jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Hongbin Lin | Xiaorong Song | Osburg Jin Huang Chai | Qiaofeng Yao | Huanghao Yang | Jianping Xie
Source: Advanced Materials (review, 2024-03-24)
Field: Materials Science — Materials Chemistry

Photoluminescent Characterization of Metal Nanoclusters: Basic Parameters, Methods, and Applications Metal nanoclusters (MNCs) can be synthesized with atomically precise structures and molecule formulae due to the rapid development of nanocluster science in recent decades. The ultrasmall size range (normally < 2 nm) endows MNCs with plenty of molecular-like properties, among which photoluminescent properties have aroused extensive attention. Tracing the research and development processes of luminescent nanoclusters, various photoluminescent analysis and characterization methods play a significant role in elucidating luminescent mechanism and analyzing luminescent properties. In this review, it is aimed to systematically summarize the normally used photoluminescent characterizations in MNCs including basic parameters and methods, such as excitation/emission wavelength, quantum yield, and lifetime. For each key parameter, first its definition and meaning is introduced and then the relevant characterization methods including measuring principles and the revelation of luminescent properties from the collected data are discussed. Then, it is discussed in details how to explore the luminescent mechanism of MNCs and construct NC-based applications based on the measured data. By means of these characterization strategies, the luminescent properties of MNCs and NC-based designs can be explained quantitatively and qualitatively. Hence, this review is expected to provide clear guidance for researchers to characterize luminescent MNCs and better understand the luminescent mechanism from the measured results. Nanoclusters ; Photoluminescence ; Luminescence ; Materials science ; Characterization (materials science) ; Nanotechnology ; Optoelectronics Nanocluster Synthesis and Applications ; Gold and Silver Nanoparticles Synthesis and Applications ; Advanced Nanomaterials in Catalysis
Authors: Qidong Li | Hesamedin Ghadiani | Vahid Jalilvand | Tahrim Alam | Zoheir Farhat | Md. Aminul Islam
Source: Materials (review, 2024-02-19)
Field: Materials Science — Metals and Alloys

Hydrogen Impact: A Review on Diffusibility, Embrittlement Mechanisms, and Characterization Hydrogen embrittlement (HE) is a broadly recognized phenomenon in metallic materials. If not well understood and managed, HE may lead to catastrophic environmental failures in vessels containing hydrogen, such as pipelines and storage tanks. HE can affect the mechanical properties of materials such as ductility, toughness, and strength, mainly through the interaction between metal defects and hydrogen. Various phenomena such as hydrogen adsorption, hydrogen diffusion, and hydrogen interactions with intrinsic trapping sites like dislocations, voids, grain boundaries, and oxide/matrix interfaces are involved in this process. It is important to understand HE mechanisms to develop effective hydrogen resistant strategies. Tensile, double cantilever beam, bent beam, and fatigue tests are among the most common techniques employed to study HE. This article reviews hydrogen diffusion behavior, mechanisms, and characterization techniques. Hydrogen embrittlement ; Materials science ; Hydrogen ; Embrittlement ; Ductility (Earth science) ; Grain boundary ; Toughness ; Cantilever ; Cracking ; Hydrogen storage ; Creep ; Corrosion ; Composite material ; Forensic engineering ; Metallurgy ; Microstructure ; Chemistry Hydrogen embrittlement and corrosion behaviors in metals ; Corrosion Behavior and Inhibition ; Nuclear Materials and Properties
Authors: Wan‐Chen Cindy Lee | X. Peter Zhang
Source: Angewandte Chemie International Edition (review, 2024-03-13)
Field: Chemistry — Organic Chemistry

