jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Xiaofei Lü | Penghui Zhang | Hanqian Pan | Pengyuan Yin | Peixin Zhang | Lifeng Yang | Xian Suo | Xili Cui | Huabin Xing
Source: Chemical Society Reviews (review, 2025-01-01)
Field: Chemistry — Inorganic Chemistry

Ionic porous materials: from synthetic strategies to applications in gas separation and catalysis Ionic porous materials possess a unique combination of tunable pore sizes and task-specific interactions between guest molecules and the charged frameworks, which endow them with versatility across diverse domains in chemistry and materials science. Significant advancements in their applications for gas separation and catalysis have been achieved in recent years due to the incorporation of ionic functionalities and ultra-microporous structures that enable molecular-scale recognition of guest molecules. This review summarizes recent advancements in the synthetic strategies of ionic porous materials, establishing design guidelines for the incorporation of ionic moieties into the backbone to fine-tune pore sizes and chemistry. It highlights the synergistic interplay of task-specific interactions with custom-designed pore structures in key applications, including adsorption separation, membrane separation, and gas conversion. Additionally, it examines structure-property relationships, offering deeper insights into enhancing performance. The report also addresses the current challenges in the practical application of these materials. Finally, the review provides future perspectives on ionic porous materials from both scientific and industrial viewpoints. Overall, this review aims to provide insights into pore structure and chemistry, supporting the precise placement of ionic functionalities. Ionic bonding ; Porous medium ; Porosity ; Gas separation ; Catalysis ; Nanotechnology ; Materials science ; Chemistry ; Biochemical engineering ; Chemical engineering ; Ion ; Organic chemistry ; Engineering ; Membrane Metal-Organic Frameworks: Synthesis and Applications ; Membrane Separation and Gas Transport ; Covalent Organic Framework Applications
Authors: Paolo Yammine | Ali El Safadi | Rima Kassab | Hanna El‐Nakat | Pierre J. Obeid | Zeina Nasr | Tony Tannous | Nouha Sari‐Chmayssem | Agapy Mansour | Ayman Chmayssem
Source: Chemistry (article, 2025-04-11)
Field: Chemistry — Organic Chemistry

Types of Crosslinkers and Their Applications in Biomaterials and Biomembranes Biomaterials and biomembranes play a crucial role in a variety of applications, particularly in the medical field due to their ability to mimic natural biological structures and functions. Crosslinkers play also an important role in enhancing the structural integrity and functionality of biomaterials and in the design of biomembranes. This review article explores the fundamentals of biomaterials and biomembranes, with a particular focus on the role of crosslinkers in biology, chemistry and medicine. We explore the various types of crosslinkers commonly used in biomaterials synthesis, examining their chemical structure, classification, and synthesis methods. Additionally, we analyze the biological properties of crosslinkers and their interactions, highlighting their biological impact, particularly in cellular behavior and cytotoxicity. This article further emphasizes recent advances and innovation, particularly in tissue engineering, drug delivery, and wound healing. Finally, we conclude by addressing current challenges and suggesting potential futures directions for research in this field. Polymer science ; Nanotechnology ; Chemistry ; Materials science Photopolymerization techniques and applications ; Additive Manufacturing and 3D Printing Technologies ; 3D Printing in Biomedical Research
Authors: Jiawei Sun | Áron Péter | Jiayan He | Jet Tsien | Haoxiang Zhang | David A. Cagan | Benjamin Vokits | David S. Peters | Martins S. Oderinde | Michael D. Mandler | Paul Richardson | D.-G. Chen | Maximilian D. Palkowitz | Nicholas Raheja | Yu Kawamata | Phil S. Baran
Source: Science (article, 2025-03-06)
Field: Chemistry — Organic Chemistry

