon nanotubes (CNTs), a promising drug candidate in nanomedicine, have attracted attention due to their excellent and unique mechanical, electronic, and physicochemical properties. This emerging nanomaterial has attracted a wide range of scientific interest in the last decade. Carbon nanotubes have many potential applications in cancer therapy, such as imaging, drug delivery, and combination therapy. Carbon nanotubes can be used as carriers for drug delivery systems by carrying anticancer drugs and enabling targeted release to improve therapeutic efficacy and reduce adverse effects on healthy tissues. In addition, carbon nanotubes can be combined with other therapeutic approaches, such as photothermal and photodynamic therapies, to work synergistically to destroy cancer cells. Carbon nanotubes have great potential as promising nanomaterials in the field of nanomedicine, offering new opportunities and properties for future cancer treatments. In this paper, the main focus is on the application of carbon nanotubes in cancer diagnostics, targeted therapies, and toxicity evaluation of carbon nanotubes at the biological level to ensure the safety and real-life and clinical applications of carbon nanotubes. Nanotechnology ; Carbon nanotube ; Cancer ; Cancer therapy ; Materials science ; Medicine ; Internal medicine Carbon Nanotubes in Composites ; Graphene and Nanomaterials Applications ; Nanoparticles: synthesis and applications