Metalloradical Catalysis: General Approach for Controlling Reactivity and Selectivity of Homolytic Radical Reactions Since Friedrich Wöhler's groundbreaking synthesis of urea in 1828, organic synthesis over the past two centuries has predominantly relied on the exploration and utilization of chemical reactions rooted in two-electron heterolytic ionic chemistry. While one-electron homolytic radical chemistry is both rich in fundamental reactivities and attractive with practical advantages, the synthetic application of radical reactions has been long hampered by the formidable challenges associated with the control over reactivity and selectivity of high-energy radical intermediates. To fully harness the untapped potential of radical chemistry for organic synthesis, there is a pressing need to formulate radically different concepts and broadly applicable strategies to address these outstanding issues. In pursuit of this objective, researchers have been actively developing metalloradical catalysis (MRC) as a comprehensive framework to guide the design of general approaches for controlling over reactivity and stereoselectivity of homolytic radical reactions. Essentially, MRC exploits the metal-centered radicals present in open-shell metal complexes as one-electron catalysts for homolytic activation of substrates to generate metal-entangled organic radicals as the key intermediates to govern the reaction pathway and stereochemical course of subsequent catalytic radical processes. Different from the conventional two-electron catalysis by transition metal complexes, MRC operates through one-electron chemistry utilizing stepwise radical mechanisms. Homolysis ; Reactivity (psychology) ; Selectivity ; Catalysis ; Chemistry ; Photochemistry ; Radical ; Organic chemistry Oxidative Organic Chemistry Reactions ; Catalytic C–H Functionalization Methods ; Radical Photochemical Reactions
Authors: Minghao Liu | Qing Xu | Gaofeng Zeng
Source: Angewandte Chemie International Edition (article, 2024-04-02)
Field: Materials Science — Materials Chemistry

Ionic Covalent Organic Frameworks in Adsorption and Catalysis The ion extraction and electro/photo catalysis are promising methods to address environmental and energy issues. Covalent organic frameworks (COFs) are a class of promising template to construct absorbents and catalysts because of their stable frameworks, high surface areas, controllable pore environments, and well-defined catalytic sites. Among them, ionic COFs as unique class of crystalline porous materials, with charges in the frameworks or along the pore walls, have shown different properties and resulting performance in these applications with those from charge-neutral COFs. In this review, current research progress based on the ionic COFs for ion extraction and energy conversion, including cationic/anionic materials and electro/photo catalysis is reviewed in terms of the synthesis strategy, modification methods, mechanisms of adsorption and catalysis, as well as applications. Finally, we demonstrated the current challenges and future development of ionic COFs in design strategies and applications. Adsorption ; Ionic bonding ; Covalent bond ; Chemistry ; Catalysis ; Inorganic chemistry ; Chemical engineering ; Organic chemistry ; Ion ; Engineering Covalent Organic Framework Applications ; Metal-Organic Frameworks: Synthesis and Applications ; Advanced Photocatalysis Techniques
Authors: Xianyuan Liu | Jinman Zhou | Ying Xue | Xianyong Lu
Source: Nano-Micro Letters (article, 2024-04-15)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Structural Engineering of Hierarchical Magnetic/Carbon Nanocomposites via In Situ Growth for High-Efficient Electromagnetic Wave Absorption Materials exhibiting high-performance electromagnetic wave absorption have garnered considerable scientific and technological attention, yet encounter significant challenges. Developing new materials and innovative structural design concepts is crucial for expanding the application field of electromagnetic wave absorption. Particularly, hierarchical structure engineering has emerged as a promising approach to enhance the physical and chemical properties of materials, providing immense potential for creating versatile electromagnetic wave absorption materials. Herein, an exceptional multi-dimensional hierarchical structure was meticulously devised, unleashing the full microwave attenuation capabilities through in situ growth, self-reduction, and multi-heterogeneous interface integration. The hierarchical structure features a three-dimensional carbon framework, where magnetic nanoparticles grow in situ on the carbon skeleton, creating a necklace-like structure. Furthermore, magnetic nanosheets assemble within this framework. Enhanced impedance matching was achieved by precisely adjusting component proportions, and intelligent integration of diverse interfaces bolstered dielectric polarization. The obtain Fe<sub>3</sub>O<sub>4</sub>-Fe nanoparticles/carbon nanofibers/Al-Fe<sub>3</sub>O<sub>4</sub>-Fe nanosheets composites demonstrated outstanding performance with a minimum reflection loss (RL<sub>min</sub>) value of - 59.3 dB and an effective absorption bandwidth (RL ≤ - 10 dB) extending up to 5.6 GHz at 2.2 mm. These notable accomplishments offer fresh insights into the precision design of high-efficient electromagnetic wave absorption materials. Reflection loss ; Materials science ; Microwave ; Absorption (acoustics) ; Attenuation ; Nanocomposite ; Electromagnetic radiation ; Nanotechnology ; Electromagnetics ; Metamaterial ; Nanoparticle ; Computer science ; Optoelectronics ; Engineering physics ; Composite material ; Optics ; Engineering ; Telecommunications ; Physics Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies ; Flame retardant materials and properties
Authors: Manzhang Xu | Hongjia Ji | Lu Zheng | Weiwei Li | Jing Wang | Hanxin Wang | Lei Luo | Qianbo Lu | Xuetao Gan | Zheng Liu | Xuewen Wang | Wei Huang
Source: Nature Communications (article, 2024-01-17)
Field: Materials Science — Materials Chemistry