Sulfonyl hydrazides as a general redox-neutral platform for radical cross-coupling Sulfonyl hydrazides are stable and usually crystalline substances that can be accessed in a variety of ways, including transiently from hydrazones, to achieve a net reductive arylation of carbonyl compounds. We show their utility as versatile radical precursors, as exemplified with seven C-C bond-forming, redox-neutral cross-couplings with activated olefins, alkyl halides, redox-active esters, aryl halides, alkenyl halides, alkynyl halides, and a trifluoromethylating reagent, to forge C(sp<sup>3</sup>)-C(sp<sup>3</sup>), C(sp<sup>3</sup>)-C(sp<sup>2</sup>), and C(sp<sup>3</sup>)-C(sp) bonds. Exogenous redox (chemical, photo/electrochemical) additives are not necessary because these functional groups serve the dual role of radical precursor and electron donor. The homogeneous, water-compatible reaction conditions are operationally simple and contribute to streamlining synthesis and mild late-stage functionalization. Redox ; Sulfonyl ; Chemistry ; Coupling (piping) ; Combinatorial chemistry ; Computational chemistry ; Materials science ; Organic chemistry Radical Photochemical Reactions ; Sulfur-Based Synthesis Techniques ; Catalytic C–H Functionalization Methods
Authors: Kehinde Olonisakin | Amar K. Mohanty | Mahendra Thimmanagari | Manjusri Misra
Source: Green Chemistry (article, 2025-01-01)
Field: Materials Science — Biomaterials

Recent advances in biodegradable polymer blends and their biocomposites: a comprehensive review Integrating biodegradable polymer blends, compatibilization strategies, and filler reinforcement to develop biodegradable composites for sustainable applications. Compatibilization ; Biodegradable polymer ; Polymer blend ; Biodegradation ; Filler (materials) ; Polymer biodegradable polymer synthesis and properties ; Electrospun Nanofibers in Biomedical Applications ; Microplastics and Plastic Pollution
Authors: Yiming Zhao | Yongjia Zhao | Jian Wang | Zhuo Wang
Source: Industrial & Engineering Chemistry Research (review, 2025-02-24)
Field: Materials Science — Materials Chemistry

Artificial Intelligence Meets Laboratory Automation in Discovery and Synthesis of Metal–Organic Frameworks: A Review This review discusses the transformative impact of the convergence of artificial intelligence (AI) and laboratory automation on the discovery and synthesis of metal–organic frameworks (MOFs). MOFs, known for their tunable structures and extensive applications in fields such as energy storage, drug delivery, and environmental remediation, pose significant challenges due to their complex synthesis processes and high structural diversity. Laboratory automation has streamlined repetitive tasks, enabled high-throughput screening of reaction conditions, and accelerated the optimization of synthesis protocols. The integration of AI, particularly Transformers and large language models (LLMs), has further revolutionized MOF research by analyzing massive data sets, predicting material properties, and guiding experimental design. The emergence of self-driving laboratories (SDLs), where AI-driven decision-making is coupled with automated experimentation, represents the next frontier in MOF research. While challenges remain in fully realizing the potential of this synergistic approach, the integration of AI and laboratory automation heralds a new era of efficiency and innovation in the discovery and engineering of MOF materials. Automation ; Metal-organic framework ; Laboratory automation ; Computer science ; Nanotechnology ; Biochemical engineering ; Data science ; Chemistry ; Process engineering ; Systems engineering ; Engineering ; Materials science ; Organic chemistry ; Adsorption Machine Learning in Materials Science ; Metal-Organic Frameworks: Synthesis and Applications ; Catalysis and Oxidation Reactions
Authors: Rajat Goyal | Shivam Maharaj | Pawan Kumar | M. Chandrasekhar
Source: Journal of Materials Science Materials in Engineering (review, 2025-01-16)
Field: Materials Science — Materials Chemistry

