jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Suman Adhikari | Priyatosh Nath | Vishal Kumar Deb | Niranjan Das | Antara Banerjee | Surajit Pathak | Asim K. Duttaroy
Source: Frontiers in Pharmacology (review, 2025-06-17)
Field: Chemistry — Organic Chemistry

Pharmacological potential of natural chalcones: a recent studies and future perspective Chalcones isolated from natural sources are the primary metabolites of numerous biologically intriguing and pharmacologically essential drugs. Chalcones' pharmacological properties are believed to result from a double bond conjugated to carbonyl functionality. This review aims to summarise the research findings, showing naturally occurring chalcones as a preferred scaffold in medicinal chemistry. Natural chalcones have an intense antimicrobial activity that targets many pathogens, including viruses, bacteria, fungi, and protozoa. Strong antibiotic qualities are exhibited by chalcones, including 4-hydroxyderricin, licochalcone A and C, isobavachalcone, and pinocembrin chalcone. Furthermore, chalcones are promising pharmacological agents for cancer treatment; they inhibit angiogenesis, decrease metastasis, and induce death in tumor cells via diverse mechanisms. Chalcones are also considered promising therapeutic agents for diabetes, neurodegenerative diseases, and cardiovascular diseases because of their anti-inflammatory and antioxidant characteristics and ability to modify enzyme functioning. This review emphasizes several aspects, such as the biosynthesis of chalcones, preparation of chalcone derivatives, isolation of chalcones, structural features of chalcones, structure-activity relationship study, the role of natural chalcones in managing various diseases and illustrates their action mechanism to control disease progression. Perspective (graphical) ; Natural (archaeology) ; Medicine ; Pharmacology ; Chemistry ; Computational biology ; Biology ; Computer science Synthesis and biological activity ; Synthesis and Characterization of Heterocyclic Compounds ; Synthesis and Biological Evaluation
Authors: Liping Cui | Shu Zhang | Yüe Zhao | Xin-Yue Ge | Le Yang | Ke Li | Liubin Feng | Rengui Li | Jiajia Chen
Source: Nature Communications (article, 2025-04-17)
Field: Materials Science — Materials Chemistry

Tunable multi-electron redox polyoxometalates for decoupled water splitting driven by sunlight It remains a great challenge to explore redox mediators with multi-electron, suitable redox potential, and stable pH buffer ability to simulate the natural solar-to-fuel process. In this work, we present a defect engineering strategy to design soluble multi-electron redox polyoxometalates mediators to construct a photocatalysis-electrolysis relay system to decouple H<sub>2</sub> and O<sub>2</sub> evolution in solar-driven water splitting. The appropriate use of vanadium atoms to replace tungsten in the Dawson-type phosphotungstate successfully regulated the redox properties of the molecular clusters. Specifically, the single vanadium substitution structure ({P<sub>2</sub>W<sub>17</sub>V}) possesses 1-electron redox active and sequential proton-electron transfer behavior, while the tri-vanadium substituted cluster ({P<sub>2</sub>W<sub>15</sub>V<sub>3</sub>}) exhibits 3-electron redox active and cooperative proton electron transfer behavior. Based on the developed multi-electronic redox mediator with pH buffering capacity, suitable redox potential (0.6 V), and fast electron exchange rate, we build a photocatalysis-electrolysis relay water splitting system. This system allows for high capacity of solar energy storage through photocatalytic O<sub>2</sub> evolution using BiVO<sub>4</sub> photocatalyst and stable H<sub>2</sub> production with a high Faraday efficiency of over 98.5% in the electrolysis subsystem. Sunlight ; Redox ; Water splitting ; Electron ; Materials science ; Nanotechnology ; Chemistry ; Physics ; Inorganic chemistry ; Photocatalysis ; Optics ; Catalysis ; Quantum mechanics ; Biochemistry Polyoxometalates: Synthesis and Applications ; Advanced Photocatalysis Techniques ; TiO2 Photocatalysis and Solar Cells
Authors: Shuwen Xue | Wen See Tan | Shuifang Mao | Haibo Pan | Xingqian Ye | Natthawuddhi Donlao | Jinhu Tian
Source: Advanced Science (review, 2025-08-27)
Field: Materials Science — Biomaterials