Reconfiguring nucleation for CVD growth of twisted bilayer MoS2 with a wide range of twist angles Twisted bilayer (TB) transition metal dichalcogenides (TMDCs) beyond TB-graphene are considered an ideal platform for investigating condensed matter physics, due to the moiré superlattices-related peculiar band structures and distinct electronic properties. The growth of large-area and high-quality TB-TMDCs with wide twist angles would be significant for exploring twist angle-dependent physics and applications, but remains challenging to implement. Here, we propose a reconfiguring nucleation chemical vapor deposition (CVD) strategy for directly synthesizing TB-MoS<sub>2</sub> with twist angles from 0° to 120°. The twist angles-dependent Moiré periodicity can be clearly observed, and the interlayer coupling shows a strong relationship to the twist angles. Moreover, the yield of TB-MoS<sub>2</sub> in bilayer MoS<sub>2</sub> and density of TB-MoS<sub>2</sub> are significantly improved to 17.2% and 28.9 pieces/mm<sup>2</sup> by tailoring gas flow rate and molar ratio of NaCl to MoO<sub>3</sub>. The proposed reconfiguring nucleation approach opens an avenue for the precise growth of TB-TMDCs for both fundamental research and practical applications. Nucleation ; Bilayer ; Materials science ; Twist ; Chemical vapor deposition ; Condensed matter physics ; Superlattice ; Bilayer graphene ; Transition metal ; Facet (psychology) ; Nanotechnology ; Chemical physics ; Crystallography ; Graphene ; Optoelectronics ; Physics ; Geometry ; Chemistry 2D Materials and Applications ; Perovskite Materials and Applications ; Graphene research and applications
Authors: Kai Xu | Xuelian Xiao | Linjing Wang | Ming Lou | Fang‐Ming Wang | Changheng Li | Hui Ping Ren | Xue Wang | Keke Chang
Source: Advanced Science (review, 2024-09-19)
Field: Materials Science — Materials Chemistry

