jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Juan Zeng | Xinxin Tang | Dalian Qin | Yuling Lü | Xiaogang Zhou | Feng Chi | Jianing Mi | Hudan Pan | Jianming Wu | Bin Huang | Anguo Wu
Source: Journal of Nanobiotechnology (review, 2025-10-15)
Field: Materials Science — Biomaterials

Engineered GLP-1R-targeting nanoplatforms: multimodal therapeutics in human diseases Glucagon-like peptide-1 receptor (GLP-1R) is a versatile therapeutic target that regulates glucose homeostasis, cardiovascular function, neuroprotection, and immune responses. Native GLP-1 undergoes rapid enzymatic degradation, limiting its clinical utility. To overcome these challenges, engineered GLP-1 analogues and nanotechnology-enabled delivery systems have emerged. This review summarizes recent advances in GLP-1R-targeted nanoplatforms, including lipid nanoparticles, polymeric carriers, inorganic nanoparticles, and biomimetic scaffolds that improve peptide stability, prolong circulation half-life, and enable selective tissue targeting. Ligand engineering approaches, such as site-specific peptide conjugation and fatty acid modifications, enhance receptor affinity and targeting precision. Stimuli-responsive release strategies that respond to glucose levels, pH shifts, and redox conditions restrict drug activation to diseased microenvironments. Multifunctional theranostic constructs co-encapsulate imaging probes with therapeutics, permitting real-time monitoring of biodistribution and receptor engagement. We discuss key translational challenges, including scalable manufacturing processes, quality control of particle size, ligand density, and release kinetics, and long-term biosafety concerns associated with inorganic materials and immune activation. Variability in GLP-1R expression among patient populations influences delivery efficacy, motivating personalized strategies guided by artificial intelligence and digital twin modeling. Emerging applications in neurodegenerative disorders, oncology, cardiovascular disease and immunology demonstrate the expanding clinical potential of GLP-1R nanomedicines. By integrating insights from materials science, pharmacology and preclinical studies, this review provides a cohesive framework for the rational design, evaluation and clinical translation of next-generation GLP-1R-targeted nanotherapeutics. Future directions include integration with genomic profiling and real-time biosensors to optimize therapeutic outcomes. Collaboration among chemists, biologists and clinicians will be essential to realize their full potential. Personalized medicine ; Biodistribution ; Drug delivery ; Targeted drug delivery ; Translational medicine ; Immune system ; Limiting ; Rational design Nanoparticle-Based Drug Delivery ; Advanced Drug Delivery Systems ; Diabetes Treatment and Management
Authors: Xia Li | Jihong Huang | Xuefeng Li | Jingjing Si | Weiwei He
Source: Nano Research (article, 2025-08-07)
Field: Materials Science — Materials Chemistry

DNA-mediated regulation of nanozymes activity and their applications in biosensing Nanozymes have emerged as highly promising alternatives to natural enzymes, featuring high stability, facile synthesis, tunability, and cost-effectiveness, making them key players in biocatalysis, environmental remediation and biomedical applications. However, the moderate catalytic activity and poor specificity of nanozymes hinder their broader applications. To address these limitations, researchers have focused on developing regulatory strategies that enhance the catalytic activity and specificity of nanozymes. Among them, DNA with programmability, recognition specificity, and abundant activate binding sites, greatly facilitates the development of smart nanozymes. Therefore, this review comprehensively summarizes DNA-mediated regulation strategies and recent researches progress on nanozymes in the field of biosensing. In addition, we discuss the current challenges and future perspectives regarding DNA-mediated regulation of nanozymes. Biosensor ; Nanotechnology ; DNA ; Chemistry ; Computational biology ; Biophysics ; Cell biology ; Materials science ; Biology ; Biochemistry Advanced Nanomaterials in Catalysis ; Advanced biosensing and bioanalysis techniques ; Biosensors and Analytical Detection
Authors: Burak Kuzu | Mustafa Çakır | Eda Açıkgöz | Mehmet Abdullah Alagöz
Source: ChemMedChem (article, 2025-07-28)
Field: Chemistry — Organic Chemistry

Unveiling Benzoxazole‐Substituted Thiazolyl‐Pyrazole Derivatives Inducing Apoptosis by Targeting β‐Tubulin and Caspase‐3 In the present study, the biological activities of novel compounds (BP-1 to BP-6), designed as antitubulin agents, were systematically evaluated, with a particular focus on their effects on the triple-negative breast cancer cell line MDA-MB-231 and non-cancerous cell line MCF-10A. BP-2 and BP-6 demonstrated micromolar-range antiproliferative activity against MDA-MB-231 cancer cells, with IC<sub>5</sub> <sub>0</sub> values of 8 and 4 µM, respectively, comparable to nocodazole (3 µM), and showed selective cytotoxicity over normal MCF-10A cells, with selectivity indices of approximately 3.3 and 8. In vitro analyses revealed that BP-2 and more notably BP-6 significantly inhibited cell proliferation in a time- and dose-dependent manner, disrupted microtubule organization through the downregulation of β-tubulin expression, and induced apoptosis, as evidenced by increased levels of Cleaved Caspase-3 and distinct apoptotic morphological changes. Among the tested compounds, BP-6 exhibited the most potent antiproliferative and proapoptotic activity, with an IC<sub>5</sub> <sub>0</sub> value close to that of NOC. Molecular docking supported these findings by showing strong binding affinities of BP-6 to both β-tubulin and Caspase-3, indicating a dual-targeted mechanism. Furthermore, molecular dynamics simulations confirmed the stable binding and dynamic integrity of BP-6 within both β-Tubulin and Caspase-3 targets, underscoring its potential as a robust candidate for anticancer drug development. Tubulin ; Apoptosis ; Nocodazole ; Cytotoxicity ; Chemistry ; Cell culture ; Docking (animal) ; Caspase 3 ; Caspase ; Downregulation and upregulation ; In vitro ; Cell growth ; Microtubule ; Biology ; Cancer research ; Programmed cell death ; Cell biology ; Biochemistry ; Cell ; Cytoskeleton ; Gene ; Genetics ; Medicine Synthesis and biological activity ; Cancer therapeutics and mechanisms ; Click Chemistry and Applications
Authors: Fengtao Yu | Mei Xu | Sha Yu | Bo Wang | Yan Liu | Jie Xu | Jian‐Ding Qiu
Source: Nano Research (article, 2025-06-10)
Field: Chemistry — Inorganic Chemistry

Isomer-tailored vinylene-based COFs for photo-enhanced uranium extraction from seawater: Mechanistic insights into carrier dynamics and structural superiority Addressing the challenges of uranium extraction from seawater (UES) requires innovative strategies to overcome ultralow concentration (3.3 ppb) and thermodynamic limits. Herein, we propose a regioisomeric engineering strategy to design vinylene-linked covalent organic frameworks (COFs) for synergistic adsorption-photocatalytic UES. Two isomeric COFs, β-PTTN-AO and α-PNNB-AO, were synthesized by tuning the substitution positions of amidoxime (AO) groups on olefin bonds. The β-PTTN-AO isomer achieves a remarkable UES capacity of 12.74 ± 0.21 mg·g⁻¹ in nature seawater, surpassing its α-positioned counterpart (8.9 ± 0.18 mg·g⁻¹) and outperforming most reported photocatalysts. Combined experiments and DFT theoretical studies correlate regioisomeric configurations with electronic structure modulation and photocatalytic activity. Specifically, β-PTTN-AO enhance π-electron delocalization and strengthen built-in electric fields, promoting exciton dissociation, charge separation and uranium reduction. This work establishes a molecular design paradigm for COF photocatalysts, advancing sustainable nuclear energy through structural isomerism. Seawater ; Uranium ; Extraction (chemistry) ; Materials science ; Molecular dynamics ; Nanotechnology ; Chemistry ; Chemical engineering ; Computational chemistry ; Organic chemistry ; Oceanography ; Metallurgy ; Geology Radioactive element chemistry and processing ; Covalent Organic Framework Applications ; Catalysis and Oxidation Reactions
Authors: Mouna Fhoula | Ikhlas Kchaou | Christian Hernández‐Álvarez | Mohamed Dammak | Sami Boufi | Inocencio R. Martín
Source: Materials Advances (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Highly photoluminescent carbon dots: a multifunctional platform for pH sensing, nano thermometry, and mercury( <scp>ii</scp> ) detection Carbon dots (CDs), a class of heavy-metal-free fluorescent nanomaterials, have attracted significant attention due to their excellent optical properties, chemical stability, low toxicity, and biocompatibility. Nanomaterials ; Biocompatibility ; Mercury (programming language) ; Nanotechnology ; Fluorescence ; Materials science ; Photoluminescence ; Carbon quantum dots ; Carbon fibers ; Nano- ; Metal ; Quantum dot ; Optoelectronics ; Metallurgy ; Composite number ; Composite material ; Computer science Carbon and Quantum Dots Applications ; Nanocluster Synthesis and Applications ; Advanced biosensing and bioanalysis techniques
Authors: Sungha Jeon | Hyeonyeob Seo | Yeji Kim | Young In Choi | Youngbin Lee | Youngmin Jung | Somin Lee | Jung Tae Lee | Seongjun Park
Source: Nature Communications (article, 2025-09-02)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Fully biocompatible, thermally drawn fiber supercapacitors for long-term bio-implantation Recent advancements in implantable bioelectronic devices have increased the demand for biocompatible energy sources with long-term electrochemical and mechanical stability. Here, we present a tough hydrogel-based supercapacitor (THBS) fiber, fabricated via a thermal drawing process (TDP), that enables the integration of all components-electrodes, electrolyte, current collectors, and encapsulation-into a single, unified, and mechanically robust fiber-shaped architecture. Through thermal/mechanical optimization and the incorporation of self-healing properties, THBS fibers exhibit durable, high electrochemical performance under dynamic, high-curvature deformations mimicking in vivo physiological motions. Despite a thickness of only a few hundred microns, they maintain mechanical and electrochemical stability. Long-term functionality was confirmed over five weeks with minimal immune response. In vivo implantation demonstrated successful LED operation in a freely moving mouse, and successful optogenetic stimulation of both central and peripheral nervous systems. These results underscore the promise of THBS fibers as next-generation, fully biocompatible energy storage devices for advanced implantable bioelectronic systems. Biocompatible material ; Supercapacitor ; Term (time) ; Fiber ; Materials science ; Nanotechnology ; Biomedical engineering ; Medicine ; Chemistry ; Composite material ; Capacitance ; Electrode ; Physics Supercapacitor Materials and Fabrication ; Electrospun Nanofibers in Biomedical Applications ; Advanced Sensor and Energy Harvesting Materials
Authors: Mikhail G. Andronov | Natalia Andronova | Michael Wand | Jürgen Schmidhuber | Djork-Arné Clevert
Source: Journal of Cheminformatics (article, 2025-03-10)
Field: Materials Science — Materials Chemistry

Accelerating the inference of string generation-based chemical reaction models for industrial applications Transformer-based, template-free SMILES-to-SMILES translation models for reaction prediction and single-step retrosynthesis are of interest to computer-aided synthesis planning systems, as they offer state-of-the-art accuracy. However, their slow inference speed limits their practical utility in such applications. To address this challenge, we propose speculative decoding with a simple chemically specific drafting strategy and apply it to the Molecular Transformer, an encoder-decoder transformer for conditional SMILES generation. Our approach achieves over 3X faster inference in reaction product prediction and single-step retrosynthesis with no loss in accuracy, increasing the potential of the transformer as the backbone of synthesis planning systems. To accelerate the simultaneous generation of multiple precursor SMILES for a given query SMILES in single-step retrosynthesis, we introduce Speculative Beam Search, a novel algorithm tackling the challenge of beam search acceleration with speculative decoding. Our methods aim to improve transformer-based models' scalability and industrial applicability in synthesis planning. Computer science ; Inference ; String (physics) ; Biochemical engineering ; Data science ; Artificial intelligence ; Engineering ; Mathematics Machine Learning in Materials Science ; Advanced Text Analysis Techniques ; Web Data Mining and Analysis
Authors: Jihoon Kim | Dong Won Kim | Jong Hui Choi | William A. Goddard | Jeung Ku Kang
Source: Proceedings of the National Academy of Sciences (article, 2025-07-07)
Field: Materials Science — Materials Chemistry

AI-driven design of multiprincipal element alloys for optimal water splitting Water splitting for hydrogen production is essential in advancing the hydrogen economy. Multiprincipal element alloys offer promising opportunities for optimizing this process, yet their vast compositional space and the presence of local minima pose significant challenges for experimental and AI-driven exploration. To overcome these challenges, an AI framework is developed by integrating Gaussian Process Regression with a configuration entropy-based acquisition function for screening and a design of experiments (DoE) for data-efficient overpotential mapping. Through Bayesian optimization across 16.2 million chemical compositions, this entropy-screened and DoE dataset-trained AI identifies Fe<sub>12</sub>Co<sub>28</sub>Ni<sub>33</sub>Mo<sub>17</sub>Pd<sub>5</sub>Pt<sub>5</sub> as the best composition for water splitting within its search space. The alloy exhibits ultralow overpotentials of 24 mV for hydrogen evolution and 204 mV for oxygen evolution at 10 mA·cm<sup>-2</sup> with robust stability, surpassing state-of-the-art non-noble and noble metal electrocatalysts including Pt/C+IrO<sub>2</sub>, Pt<sub>35</sub>Ru<sub>65</sub>, and Ru-VO<sub>2</sub>-demonstrating remarkable performance beyond reach by contemporary experimental and AI frameworks. Overpotential ; Water splitting ; Bayesian optimization ; Materials science ; Hydrogen ; Oxygen evolution ; Alloy ; Maxima and minima ; Computer science ; Nanotechnology ; Chemistry ; Metallurgy ; Artificial intelligence ; Mathematics ; Physical chemistry ; Electrochemistry ; Catalysis Machine Learning in Materials Science ; Electrocatalysts for Energy Conversion ; Catalytic Processes in Materials Science
Authors: Alexander Foutch | Kazuma Kobayashi | Ayodeji Alajo | Dinesh Kumar | Syed Bahauddin Alam
Source: Progress in Nuclear Energy (article, 2025-04-24)
Field: Materials Science — Materials Chemistry

AI-driven uncertainty quantification &amp; multi-physics approach to evaluate cladding materials in a microreactor The pursuit of enhanced nuclear safety has spurred the development of accident-tolerant cladding (ATC) materials for light water reactors (LWRs). This study investigates the potential of repurposing these ATCs in advanced reactor designs, aiming to expedite material development and reduce costs. The research employs a multi-physics approach, encompassing neutronics, heat transfer, thermodynamics, and structural mechanics, to evaluate four candidate materials (Haynes 230, Zircaloy-4, FeCrAl, and SiC–SiC) within the context of a high-temperature, sodium-cooled microreactor, exemplified by the Kilopower design. While neutronic simulations revealed negligible power profile variations among the materials, finite element analyses highlighted the superior thermal stability of SiC–SiC and the favorable stress resistance of Haynes 230. The high-temperature environment significantly impacted material performance, particularly for Zircaloy-4 and FeCrAl, while SiC–SiC’s inherent properties limited its ability to withstand stress loads. Additionally, AI-driven uncertainty quantification and sensitivity analysis were conducted to assess the influence of material property variations on maximum hoop stress. The findings underscore the need for further research into high-temperature material properties to facilitate broader applicability of existing materials to advanced reactors. Haynes 230 is identified as the most promising candidate based on the evaluated criteria. Microreactor ; Cladding (metalworking) ; Nuclear engineering ; Materials science ; Nuclear physics ; Computer science ; Physics ; Chemistry ; Composite material ; Catalysis Nuclear Materials and Properties ; Nuclear reactor physics and engineering ; Molten salt chemistry and electrochemical processes
Authors: Lakshika Sharma | Abhishek Dadhich | Irra Dhar | Rashmi Choudhary | Mamta Dhiman | Madan Mohan Sharma
Source: OpenNano (article, 2025-08-27)
Field: Materials Science — Materials Chemistry

Myco-nanotechnology at the crossroads: eco-friendly synthesis, agricultural applications, and AI-driven risk mitigation of fungal-derived nanoparticles • Introduces Myco-NPs as eco-friendly nanomaterials with potential for sustainable agriculture. • Emphasizes novel integration of AI-based tools for predictive nanotoxicity modeling. • Critically analyzes plant-specific and matrix-dependent toxicity thresholds of Myco-NPs. • Highlights the application of omics-driven approaches to decode plant–nanoparticle interactions. • Advocates eco-design and LCA frameworks to ensure safe and responsible use of Myco-NPs. Fungal-based nanotechnology is emerging as a promising and sustainable approach in agriculture, environmental cleanup, and biotechnology. Nanoparticles produced by fungi known as Myco-nanoparticles offer a greener method of synthesis, along with good stability and strong biological activity. However, their increasing use has raised concerns about possible environmental risks and long-term effects. This review highlights recent advances in the eco-friendly production of Myco-nanoparticles and their potential to support plant growth, improve nutrient uptake, and boost resistance to stress and disease. While small amounts of these particles may be helpful, higher doses can lead to harmful effects such as oxidative stress and damage to plant DNA. Compared to nanoparticles made by plants or bacteria, fungal-derived particles are often more stable and easier to produce, though they still pose similar safety concerns. This review uniquely connects fungal nanobiotechnology with AI-driven toxicity prediction and omics-based pathway mapping an integrated approach that lays the groundwork for precision myconanotechnology with reduced ecological impact. Nanotechnology ; Environmentally friendly ; Nanoparticle ; Agriculture ; Applications of nanotechnology ; Materials science ; Business ; Biology ; Ecology Nanoparticles: synthesis and applications ; Graphene and Nanomaterials Applications ; Nanotechnology research and applications
Authors: Thanapat Worakul | Mohammed Azzouzi | Matthew D. Wodrich | Clémence Corminboeuf
Source: ChemRxiv (preprint, 2025-11-10)
Field: Materials Science — Materials Chemistry

MolCraftDiffusion: 3D Molecular Generation Framework for Data-driven Molecular Applications Modular design ; Limiting ; Construct (python library) ; Generative grammar ; Software Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Crystallography and molecular interactions
Authors: Xiaomin Cen | Zhengyang Cai | Lingli Zhang | Jia Zhou | Zhongbiao Tan | Hao Shi
Source: Food Packaging and Shelf Life (article, 2025-08-31)
Field: Materials Science — Biomaterials

Modified collagen-based biofilms for postharvest preservation of fruits and vegetables Postharvest ; Biofilm ; Food science ; Horticulture ; Biology ; Biotechnology ; Chemistry ; Bacteria Nanocomposite Films for Food Packaging ; Collagen: Extraction and Characterization ; Postharvest Quality and Shelf Life Management
Authors: Victor Ugbetan Agbogo | Emmanuel Rotimi Sadiku | Lucey Mavhungu | Moipone Linda Teffo
Source: AIMS bioengineering (article, 2025-01-01)
Field: Materials Science — Biomaterials

Next-generation biodegradable polymers: toward a circular plastics economy Research into biodegradable polymers as sustainable alternatives to traditional petrochemical plastics has increased significantly in response to the growing environmental impact of plastic pollution. In this review, we offer a comprehensive, multidisciplinary overview of current advances in the creation, degradation processes, and green energy applications of biodegradable polymers. We examined how chemical structure, environmental factors, and microbiological activity influence polymer breakdown, alongside controlled degradation and lifecycle optimization. Consideration was given to incorporating biodegradable materials into next-generation energy devices such as transient batteries, triboelectric nanogenerators, and supercapacitors. A comparative analysis highlighted the material properties, performance trade-offs, and environmental impacts of key polymers like PLA, PCL, cellulose, and chitosan. Emerging trends were explored within regulatory support and circular economy frameworks, including smart polymers, nanocomposites, and AI-driven material design. In the review, we also emphasized key challenges and future research directions necessary for practical implementation, demonstrating the potential of biodegradable polymers to enable scalable, environmentally friendly solutions across energy and material sectors. Circular economy ; Biodegradable polymer ; Environmentally friendly ; Petrochemical ; Environmental degradation ; Multidisciplinary approach ; Life-cycle assessment ; Sustainability biodegradable polymer synthesis and properties
Authors: Caichao Ye | Tao Feng | Weishu Liu | Wenqing Zhang
Source: Accounts of Materials Research (article, 2025-07-03)
Field: Materials Science — Materials Chemistry

Functional Unit: A New Perspective on Materials Science Research Paradigms New materials have long marked the civilization level, serving as an impetus for technological progress and societal transformation. The classic structure-property correlations were key of materials science and engineering. However, the knowledge of materials faces significant challenges in adapting to exclusively data-driven approaches for new material discovery. This perspective introduces the concepts of functional units (FUs) to fill the gap in understanding of material structure-property correlations and knowledge inheritance as the "composition-microstructure" paradigm transitions to a data-driven AI paradigm transitions. Firstly, we provide a bird's-eye view of the research paradigm evolution from early "process-structure-properties-performance" to contemporary data-driven AI new trend. Next, we highlight recent advancements in the characterization of functional units across diverse material systems, emphasizing their critical role in multiscale material design. Finally, we discuss the integration of functional units into the new AI-driven paradigm of materials science, addressing both opportunities and challenges in computational materials innovation. Perspective (graphical) ; Unit (ring theory) ; Engineering ethics ; Computer science ; Psychology ; Mathematics education ; Engineering ; Artificial intelligence Machine Learning in Materials Science ; Thermal properties of materials ; Semiconductor materials and interfaces