Exploring quantum materials and applications: a review Abstract Researchers in condensed matter physics are currently exploring new materials for specific use in various applications. The peculiar properties of quantum materials (QMs) have garnered significant attention because they have the potential to serve as building blocks for entirely new technologies in modern science and technology. QMs exhibit emerging phenomena governed by quantum confinement, strong electronic correlations, topology, and symmetry, making them exceptional materials. This review paper provides an overview of these unique properties, different types of QMs, and their applications with the latest case studies, presenting a prospective outlook on QMs in multiple domains. Computer science ; Nanotechnology ; Materials science Electronic and Structural Properties of Oxides ; Advanced Condensed Matter Physics ; 2D Materials and Applications
Authors: Ziqi Fu | Pengfei Huang | Xiaoyang Wang | Wei‐Di Liu | Lingchang Kong | Kang Chen | Jinyang Li | Yanan Chen
Source: Advanced Energy Materials (article, 2025-05-12)
Field: Materials Science — Materials Chemistry

Artificial Intelligence‐Assisted Ultrafast High‐Throughput Screening of High‐Entropy Hydrogen Evolution Reaction Catalysts Abstract The development of high‐entropy alloy (HEA) catalysts is hindered by the “combinatorial explosion” challenge inherent to their complex component design. This study presents an artificial intelligence‐assisted high‐throughput framework that synergizes large language models (LLMs) for literature mining and genetic algorithms (GAs) for iterative optimization to overcome this challenge. Here, LLMs analyzed 14 242 publications to identify 10 critical hydrogen evolution reaction (HER)‐active elements (Fe, Co, Ni, Pt, etc.), narrowing the candidate pool to 126 Pt‐based HEA combinations. GA‐driven experiment optimizes this subset via ultrafast high‐throughput material synthesis and screening using ultrafast high‐temperature thermal shock technology, achieving convergence in 4 iterations (24 samples) for 60% reduction of the versus conventional GA approaches. The optimal IrCuNiPdPt/C catalyst exhibits the record‐low HER overpotentials of 25.5 and 119 mV at 10 and 100 mA cm⁻ 2 , surpassing commercial Pt/C by 49% and 18%, respectively, which demonstrates 300‐h stability with negligible decay. This work establishes a paradigm‐shifting strategy bridging computational intelligence and autonomous experiment, that slashes the discovery time from millennia to hours, enabling rational design of multi‐component catalysts for sustainable energy applications. Materials science ; Throughput ; Catalysis ; Ultrashort pulse ; Entropy (arrow of time) ; High-throughput screening ; Nanotechnology ; Computer science ; Thermodynamics ; Organic chemistry ; Bioinformatics ; Biology ; Telecommunications ; Physics ; Chemistry ; Quantum mechanics Machine Learning in Materials Science ; Electrocatalysts for Energy Conversion ; Catalytic Processes in Materials Science
Authors: Zhichen Lun | Xiaohong Wu | Jiajun Dong | Bin Wu
Source: Foods (review, 2025-07-02)
Field: Chemistry — Analytical Chemistry

Deep Learning-Enhanced Spectroscopic Technologies for Food Quality Assessment: Convergence and Emerging Frontiers Nowadays, the development of the food industry and economic recovery have driven escalating consumer demands for high-quality, nutritious, and safe food products, and spectroscopic technologies are increasingly prominent as essential tools for food quality inspection. Concurrently, the rapid rise of artificial intelligence (AI) has created new opportunities for food quality detection. As a critical branch of AI, deep learning synergizes with spectroscopic technologies to enhance spectral data processing accuracy, enable real-time decision making, and address challenges from complex matrices and spectral noise. This review summarizes six cutting-edge nondestructive spectroscopic and imaging technologies, near-infrared/mid-infrared spectroscopy, Raman spectroscopy, fluorescence spectroscopy, hyperspectral imaging (spanning the UV, visible, and NIR regions, to simultaneously capture both spatial distribution and spectral signatures of sample constituents), terahertz spectroscopy, and nuclear magnetic resonance (NMR), along with their transformative applications. We systematically elucidate the fundamental principles and distinctive merits of each technological approach, with a particular focus on their deep learning-based integration with spectral fusion techniques and hybrid spectral-heterogeneous fusion methodologies. Our analysis reveals that the synergy between spectroscopic technologies and deep learning demonstrates unparalleled superiority in speed, precision, and non-invasiveness. Future research should prioritize three directions: multimodal integration of spectroscopic technologies, edge computing in portable devices, and AI-driven applications, ultimately establishing a high-precision and sustainable food quality inspection system spanning from production to consumption. Hyperspectral imaging ; Computer science ; Artificial intelligence ; Deep learning ; Emerging technologies ; Quality (philosophy) ; Machine learning ; Data science ; Nanotechnology ; Systems engineering ; Materials science ; Engineering ; Physics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Advanced Chemical Sensor Technologies
Authors: Axel Tosello Gardini | Umberto Raucci | Michele Parrinello
Source: Nature Communications (article, 2025-03-12)
Field: Materials Science — Materials Chemistry

