jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Mohamed Slamani | Borhen Louhichi | Salah Amroune | Mohammad Jawaid
Source: Advanced Materials Technologies (article, 2026-01-29)
Field: Materials Science — Polymers and Plastics

Next‐Generation Composite Materials and Manufacturing: A Review of Smart, Sustainable, and Digital Advancements ABSTRACT This critical review examines recent advances in sustainable digital composite manufacturing, focusing on aligning high‐performance composites with circular economy principles. It systematically evaluates next‐generation natural fiber reinforcements, recycled polymers, and bio‐based resins, alongside digital tools such as Artificial Intelligence (AI)‐driven design optimization and blockchain‐enabled supply chain transparency. Findings show that advanced bio‐resins and fiber treatments can reduce environmental impact by 40–60%, while digital twins and AI improve production efficiency by up to 30%. The review critically assesses the scalability and real‐world limitations of these innovations, highlighting gaps between theoretical potential and industrial adoption. It emphasizes how integrating sustainable materials with digital technologies enhances lifecycle sustainability, while identifying persistent challenges in cost, standardization, and system integration. By bridging materials science, sustainability, and digitalization, this work provides a forward‐looking roadmap for next‐generation composites. Emerging areas include smart composites, autonomous manufacturing, and self‐healing materials, all essential for meeting performance and environmental benchmarks. The review also examines intelligent composite systems with embedded sensing, self‐healing, and adaptive capabilities, highlighting their role in next‐generation applications. The study concludes that coordinated efforts in research, policy, and industry collaboration are essential to fully realize the potential of sustainable digital composite manufacturing. Industry 4.0 ; Bridging (networking) ; Scalability ; Emerging technologies ; Supply chain ; Sustainability ; Work (physics) Natural Fiber Reinforced Composites ; Fiber-reinforced polymer composites ; Polymer composites and self-healing
Authors: M. Soner Bay | Gizem Tiris | Asena Ayse Genc | Nevin Erk | Reem H. Obaydo | Hayam M. Lotfy
Source: Green Analytical Chemistry (article, 2026-01-05)
Field: Chemistry — Spectroscopy

AI-assisted design and optimization of two smart green HPLC methods for simultaneous determination of some antiviral drugs • Two AI-assisted HPLC methods developed for DTG, 3TC, and ABA determination. • Methods validated per ICH Q2(R2) for accuracy, precision, and linearity. • Gradient and isocratic modes tailored for binary and ternary formulations. • Smart chemistry approach combines GAC, WAC, and AI-driven optimization. • Fast, eco-friendly methods suitable for routine pharmaceutical QC labs. Two novel high-performance liquid chromatography (HPLC) methods were developed and validated for the determination of dolutegravir (DTG), lamivudine (3TC), and abacavir (ABA) in pharmaceutical formulations. In this study, AI engines such as Copilot, ChatGPT 5.2, Gemini, and Perplexity were integrated into HPLC method development. The selected predicted conditions underwent experimental optimization, validation, and refinement. Their practical implementation significantly improved efficiency and accuracy in the analytical process. The first method, an isocratic HPLC, was designed for the simultaneous quantification of DTG and 3TC using an XBridge® C18 column and a mobile phase of acetonitrile:phosphate buffer (pH 3.5, 50:50 v/v ). Detection was performed at 258.0 nm for DTG and 275.0 nm for 3TC. The second method, a gradient HPLC, enabled the simultaneous quantification of DTG, 3TC, and ABA on a Spherisorb® ODS2 C18 column with methanol and TEA/TFA buffer (pH 3.15) as the mobile phase. Detection wavelengths were 258.0, 278.0, and 294.0 nm for DTG, 3TC, and ABA, respectively. The calibration ranges were wide and showed excellent linearity. Both techniques were validated in accordance with ICH Q2(R2) guidelines. The approaches align with smart analytical chemistry principles, combining green and white analytical chemistry (GAC and WAC) with AI-driven method development, resulting in accurate, fast, and sustainable techniques suitable for routine quality control applications. High-performance liquid chromatography ; Ternary operation ; Bioanalysis ; Pharmaceutical formulation ; Calibration curve ; Calibration ; Detection limit ; Accuracy and precision Analytical Chemistry and Chromatography ; Analytical Methods in Pharmaceuticals ; Pesticide Residue Analysis and Safety
Authors: Madeleine A. Gaidimas | Jiaru Bai | Yeonghun Kang | Kent O. Kirlikovali | Varinia Bernales | Alán Aspuru-Guzik | Omar K. Farha
Source: Chem (article, 2026-02-25)
Field: Chemistry — Inorganic Chemistry