Data‐Driven Materials Research and Development for Functional Coatings Functional coatings, including organic and inorganic coatings, play a vital role in various industries by providing a protective layer and introducing unique functionalities. However, its design often involves time-consuming experimentation with multiple materials and processing parameters. To overcome these limitations, data-driven approaches are gaining traction in materials science. In this paper, recent advances in data-driven materials research and development (R&D) for functional coatings, highlighting the importance, data sources, working processes, and applications of this paradigm are summarized. It is begun by discussing the challenges of traditional methods, then introduce typical data-driven processes. It is demonstrated how data-driven approaches enable the identification of correlations between input parameters and coating performance, thus allowing for efficient prediction and design. Furthermore, carefully selected case studies are presented across diverse industries that exemplify the effectiveness of data-driven methods in accelerating the discovery of new functional coatings with tailored properties. Finally, the emerging research directions, involving integrating advanced techniques and data from different sources, are addressed. Overall, this review provides an overview of data-driven materials R&D for functional coatings, shedding light on its potential and future developments. Computer science ; Data science ; Identification (biology) ; Coating ; Data-driven ; Systems engineering ; Nanotechnology ; Biochemical engineering ; Materials science ; Artificial intelligence ; Engineering Machine Learning in Materials Science ; Fuel Cells and Related Materials ; Corrosion Behavior and Inhibition
Authors: Junxiong Xiao | Mukun He | Beibei Zhan | Hua Guo | Jingliang Yang | Yali Zhang | Xiaosi Qi | Junwei Gu
Source: Materials Horizons (review, 2024-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Multifunctional microwave absorption materials: construction strategies and functional applications The widespread adoption of wireless communication technology, especially with the introduction of artificial intelligence and the Internet of Things, has greatly improved our quality of life. However, this progress has led to increased electromagnetic (EM) interference and pollution issues. The development of advanced microwave absorbing materials (MAMs) is one of the most feasible solutions to solve these problems, and has therefore received widespread attention. However, MAMs still face many limitations in practical applications and are not yet widely used. This paper presents a comprehensive review of the current status and future prospects of MAMs, and identifies the various challenges from practical application scenarios. Furthermore, strategies and principles for the construction of multifunctional MAMs are discussed in order to address the possible problems that are faced. This article also presents the potential applications of MAMs in other fields including environmental science, energy conversion, and medicine. Finally, an analysis of the potential outcomes and future challenges of multifunctional MAMs are presented. Microwave ; Materials science ; Absorption (acoustics) ; Nanotechnology ; Composite material ; Engineering ; Telecommunications Electromagnetic wave absorption materials ; Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies
Authors: Zih-An Chen | C.‐H. Wu | Si‐Han Wu | Chiung-Yin Huang | Chung‐Yuan Mou | Kuo‐Chen Wei | Yun Yen | I-Ting Chien | Sabiha Runa | Yi‐Ping Chen | Peilin Chen
Source: ACS Nano (article, 2024-05-08)
Field: Materials Science — Biomaterials

Receptor Ligand-Free Mesoporous Silica Nanoparticles: A Streamlined Strategy for Targeted Drug Delivery across the Blood–Brain Barrier Mesoporous silica nanoparticles (MSNs) represent a promising avenue for targeted brain tumor therapy. However, the blood-brain barrier (BBB) often presents a formidable obstacle to efficient drug delivery. This study introduces a ligand-free PEGylated MSN variant (RMSN<sub>25</sub>-PEG-TA) with a 25 nm size and a slight positive charge, which exhibits superior BBB penetration. Utilizing two-photon imaging, RMSN<sub>25</sub>-PEG-TA particles remained in circulation for over 24 h, indicating significant traversal beyond the cerebrovascular realm. Importantly, DOX@RMSN<sub>25</sub>-PEG-TA, our MSN loaded with doxorubicin (DOX), harnessed the enhanced permeability and retention (EPR) effect to achieve a 6-fold increase in brain accumulation compared to free DOX. In vivo evaluations confirmed the potent inhibition of orthotopic glioma growth by DOX@RMSN<sub>25</sub>-PEG-TA, extending survival rates in spontaneous brain tumor models by over 28% and offering an improved biosafety profile. Advanced LC-MS/MS investigations unveiled a distinctive protein corona surrounding RMSN<sub>25</sub>-PEG-TA, suggesting proteins such as apolipoprotein E and albumin could play pivotal roles in enabling its BBB penetration. Our results underscore the potential of ligand-free MSNs in treating brain tumors, which supports the development of future drug-nanoparticle design paradigms. Drug delivery ; Blood–brain barrier ; Mesoporous silica ; Biophysics ; Nanocarriers ; Nanomedicine ; In vivo ; Nanoparticle ; Nanotechnology ; Chemistry ; Doxorubicin ; PEG ratio ; Ligand (biochemistry) ; Targeted drug delivery ; Drug delivery to the brain ; Materials science ; Pharmacology ; Receptor ; Medicine ; Mesoporous material ; Biochemistry ; Biology ; Chemotherapy ; Internal medicine Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; Lanthanide and Transition Metal Complexes
Authors: Iftikhar Hussain | Umay Amara | Faiza Bibi | Abdul Hanan | Muhammad Nazim Lakhan | Irfan Ali Soomro | Amjad Khan | Irum Shaheen | Uzair Sajjad | Gokana Mohana Rani | Muhammad Sufyan Javed | Karim Khan | Muhammad Bilal Hanif | Mohammed A. Assiri | Sumanta Sahoo | Wail Al Zoubi | Debananda Mohapatra | Kaili Zhang
Source: Advances in Colloid and Interface Science (article, 2024-01-04)
Field: Materials Science — Materials Chemistry