Machine learning-driven molecular dynamics unveils a bulk phase transformation driving ammonia synthesis on barium hydride The modern view of industrial heterogeneous catalysis is evolving from the traditional static paradigm where the catalyst merely provides active sites, to that of a functional material in which dynamics plays a crucial role. Using machine learning-driven molecular dynamics simulations, we confirm this picture for the ammonia synthesis catalysed by BaH<sub>2</sub>. Recent experiments show that this system acts as a highly efficient catalyst, but only when exposed first to N<sub>2</sub> and then to H<sub>2</sub> in a chemical looping process. Our simulations reveal that when first exposed to N<sub>2</sub>, BaH<sub>2</sub> undergoes a profound change, transforming into a superionic mixed compound, BaH<sub>2-2x</sub>(NH)<sub>x</sub>, characterized by a high mobility of both hydrides and imides. This transformation is not limited to the surface but involves the entire catalyst. When this compound is exposed to H<sub>2</sub> in the second step of the looping process, ammonia is readily formed and released, a process greatly facilitated by the high ionic mobility. Once all the nitrogen hydrides are hydrogenated, the system reverts to its initial state, ready for the next looping cycle. Our microscopic analysis underlines the dynamic nature of this heterogeneous catalyst, which does not merely serve as static platform for reactions, rather it is a dynamic entity that evolves under reaction conditions. Barium ; Ammonia ; Hydride ; Molecular dynamics ; Phase (matter) ; Transformation (genetics) ; Ammonia production ; Materials science ; Dynamics (music) ; Nanotechnology ; Chemical physics ; Chemistry ; Computer science ; Inorganic chemistry ; Computational chemistry ; Physics ; Metal ; Biochemistry ; Organic chemistry ; Metallurgy Machine Learning in Materials Science ; Ammonia Synthesis and Nitrogen Reduction ; Hydrogen Storage and Materials
Authors: Heng Zhang | Qingxia He | Fei Zhang | Yanshuai Duan | Mengmeng Qin | Wei Feng
Source: Advanced Materials (review, 2025-05-16)
Field: Materials Science — Materials Chemistry

Biomimetic Intelligent Thermal Management Materials: From Nature‐Inspired Design to Machine‐Learning‐Driven Discovery The development of biomimetic intelligent thermal management materials (BITMs) is essential for tackling thermal management challenges in electronics and aerospace applications. These materials possess not only exceptional thermal conductivity but also environmental compatibility. However, developing such materials necessitates overcoming intricate challenges, such as precise control over the material structure and optimization of the material's properties and stability. This review comprehensively overviews the research progress of BITMs, emphasizing the synergy between biomimetic design principles and artificial-intelligence-driven methodologies to enhance their performance. The unique nature-inspired structures are explored and valuable insights are provided into adaptive thermal management strategies, which can be further enhanced through data analytics and machine learning (ML). This review offers insights into overcoming design challenges and outlines future prospects for advanced BITMs by integrating ML and biomimetic design principles. Materials science ; Biomimetics ; Nanotechnology ; Biomimetic materials ; Thermal management of electronic devices and systems ; Systems engineering ; Construction engineering ; Mechanical engineering ; Engineering Machine Learning in Materials Science ; Thermal Radiation and Cooling Technologies ; Advanced Thermoelectric Materials and Devices
Authors: Dilgam Ahmadli | Sven Müller | Yuanhao Xie | Tomáš Šmejkal | Simon Jaeckh | Andrei V. Iosub | Simon R. Williams | Tobias Ritter
Source: Journal of the American Chemical Society (article, 2025-01-22)
Field: Chemistry — Organic Chemistry

Standardized Approach for Diversification of Complex Small Molecules via Aryl Thianthrenium Salts Thianthrenation is a useful strategy for the late-stage diversification of complex small molecules owing to the positional selectivity and the synthetic versatility of thianthrenium salts as electrophilic linchpins. However, substrate-dependent identification of suitable reaction conditions for thianthrenation can be difficult. Reported reaction conditions for the functionalization of thianthrenium salts vary significantly and, in some instances, lack robustness and practicality. Herein, we report a generalized approach for the preparation of thianthrenium salts and two reaction manifolds for practical, robust, and parallel diversification of thianthrenium salts. Chemistry ; Aryl ; Diversification (marketing strategy) ; Molecule ; Small molecule ; Combinatorial chemistry ; Computational chemistry ; Organic chemistry ; Biochemistry ; Business Catalytic C–H Functionalization Methods ; Catalytic Cross-Coupling Reactions ; Radical Photochemical Reactions
Authors: Xiao Wang | Chenhao Shu | Gang Wang | Peng Han | Long Zheng | Lei Xu | Ye Chen
Source: Nanoscale (review, 2025-01-01)
Field: Materials Science — Materials Chemistry

Recent progress of noble metal-based nanozymes: structural engineering and biomedical applications Due to their tunable catalytic activity, high chemical stability, and favorable electronic structure, noble metal-based nanozymes that can mimic important biocatalytic processes have attracted great attention. Rational structural design of noble metal-based nanozymes can endow them with excellent enzyme-like activities, enhanced sensitivity and stability, as well as unique physicochemical functionalities towards various biomedical applications such as sensing, diagnostics, and disease treatment. This review summarizes the recent progress in structural engineering of noble metal-based nanozymes and emphasizes the relationship between key structural factors of nanozymes and their enzyme-like properties in various enzyme-mimicking reactions. The diverse applications of noble metal-based nanozymes in biosensors, antibiosis, and disease treatment are further introduced. Finally, current challenges and future research directions in noble metal-based nanozymes are discussed. This review could offer scientific guidance to design and fabricate advanced nanozymes with enhanced functionality and performance towards clinical, environmental and biomedical applications. Noble metal ; Nanotechnology ; Rational design ; Materials science ; Catalysis ; Metal ; Biochemical engineering ; Chemistry ; Engineering ; Metallurgy Advanced Nanomaterials in Catalysis ; Nanocluster Synthesis and Applications ; Nanoplatforms for cancer theranostics
Authors: Aslı Çakan | Chanaprom Cholsuk | Angus Gale | Mehran Kianinia | Serkan Paçal | Serkan Ateş | Igor Aharonovich | Milos Toth | Tobias Vogl
Source: Advanced Optical Materials (article, 2025-02-13)
Field: Materials Science — Materials Chemistry

Quantum Optics Applications of Hexagonal Boron Nitride Defects Abstract Hexagonal boron nitride (hBN) has emerged as a compelling platform for both classical and quantum technologies. In particular, the past decade has witnessed a surge of novel ideas and developments, which may be overwhelming for newcomers to the field. This review provides an overview of the fundamental concepts and key applications of hBN, including quantum sensing, quantum key distribution, quantum computing, and quantum memory. Additionally, critical experimental and theoretical advances that have expanded the capabilities of hBN are highlighted, in a cohesive and accessible manner. The objective is to equip readers with a comprehensive understanding of the diverse applications of hBN, and provide insights into ongoing research efforts. Materials science ; Hexagonal boron nitride ; Hexagonal crystal system ; Quantum optics ; Optoelectronics ; Nitride ; Boron nitride ; Nanotechnology ; Engineering physics ; Optics ; Crystallography ; Graphene ; Physics Diamond and Carbon-based Materials Research ; Graphene research and applications ; Boron and Carbon Nanomaterials Research