Reimagining metal-organic framework discovery: Integrating experiment, computation, and artificial intelligence Workflow ; Perspective (graphical) ; Applications of artificial intelligence ; Space (punctuation) Metal-Organic Frameworks: Synthesis and Applications ; Machine Learning in Materials Science ; Supramolecular Chemistry and Complexes
Authors: Vinodhini S.P | Jasmine Christina X | Anitha G | Joseph Raj Xavier
Source: Journal of Power Sources (article, 2026-01-28)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Polypyrrole nanocomposites for next-generation supercapacitors: A comprehensive review of design strategies, challenges, and future directions Supercapacitor ; Polypyrrole ; Nanocomposite ; Energy storage ; Electrochemical energy storage ; Conductive polymer ; Electrochemistry Supercapacitor Materials and Fabrication ; Conducting polymers and applications ; Advancements in Battery Materials
Authors: Xuxuan Pan | Zhuo Wang | Wenhao Zhou | F. Liu | Jun Chen
Source: Energies (article, 2026-01-20)
Field: Materials Science — Materials Chemistry

Research Progress on Polymer Materials in High-Voltage Applications: A Review High-voltage equipment imposes increasingly stringent demands on polymeric insulating materials, particularly in terms of dielectric strength, space charge suppression, thermo-electrical stability, and interfacial reliability. Conventional polymers are prone to critical failure modes under high electric fields, including electrical treeing, partial discharge, interfacial degradation, and thermo-oxidative aging. This review systematically summarizes recent advances in polymer modification strategies specifically designed for high-voltage applications, covering nanofiller reinforcement, plasma surface engineering, and the development of self-healing insulating polymers. Multi-scale structural control and interface engineering, aligned with the specific requirements of high-voltage environments, have emerged as pivotal approaches to enhance insulation performance. Moreover, the integration of artificial intelligence-driven materials design, digital characterization, and application-oriented modeling holds significant promise for accelerating the development of next-generation high-voltage polymeric systems, thereby offering robust materials solutions for the reliable long-term operation of high-voltage equipment. Polymer ; Dielectric ; Surface modification ; Interface (matter) ; Space charge High voltage insulation and dielectric phenomena ; Dielectric materials and actuators ; Polymer Science and PVC
Authors: S. Wang | Yutong Dai | Jing Zhang | Yiling Tong | Jingru Yang | Songyao Liu | Zheng Dai | XiangJu XIAO FengShou MENG
Source: Chemical Research in Chinese Universities (article, 2026-01-05)
Field: Chemistry — Inorganic Chemistry

Construction of Functional Metal-Organic Frameworks and Their Applications in the Biomedical Field Scope (computer science) ; Biosafety ; Scalability ; Field (mathematics) ; Scientific field ; Subject (documents) ; Metal-organic framework Metal-Organic Frameworks: Synthesis and Applications ; Advanced Nanomaterials in Catalysis ; Nanocluster Synthesis and Applications
Authors: Zuhong Lin | Daoyuan Ren | K. Ran | Jing Sun | Songlin Yu | Xuefeng Bai | X. D. Huang | Haiyang He | Peng‐Zhi Pan | Ying Fang | Zhanglin Li | Haipu Li | Jingjing Yao
Source: Transactions of Materials Research (article, 2026-01-01)
Field: Chemistry — Inorganic Chemistry

Reshaping MOFs synthesis conditions mining with a dynamic multi-agents framework of large language model Accurately identifying the synthesis conditions of metal-organic frameworks (MOFs) is essential for guiding experimental design, yet remains challenging because relevant information in the literature is often scattered, inconsistent, and difficult to interpret. We present MOFh6, a large-language-model-driven system that reads raw articles or crystal codes and converts them into standardized synthesis tables. It links related descriptions across paragraphs, unifies ligand abbreviations with full names, and outputs structured parameters ready for use. MOFh6 achieved 99% extraction accuracy, resolved 90.8% of abbreviation cases across five major publishers, and maintained a precision of 0.93 ± 0.01. Processing a full text takes 9.6s, locating synthesis descriptions 36 s, with 100 papers processed for 4.24$. By replacing static database lookups with real-time extraction, MOFh6 reshapes MOFs synthesis research, accelerating the conversion of literature knowledge into practical synthesis protocols, enabling scalable, data-driven materials discovery. • LLM-powered MOFh6 unifies fragmented synthesis knowledge into structured data. • Transforms MOF synthesis informatics with scalable and cost-efficient workflow. • End-to-end system supports literature mining, structure query, and MOFs visualization. • 7 × faster processing, 76% lower cost, advancing MOF synthesis information discover. Scalability ; Information extraction ; Informatics ; Raw data ; Program synthesis ; Software Metal-Organic Frameworks: Synthesis and Applications ; Machine Learning in Materials Science ; Inorganic Chemistry and Materials
Authors: Lei Ding | Huichao Jin | Chao Chen | Mohamed S. Selim | Shimaa A. Higazy | Wei Tian | Limei Tian | Luquan Ren
Source: Progress in Materials Science (article, 2026-01-23)
Field: Materials Science — Surfaces, Coatings and Films

Amphiphilic surfaces: design, preparation, and applications Amphiphile ; Wetting ; Homogeneous ; Fabrication ; Domain (mathematical analysis) ; Surface (topology) ; Surface energy ; Surface engineering Surface Modification and Superhydrophobicity ; Polymer Surface Interaction Studies ; Hydrogels: synthesis, properties, applications
Authors: Jiaqi Song | Yue Xu | Yang Yang | Guang Zhang | Xinyu Xu | Jiawang Wang | Chunmin Ma | Na Zhang
Source: Coordination Chemistry Reviews (article, 2026-01-13)
Field: Materials Science — Materials Chemistry

From monomodal to multimodal: The intelligent evolution of photoelectric nanozymes in food safety detection sensing Food safety ; Blueprint ; Reliability (semiconductor) ; Key (lock) ; Field (mathematics) Advanced Nanomaterials in Catalysis ; Nanocluster Synthesis and Applications ; Biosensors and Analytical Detection
Authors: Yuying Song | Jie Zhou | Sanwei Hao | Changyou Shao | Wenting Yu | Yaru Yu | Fangqing Wang | Zhiyu Li | Peng Fu | Jun Yang | Hailin Cong | Chaoji Chen
Source: Progress in Materials Science (article, 2026-03-10)
Field: Materials Science — Biomaterials

Next-gen cellulose therapeutics: fusing in vivo/in vitro data for precision healthcare Wearable computer ; Personalized medicine ; Personalization ; Precision medicine ; Health care ; Participatory sensing ; Biomedicine ; Wearable technology Advanced Cellulose Research Studies ; Advanced Sensor and Energy Harvesting Materials ; Biosensors and Analytical Detection
Authors: Jian Qiu | Zejian Li | Jiabin Ma | Jun Lu | Chenlu He
Source: Small (article, 2026-01-14)
Field: Chemistry — Organic Chemistry

Integrated Photon Ellipticity Recognition with Chiral Nanomaterials Light's spin angular momentum endows photons with rich polarization degrees of freedom, an extra "knob" of control beyond intensity and wavelength that underpins breakthroughs in imaging, sensing, data storage, and quantum information. Yet reliably measuring the photon polarization information remains challenging. Conventional detectors rely on bulky optical assemblies with multiple polarizers, wave plates, and filters. By contrast, photodetectors built around intrinsically chiral active layers can directly transduce linear, elliptical, and circular polarization states into electrical signals, offering compact, monolithic advantages, while in combination with the potential of flexible and wearable electronics. This review analyzes recent advances in photon ellipticity identification, focusing on circularly polarized light (CPL) photodetectors using chiral materials, including organic semiconductors, halide perovskites, and symmetry-breaking metamaterials. We first outline fundamental operating principles and key performance metrics, then compare material-specific advantages and limitations for CPL detection applications. Looking forward, we highlight transformative opportunities where chiral optoelectronics converges with artificial intelligence (AI), enabling accelerated material discovery, neuromorphic polarization processing architectures, and self-adaptive flexible detection systems. This review outlines a roadmap for advancing high-performance CPL photodetectors integrating sensitivity, robustness, and intelligence for next-generation quantum and secure communications. Photodetector ; Neuromorphic engineering ; Photon ; Circular polarization ; Polarization (electrochemistry) ; Quantum information science ; Photon polarization ; Nanomaterials ; Quantum dot Synthesis and Properties of Aromatic Compounds ; Metamaterials and Metasurfaces Applications ; Organic Electronics and Photovoltaics
Authors: Yong Liu | Wenwen Chi | Yu-Ou He | Wang‐Kang Han | Zhi-Guo Gu
Source: Coordination Chemistry Reviews (article, 2026-02-13)
Field: Materials Science — Materials Chemistry

Bipyridine-based covalent organic frameworks: structural regulation and photocatalytic applications Rational design ; Photocatalysis ; Covalent bond ; Design elements and principles ; Charge (physics) ; Semiconductor Covalent Organic Framework Applications ; Advanced Photocatalysis Techniques ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Al-Hassan Soliman Wadan | M H Ali | Doha El-Sayed Ellakwa
Source: Journal of Nanobiotechnology (article, 2026-02-06)
Field: Materials Science — Materials Chemistry

Sustainable nanomaterials for precision dental medicine: green synthesis, therapeutic applications, and future directions Sustainable nanomaterials are emerging as transformative platforms for precision dental medicine, uniquely combining environmental responsibility with individualized therapeutic performance. Green-synthesized metallic, polymeric, carbon-based, and bioactive nanomaterials exhibit superior biocompatibility, biodegradability, and a reduced ecological burden compared to conventionally produced analogues, while enabling enhanced antimicrobial, regenerative, and diagnostic capabilities. This review synthesizes recent advances in eco-friendly nanoparticle synthesis, life-cycle sustainability metrics, and the integration of nanotechnology into patient-specific diagnostics, controlled-release therapeutics, and regenerative dentistry. Emphasis is placed on biogenic routes for silver, gold, ZnO, chitosan, bioactive glass, cellulose nanocrystals, and lignin nanocarriers, as well as their clinical potential in caries management, periodontal regeneration, endodontic disinfection, implant surface engineering, and point-of-care diagnostics. Additionally, their compatibility with multi-omics-driven precision dentistry is highlighted. We further analyze safety profiles, biodegradation pathways, regulatory frameworks, and translational challenges related to standardization and AI-assisted personalization. Sustainable nano-platforms represent a strategic route to advance dental care toward predictive, preventive, and personalized practice while ensuring environmental stewardship and global healthcare equity. Transformative learning ; Sustainability ; Nanomedicine ; Stewardship (theology) ; Precision medicine ; Health care ; Standardization ; Dental care ; Dental implant Nanoparticles: synthesis and applications ; Advanced Nanomaterials in Catalysis ; Graphene and Nanomaterials Applications
Authors: Dhruv Ahlawat | Vaibhav Mishra | Sourabh Singh | Mohd Zaki | Vaibhav Bihani | Hargun Singh Grover | Biswajit Mishra | Santiago Miret | Mausam | N. M. Anoop Krishnan
Source: Nature Machine Intelligence (article, 2026-02-27)
Field: Materials Science — Materials Chemistry

A family of large language models for materials research with insights into model adaptability in continued pretraining Adaptation (eye) ; Adaptability ; Domain adaptation ; Language model ; Domain (mathematical analysis) ; Software deployment Machine Learning in Materials Science ; Block Copolymer Self-Assembly ; Composite Material Mechanics
Authors: Yiming Ma | Xuming Yuan | Ashish Yewale | Brahim Benyahia
Source: Particuology (article, 2026-01-23)
Field: Materials Science — Materials Chemistry

Recent advances in the digital transformation of crystallization process development and operation: Synergy between model- and AI-driven strategies Process (computing) ; Workflow ; Process modeling ; Process control ; Work in process ; New product development Crystallization and Solubility Studies ; Process Optimization and Integration ; Fluid Dynamics and Mixing
Authors: Iván Cortés | Cristina Cuadrado | J. G. GAVIN | Marı́a M. Zanardi | Antonio Hernández Daranas | Ariel M. Sarotti
Source: Journal of Chemical Information and Modeling (article, 2026-01-20)
Field: Chemistry — Spectroscopy

Solvent Matters: Bridging Theory and Experiment in Quantum-Mechanical NMR Structural Elucidation Quantum-mechanical NMR (QM-NMR) is widely used in structure elucidation. A long-sought holey grail in this field is solving structures from a simple <sup>1</sup>H NMR spectrum with AI-driven workflows. Yet, solvent effects on chemical shifts, though long recognized, remain overlooked. We show in a theory-experiment study that implicit solvation models miss solvent-induced variations and introduce a Python tool to quantify solvent sensitivity, aiding more reliable QM-NMR structural assignments. Solvation ; Bridging (networking) ; Solvent ; Python (programming language) ; Solvent effects ; Nuclear magnetic resonance spectroscopy ; Holy Grail ; Molecule Molecular spectroscopy and chirality ; Advanced NMR Techniques and Applications ; NMR spectroscopy and applications
Authors: Mahesh Kumar | Manini Bhatt | Bodhisatwa Das
Source: RSC Advances (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

Carbon nanodots as theranostics agents in cancer: advances in design, targeting, and real-time monitoring Carbon nanodots (CNDs) have emerged as a promising class of carbon-based nanomaterials for cancer theranostics, uniquely integrating diagnosis and therapy on a single platform. Their ultrasmall size, high aqueous dispersibility, tunable photoluminescence extending into the near-infrared (NIR) window, and compatibility with green, scalable synthesis enable deep-tissue imaging and targeted intervention with reduced systemic toxicity compared with many conventional nanomaterials. This review summarises recent advances in the top-down and bottom-up fabrication of CNDs, including heteroatom doping and surface functionalisation with ligands or stimuli-responsive linkers, and relates these design parameters to optical performance, tumour selectivity, and responsiveness to the tumour microenvironment. Particular emphasis is placed on CND-based platforms for multimodal imaging (fluorescence, MRI, and photoacoustic), controlled-release drug delivery, gene silencing, and light-activated photodynamic and photothermal therapies, as well as emerging synergistic systems that combine these functions for real-time, image-guided treatment. Remaining challenges, such as batch-to-batch variability, incomplete understanding of long-term biosafety (especially for metal-doped CNDs), and limited clinical-scale manufacturing and regulatory readiness, are critically discussed alongside future opportunities, including NIR-II optimisation, protein-corona-resistant surface engineering, and AI-assisted CND design for personalised cancer theranostics. Photothermal therapy ; Cancer therapy ; Nanomaterials ; Photodynamic therapy ; Nanodot ; Cancer imaging ; Optical imaging ; Photoluminescence Carbon and Quantum Dots Applications ; Graphene and Nanomaterials Applications ; Advanced Nanomaterials in Catalysis
Authors: Huifang Liu | Yan Han | Hongjun Zeng | Tao Hu | Shenglin Ma
Source: Autex Research Journal (article, 2026-01-01)
Field: Materials Science — Polymers and Plastics

Tangled knowledge: mapping research hotspots and emerging frontiers in textile technology through bibliometric analysis Abstract The progress of textile technology continually drives the development of the textile product market, making the clarification of its research trajectory a key priority in the field. This paper aims to map the research status, core themes, and future trends of textile technology during 2005–2025, and specifically to elucidate the profound reasons for the field’s recent research growth entering a plateau after a period of high output. The study adopts the bibliometric method, using 1,365 papers retrieved from the Web of Science database as a sample, and employs CiteSpace for a systematic analysis of keywords, authors, institutions, and disciplines. The results show that the field has formed a well-established research cluster centered on materials science and engineering, with representative institutions including Lodz University of Technology and Donghua University. Research topics are highly concentrated on nanotechnology and surface modification, dedicated to enhancing fabric functionality, such as strengthening mechanical properties and increasing antibacterial capacity. At the same time, emerging themes such as smart textiles and silver nanoparticles have concentratedly emerged since 2023, reflecting a transformation demand towards intelligence and functionalization. Crucially, evidence at the institutional and disciplinary levels indicates that cooperation and knowledge integration between cutting-edge knowledge streams such as artificial intelligence, biology, and ecology and the aforementioned mainstream materials science cluster are significantly insufficient. The structural divide between the mainstream and the cutting-edge is the fundamental reason for the field’s stagnation following a period of rapid growth. Future research emphasis should shift from incremental optimization within material science to breaking disciplinary boundaries and fostering deep interdisciplinary integration. Mainstream ; Textile ; Discipline ; Field (mathematics) ; Big data ; Web of science ; Bibliometrics Textile materials and evaluations ; Dyeing and Modifying Textile Fibers ; Silk-based biomaterials and applications