Polyphenol‐Based Functional Materials: Structural Insights, Composite Strategies, and Biomedical Applications Polyphenols hold significant promise in pharmaceutical, biotechnology, and food-related applications owing to their potent free radical scavenging, antimicrobial, antitumor, and other properties. The unique chemical architecture, featuring multiple phenolic hydroxyl groups and aromatic ring systems-confers a high capacity for both non-covalent (e.g., hydrogen bonding, π-π stacking, metal ion coordination) and covalent interactions (e.g., Michael addition, Schiff base formation). These versatile interaction modes underpin the rational design and engineering of advanced composite materials with tailored functionalities. Recent advances in nanotechnology and materials science have catalyzed the integration of polyphenols with broad biomaterials, including metals, polysaccharides, and proteins, to enhance their biocompatibility, mechanical properties, and therapeutic efficacy. This review systematically explores the sources, structures, and physiological activities of polyphenols, elucidating their interaction mechanisms with different materials. Emphasis focuses on the design of polyphenol-based nanomaterials, bioactive scaffolds, and smart drug delivery platforms capable of modulating local microenvironments and orchestrating cellular responses for precision therapeutic interventions. The translational potential of these functional materials in regenerative and precision medicine is also critically examined, alongside key challenges such as stability, responsiveness, and the fine-tuning of release kinetics. Composite number ; Polyphenol ; Materials science ; Nanotechnology ; Biochemical engineering ; Chemistry ; Composite material ; Engineering ; Biochemistry Supramolecular Self-Assembly in Materials ; Polydiacetylene-based materials and applications ; Conducting polymers and applications
Authors: Zhaoxin Liu | Lingqiang Meng | Yanrong Jiang | Chao Li | Huanchao Gu | K. X. Zhao | Ji Zhang | Hong Meng | Yi Ren
Source: Journal of the American Chemical Society (article, 2025-01-20)
Field: Chemistry — Organic Chemistry

Hyperconjugation Engineering of π-Extended Azaphosphinines for Designing Tunable Thermally Activated Delayed Fluorescence Emitters Implanting heteroatoms into organic π-conjugated molecules (OCMS) offered a great opportunity to fine-tune the chemical structures and optoelectronic properties. This work describes a new family of 1,4-azaphosphinines with extended σ-π hyperconjugations. The photophysical studies revealed that azaphosphinines exhibited narrow-band thermally activated delayed fluorescence (TADF) ( full width at half-maximum: 26-40 nm). According to the orbital localization analysis and natural bond orbital analysis, the effective σ*-π* hyperconjugation is believed to induce the multiple-resonance (MR) TADF, which is distinct from the p-π conjugation-induced MR-TADF in BN systems. Although having the large <sub>Δ</sub><i>E</i><sub>S1-T1</sub>s (>3.0 ev), the study suggested that σ*-π hyperconjugation endowed the system with the structural vibration favorable for the spin-vibronic-assisted RISC. Having the tunable p-centers (lp, O, S, Se, and Me<sup>+</sup>), azaphosphinines showed a fine-tuned TADF. Generally, azaphosphinines with strong σ*-π* hyperconjugations showed small <sub>Δ</sub><i>E</i><sub>S1-T1</sub>s, efficient RISCs, and high PLQYs. Leveraging on the efficient hyperconjugations, TADF emission of the system spanned from UV-blue to green. Particularly, extended azaphosphinines exhibited the high photoluminescence quantum yields (74% in toluene and 92% in the 10% doped PMMA). As a proof of concept, two azaphosphinines with a PO center were applied as the light-emitting materials in organic lighting-emitting diodes. The devices showed the narrow-band UV- and deep-blue emission with EQE as high as 10.3%. The current study offered us a new strategy, namely, σ-π hyperconjugation-induced MR-TADF, for designing OCMs with tunable light-emitting properties. Chemistry ; Hyperconjugation ; Fluorescence ; Photochemistry ; Nanotechnology ; Organic chemistry ; Molecule ; Optics Organoboron and organosilicon chemistry ; Sulfur-Based Synthesis Techniques ; Synthesis and characterization of novel inorganic/organometallic compounds
Authors: Nils Bäumer | Shiho Yamada | Soichiro Ogi | Shigehiro Yamaguchi
Source: Journal of the American Chemical Society (article, 2025-02-28)
Field: Materials Science — Biomaterials

Interfacing Flexible Design and Social Self-Sorting Enables Comprehensive Control over Photophysical and Self-Assembly Properties of Supramolecular Polymers Supramolecular self-assembly offers an intriguing approach to construct microarchitectures, which combine properties of their molecular constituents with dynamic supramolecular features. Control over intermolecular interactions and their resulting properties can sometimes be achieved by targeted design. However, it is often unfeasible to transfer the insights gained from a specific supramolecular synthon to another chromophore without tedious synthetic work guided by trial and error. Herein we demonstrate how a flexible molecular design approach enables access to a diverse library of photophysical properties, which can be further diversified by social self-sorting strategies using a second supramolecular building block as a modulator. By intercalation into the supramolecular polymer the modulator can disrupt interchromophore interactions and modulate the ensembles emissive properties across the visible color space by simply adjusting the ratio between the two building blocks. Furthermore, by combining a chromophore appended synthon with a different morphology than the modulator the mesoscopic size distribution of the coassemblies can be modified to resemble either of its constituents. Crucially, this moldability is not only achievable for systems under thermodynamic control, but can be also employed to tune photophysical properties and thermal stability profiles of kinetically controlled states. Finally, the thermodynamic stability of the modulated polymers can be adjusted by varying the amount of solubilizing alkyl chains in the ensemble. This peripheral stabilization approach does not affect the engineered photophysical or supramolecular properties. Our results demonstrate how flexible molecular design enriched by a supramolecular modulator can offer access to a wide variety of photophysical properties and enable unique fine-tuning of various supramolecular properties. Interfacing ; Chemistry ; Supramolecular chemistry ; Sorting ; Self-assembly ; Nanotechnology ; Polymer ; Supramolecular polymers ; Computer hardware ; Molecule ; Organic chemistry ; Computer science Supramolecular Self-Assembly in Materials ; Polydiacetylene-based materials and applications ; Luminescence and Fluorescent Materials
Authors: Gao-Feng Liu | Zhiwei Li | Zijun Huang | Zhiyuan Zhou | Yingxian Li | Anlian Huang | Zhengqing Cai | Gangfeng Ouyang | Bao‐Hui Ye | Yue‐Biao Zhang
Source: Journal of the American Chemical Society (article, 2025-01-03)
Field: Materials Science — Materials Chemistry

Rapid Crystallization and Versatile Metalation of Acetylhydrazone-Linked Covalent Organic Frameworks for Heterogenous Catalysis Covalent organic frameworks (COFs) hold promise in heterogeneous metal catalysis benefiting from their robust, crystalline, and porous structures. However, synthetic challenges persist in prolonged crystallization times, limited metal loading, and uncertain coordination environments. Here, we present the rapid crystallization and versatile metalation of new acetylhydrazone-linked COFs (AH-COFs) by condensation of ketone and hydrazide components, featuring full conversion within 30 min under open-air and mild conditions. The obtained AH-COFs exhibit exceptional thermal and chemical stability, maintaining high crystallinity and microporosity even under harsh conditions. This method shows the versatility of <i>in situ</i> metalation through subcomponent assembly with a wide range of metal centers, and the delicate control of coordination geometry through isoreticular functionalization for fine-tuning of the pore environments and metal catalytic activity. The metalated AH-COFs demonstrate excellent catalytic performance: AH-COF-2-Zn achieves high efficiency in CO<sub>2</sub> cycloaddition, while AH-COF-1-Cu-PSM achieves near-quantitative conversion in copper-catalyzed azide-alkyne cycloaddition (CuAAC) reactions, with both catalysts retaining their activity over multiple cycles. This study offers an efficient and versatile method for the rapid crystallization of designable, stable, and functional COFs, heading to practical applications prioritized on efficiency, scalability, and sustainability. Chemistry ; Metalation ; Crystallization ; Covalent bond ; Crystallinity ; Catalysis ; Aldol condensation ; Thermal stability ; Metal-organic framework ; Ketone ; Combinatorial chemistry ; Chemical engineering ; Nanotechnology ; Organic chemistry ; Crystallography ; Materials science ; Adsorption Covalent Organic Framework Applications ; Metal-Organic Frameworks: Synthesis and Applications ; Advanced Photocatalysis Techniques
Authors: Wenhao Li | Sheng Wu | Jing Ren | Puxian Xiong
Source: Advanced Functional Materials (article, 2025-04-27)
Field: Materials Science — Materials Chemistry

Defects in Inorganic Mechanoluminescent Phosphors: Insights and Impacts Abstract Mechanoluminescence (ML), the light emission of materials in response to mechanical stimuli, has gained significant attention in various fields due to the in situ and real‐time “force to light” converting ability. Defects dominate the ML process, either for accommodating carriers or as sites for carrier recombination. However, comprehensive discussions on ML‐based defects are rarely reported. The review opens with an exploration of recent progress in ML research, highlighting the central role of defects in ML. A range of defect types commonly exist in ML materials are firstly introduced, which aims to highlight the profound influences on ML. Subsequently reported defect‐dominated phosphors are researched to elucidate the intricate relationship between specific defect types and their influence on ML performance, shedding light on the underlying luminescence mechanisms. Afterward, experimental techniques for defect characterization are also researched to demonstrate how defects work in ML. The role of computational modeling is confirmed to act as a powerful tool for investigating the atomistic mechanisms of defect‐related processes and enabling precise control of defects in ML materials. In conclusion, this mini‐review underscores the centrality of defects in ML materials, offering an integrated perspective on their profound influence and potential to guide future research endeavors. Materials science ; Phosphor ; Mechanoluminescence ; Nanotechnology ; Composite material ; Optoelectronics Luminescence Properties of Advanced Materials ; Radiation Detection and Scintillator Technologies ; Luminescence and Fluorescent Materials
Authors: Yushi Zou | Austin H. Cheng | Abdulrahman Aldossary | Jie Bai | Shi Xuan Leong | Jorge A. Campos-Gonzalez-Angulo | Changhyeok Choi | Cher Tian Ser | Gary Tom | Andrew Wang | Zijian Zhang | Ilya Yakavets | Hao Han | Chris Crebolder | Varinia Bernales | Alán Aspuru‐Guzik
Source: Matter (article, 2025-07-01)
Field: Materials Science — Materials Chemistry

El Agente: An autonomous agent for quantum chemistry <h2>Summary</h2> Computational chemistry tools are widely used to study the behavior of chemical phenomena. Yet, the complexity of these tools can make them inaccessible to non-specialists and challenging even for experts. In this work, we introduce El Agente Q, an LLM-based multi-agent system that dynamically generates and executes quantum chemistry workflows from natural language user prompts. The system is built on a novel cognitive architecture featuring a hierarchical memory framework that enables flexible task decomposition, adaptive tool selection, post-analysis, and autonomous file handling and submission. El Agente Q is benchmarked on six university-level course exercises and two case studies, demonstrating robust problem-solving performance (averaging <i>></i>87% task success) and adaptive error handling through <i>in situ</i> debugging. It also supports longer-term, multi-step task execution for more complex workflows, while maintaining transparency through detailed action trace logs. Together, these capabilities lay the foundation for increasingly autonomous and accessible quantum chemistry. Chemistry ; Quantum ; Physics ; Quantum mechanics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Tarek Khater | Sarah Alkhatib | Aamna AlShehhi | Charalampos Pitsalidis | Anna Maria Pappa | Sơn Tùng Ngô | Vincent Chan | Vi Khanh Truong
Source: Journal of Cheminformatics (review, 2025-08-04)
Field: Materials Science — Materials Chemistry

Generative artificial intelligence based models optimization towards molecule design enhancement Generative artificial intelligence (GenAI) models have emerged as a transformative tool for addressing the complex challenges of drug discovery, enabling the design of structurally diverse, chemically valid, and functionally relevant molecules. Despite significant advancements, the rapid expansion of GenAI applications still faces challenges related to prediction accuracy, molecular validity, and optimization for drug-like properties. This review provides a comprehensive analysis of recent techniques and strategies aimed at enhancing the performance of GenAI models in molecular design. We explore key generative architectures, including variational autoencoders, generative adversarial networks, and transformer-based models, highlighting their unique contributions to drug discovery. Additionally, we discuss critical advancements such as reinforcement learning, multi-objective optimization, and the integration of domain-specific chemical knowledge, which collectively enhance molecular validity, novelty, and drug-likeness. Also, the review examines persistent challenges, including data quality limitations, model interpretability, and the need for improved objective functions, while offering insights into future research directions. By mapping the evolving landscape of GenAI-driven molecular design and providing strategic guidance for overcoming existing limitations, this review serves as an essential resource for researchers leveraging GenAI in drug discovery. Computer science ; Generative grammar ; Artificial intelligence ; Generative model ; Machine learning ; Data science Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Yuping Huang | Ziang Li | Zhaoying Bian | Haojun Jin | Guoqing Zheng | Dong Hu | Ye Sun | Chenlong Fan | Weijun Xie | Huimin Fang
Source: Foods (review, 2025-01-16)
Field: Chemistry — Analytical Chemistry

Overview of Deep Learning and Nondestructive Detection Technology for Quality Assessment of Tomatoes Tomato, as the vegetable queen, is cultivated worldwide due to its rich nutrient content and unique flavor. Nondestructive technology provides efficient and noninvasive solutions for the quality assessment of tomatoes. However, processing the substantial datasets to achieve a robust model and enhance detection performance for nondestructive technology is a great challenge until deep learning is developed. The aim of this paper is to provide a systematical overview of the principles and application for three categories of nondestructive detection techniques based on mechanical characterization, electromagnetic characterization, as well as electrochemical sensors. Tomato quality assessment is analyzed, and the characteristics of different nondestructive techniques are compared. Various data analysis methods based on deep learning are explored and the applications in tomato assessment using nondestructive techniques with deep learning are also summarized. Limitations and future expectations for the quality assessment of the tomato industry by nondestructive techniques along with deep learning are discussed. The ongoing advancements in optical equipment and deep learning methods lead to a promising outlook for the application in the tomato industry and agricultural engineering. Nondestructive testing ; Deep learning ; Quality (philosophy) ; Artificial intelligence ; Computer science ; Characterization (materials science) ; Quality assessment ; Engineering ; Biochemical engineering ; Nanotechnology ; Materials science ; Reliability engineering ; Evaluation methods Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Fanjie Xu | Wentao Guo | Feng Wang | Lin Yao | Hongshuai Wang | Fujie Tang | Zhifeng Gao | Linfeng Zhang | E Weinan | Zhong‐Qun Tian | Jun Cheng
Source: Nature Computational Science (article, 2025-03-28)
Field: Chemistry — Spectroscopy

Toward a unified benchmark and framework for deep learning-based prediction of nuclear magnetic resonance chemical shifts Benchmark (surveying) ; Deep learning ; Nuclear magnetic resonance ; Computer science ; Artificial intelligence ; Machine learning ; Physics ; Geology Molecular spectroscopy and chirality ; Metabolomics and Mass Spectrometry Studies ; Computational Drug Discovery Methods