Mo-based MXenes: Synthesis, properties, and applications MXenes ; Nanotechnology ; Materials science ; Computer science ; Biochemical engineering ; Engineering MXene and MAX Phase Materials ; 2D Materials and Applications ; Advanced Memory and Neural Computing
Authors: Wen‐Qiang Cao | Min Zhang | Mao‐Sheng Cao
Source: Advanced Functional Materials (article, 2024-08-27)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A Perspective of Tailoring Dielectric Genes for 2D Materials Toward Advanced Electromagnetic Functions Abstract 2D materials and their composites with electromagnetic properties are becoming increasingly popular. Obtaining insight into the nature of electromagnetic (EM) response manipulation is imperative to guide scientific research and technological exploitation at such a critical time. From this perspective, the dielectric genes of 2D material hybrids have been highlighted based on the recent literature. This endows an unlimited possibility of manipulating the EM response, even at elevated temperatures. The definitions and criteria of dielectric genes toward 2D material hybrids and composites are systematically clarified and summarized. The dielectric gene categories are successfully discriminated, including the conduction networks, intrinsic defects, impurity defects, and interfaces in the composite, and their temperature evolution is revealed in detail. More importantly, tuning strategies for microwave absorption, electromagnetic shielding effectiveness, and expanded electromagnetic functions are thoroughly discussed. Finally, significant predictions are provided for multispectral electromagnetic functions, and future applications of multifunctional exploration are anticipated. Dielectric genes will open an unexpected horizon for advanced functional materials in the coming 5G/6G age, providing a significant boost to promoting environmental electromagnetic protection, electromagnetic devices, and next‐generation smart devices. Materials science ; Perspective (graphical) ; Dielectric ; Nanotechnology ; Engineering ethics ; Engineering physics ; Optoelectronics ; Artificial intelligence ; Computer science ; Physics ; Engineering Electromagnetic wave absorption materials ; Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies
Authors: Hanyu Zheng | Quan Liu | Ivan I. Kravchenko | Xiaomeng Zhang | Yuankai Huo | Jason Valentine
Source: Nature Nanotechnology (article, 2024-01-04)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Multichannel meta-imagers for accelerating machine vision Computer science ; Machine vision ; Artificial intelligence ; Multiplexing ; Energy consumption ; Convolution (computer science) ; Artificial neural network ; Computer vision ; Telecommunications ; Electrical engineering Metamaterials and Metasurfaces Applications ; Neural Networks and Reservoir Computing ; Advanced Memory and Neural Computing
Authors: David Buterez | Jon Paul Janet | Steven J. Kiddle | Dino Oglić | Píetro Lió
Source: Nature Communications (article, 2024-02-26)
Field: Materials Science — Materials Chemistry

Transfer learning with graph neural networks for improved molecular property prediction in the multi-fidelity setting We investigate the potential of graph neural networks for transfer learning and improving molecular property prediction on sparse and expensive to acquire high-fidelity data by leveraging low-fidelity measurements as an inexpensive proxy for a targeted property of interest. This problem arises in discovery processes that rely on screening funnels for trading off the overall costs against throughput and accuracy. Typically, individual stages in these processes are loosely connected and each one generates data at different scale and fidelity. We consider this setup holistically and demonstrate empirically that existing transfer learning techniques for graph neural networks are generally unable to harness the information from multi-fidelity cascades. Here, we propose several effective transfer learning strategies and study them in transductive and inductive settings. Our analysis involves a collection of more than 28 million unique experimental protein-ligand interactions across 37 targets from drug discovery by high-throughput screening and 12 quantum properties from the dataset QMugs. The results indicate that transfer learning can improve the performance on sparse tasks by up to eight times while using an order of magnitude less high-fidelity training data. Moreover, the proposed methods consistently outperform existing transfer learning strategies for graph-structured data on drug discovery and quantum mechanics datasets. Computer science ; Fidelity ; Transfer of learning ; Machine learning ; Graph ; Property (philosophy) ; Artificial intelligence ; High fidelity ; Artificial neural network ; Data mining ; Theoretical computer science Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics