jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Felipe Garcı́a | Mamoru Senna | V. Šepelák
Source: RSC Mechanochemistry (article, 2025-01-01)
Field: Chemistry — Physical and Theoretical Chemistry

Moving mechanochemistry forward: reimagining inorganic chemistry through mechanochemistry Felipe Garcia, Mamoru Senna and Vladimir Šepelák outline the opportunities of mechanochemistry for inorganic synthesis. Mechanochemistry ; Garcia ; Chemistry ; Nanotechnology ; Materials science ; Philosophy ; Humanities Crystallography and molecular interactions ; Building materials and conservation ; X-ray Diffraction in Crystallography
Authors: M. M. Bhandari | Seema Raj | Md Sabir Alam
Source: Bioimpacts (article, 2025-08-25)
Field: Materials Science — Biomaterials

Recent innovations in nanomedicine and nano-based techniques for the treatment of breast cancer Breast cancer (BC) is a persistent global health challenge, necessitating innovative therapeutic strategies. Recently, nanotechnology has appeared as a transformative methodology to treat BC, suggesting precise targeting, controlled drug delivery, and improved imaging capabilities. This review offers a current overview of the latest innovations around nanotechnology for BC therapy in the field of new nanomedicines and nano-based drug delivery methods by carefully examining the utilization of nanoparticles to enhance the effectiveness of both new and old medications and to enable targeted evaluation using disease markers. Key topics include early detection, targeted drug delivery, multimodal imaging, and combination therapies. The paper underscores the probability of using nanotechnology to reshape BC management landscape and outlines potential future directions. Nanomedicine ; Breast cancer ; Transformative learning ; Drug delivery ; Targeted drug delivery ; Cancer ; Cancer therapy Nanoparticle-Based Drug Delivery
Authors: Nikolaos Xenidis | Mehrdad Rezaei Golghand | Nikita I. Raginov | Joachim Oberhammer | Dmitry V. Krasnikov | Albert G. Nasibulin | V. E. Lyubchenko
Source: Nature Communications (article, 2025-12-02)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Ultrathin Single-Walled Carbon Nanotube Surface Wave Absorbers for Terahertz Dielectric Waveguides Dielectric waveguides are an emerging platform for terahertz (THz) integrated circuits, but a key challenge for dense integration is the realization of terminations that enable both multi-port device characterization and elimination of electromagnetic interference. Here, we demonstrate a compact, broadband termination by coating silicon waveguides with ultrathin single-walled carbon nanotube (SWCNT) films. Fabricated via a floating-catalyst (aerosol) chemical vapor deposition process, film thicknesses vary from 2 to 53 nm and are characterized in 140-220 GHz. A 53 nm thick film introduces up to 47 dB of attenuation while maintaining over 20 dB reflection loss, confirming nearly reflection-free absorption. Shielding analysis shows absorption dominates over reflection, and a record specific shielding efficiency of 5.5 × 10<sup>9</sup> dB cm<sup>2</sup> g<sup>-1</sup> is achieved. This approach offers a footprint-efficient solution for high-density THz circuits without bulky, radiative terminations. Terahertz radiation ; Chemical vapor deposition ; Carbon nanotube ; Electromagnetic shielding ; Dielectric ; Absorption (acoustics) ; Attenuation ; Reflection (computer programming) ; Electromagnetic radiation Electromagnetic wave absorption materials ; Terahertz technology and applications ; Metamaterials and Metasurfaces Applications
Authors: Hyunseok Shim | Heena Kim | Seonmin Jang | Nam‐In Kim | Taeheon Kim | Donghyeon Seo | Hae Jin Kim
Source: Nano Research (article, 2025-07-11)
Field: Materials Science — Polymers and Plastics

Intrinsically stretchable organic electrochemical synaptic transistors for versatile response modulations The development of intrinsically stretchable organic electrochemical synaptic transistors (ISOESTs) based entirely on elastomeric materials is pivotal for advancing applications requiring neuromorphic functionality under significant mechanical deformation. This study presents ISOESTs capable of replicating a comprehensive range of synaptic behaviors, including excitatory postsynaptic currents (EPSCs), paired-pulse facilitation (PPF), and transitions from short-term memory (STM) to long-term memory (LTM). Remarkably, these synaptic characteristics were preserved even when the devices were subjected to 30% uniaxial strain, demonstrating exceptional mechanical robustness and functional stability. A pixelated 5 × 5 array of ISOESTs exhibited minimal device-to-device variation, underscoring the scalability and uniformity of the fabrication approach. To further illustrate their potential, a neurologically integrated electronic skin (e-skin) was fabricated, incorporating these ISOESTs to enable modulation of synaptic responses. The modulation of synaptic responses was strongly correlated with electrochemical analyses, establishing a robust operational framework for programmable neuromorphic systems. Comprehensive investigations into device fabrication, operation mechanisms, and integration strategies provide critical insights into the potential of these systems for next-generation applications in wearable electronics, soft robotics, neuro-prosthetics, and human–machine interfaces. This work represents a significant step toward realizing adaptive, biologically inspired electronic platforms capable of bridging the gap between engineered systems and living tissues. Materials science ; Nanotechnology ; Electrochemistry ; Transistor ; Optoelectronics ; Chemistry ; Electrode ; Electrical engineering ; Voltage ; Engineering Conducting polymers and applications ; Advanced Memory and Neural Computing ; Neuroscience and Neural Engineering
Authors: Yuvraj Patil
Source: Chemistry - A European Journal (review, 2025-11-07)
Field: Materials Science — Materials Chemistry

Emerging BODIPY‐Based NonFullerene Acceptors: Innovations for Organic Solar Cells Recent rapid progress in nonfullerene acceptors (NFAs) has transformed the landscape of organic solar cells (OSCs), resulting in a substantial improvement in power conversion efficiency (PCE). BODIPY (boron-dipyrromethene) derivatives as NFAs have emerged as an important category of materials owing to their strong visible to near-infrared (NIR) absorption, tunable frontier energy levels, and adjustable molecular architectures. This review highlights recent developments in BODIPY derivatives, used as NFAs, emphasizing their molecular design, optoelectronic features, and applications as NFAs in OSCs. Through strategic selection of donor and acceptor moieties, extended π-conjugation, and tunable optical and electrochemical properties, these NFAs achieve enhanced charge transport and broader visible absorption profiles. Despite challenges like aggregation and suboptimal film morphology, these NFAs have demonstrated a promising PCE of 13.94% in binary blends. This first comprehensive review on BODIPY-based NFAs thoroughly highlights their design, photonic and electronic properties, and solar cell performance. By addressing current limitations and outlining future opportunities, this work provides critical insights into the development of BODIPY dyes as NFAs for efficient next-generation OSC applications. Organic solar cell ; BODIPY ; Solar cell ; Photovoltaic system ; Energy conversion efficiency ; Acceptor ; Photonics Luminescence and Fluorescent Materials ; Organic Electronics and Photovoltaics ; Synthesis and Properties of Aromatic Compounds
Authors: Felix Thelen | Florian Lourens | Alfred Ludwig
Source: Advanced Intelligent Discovery (preprint, 2025-06-18)
Field: Materials Science — Materials Chemistry

Accelerating Surface Composition Characterization of Thin‐Film Materials Libraries Using Multi‐Output Gaussian Process Regression Efficient characterization of surface compositions across high‐dimensional materials spaces is critical for accelerating the discovery of surface‐dominated functional materials. While X‐ray photoelectron spectroscopy allows detailed surface composition investigation, it remains a time‐intensive technique. In this work, it is demonstrated that Gaussian process regression can be used to accurately predict surface compositions from rapidly acquired volume composition data obtained by energy‐dispersive X‐ray spectroscopy, drastically reducing the number of required surface measurements. As a proof of principle, an exemplary system, the oxide Mg‐Mn‐Al‐O, is synthesized as a composition‐spread thin‐film materials library and analyzed by high‐throughput methods. We show that the surface composition of the entire library can be predicted with an accuracy of 96% with only 13 measurements, reducing the total measurement time by 277 h. This is a scalable and data‐efficient solution for integrating surface analysis into materials discovery workflows. Characterization (materials science) ; X-ray photoelectron spectroscopy ; Surface (topology) ; Materials science ; Workflow ; Thin film ; Surface energy ; Process (computing) ; Composition (language) ; Gaussian process ; Spectroscopy ; Computer science ; Gaussian ; Nanotechnology ; Chemical engineering ; Chemistry ; Physics ; Mathematics ; Database ; Composite material ; Engineering Machine Learning in Materials Science ; Electron and X-Ray Spectroscopy Techniques ; Electronic and Structural Properties of Oxides
Authors: Takao Fujita
Source: Asian Journal of Advanced Research and Reports (article, 2025-05-23)
Field: Materials Science — Materials Chemistry

Unifying Grain Boundary Networks and Crystal Graphs: A HyperGraph and SuperHyperGraph Perspective in Material Sciences Graph theory provides a foundation for modeling relationships among discrete elements via vertices and edges (Diestel, 2000, 2005). HyperGraphs extend this framework by allowing edges—hyperedges—to join more than two vertices, while superhypergraphs introduce nested powerset layers to capture hierarchical and selfreferential connections. Network analogues—hypernetworks and superhypernetworks—apply these ideas to empirical data structures. In materials science, graph-based models such as Grain Boundary Networks represent grains as vertices and their interfaces as edges (Schuh et al., 2003; Rohrer, 2011; Frary and Schuh, 2005), whereas Crystal Graphs encode atoms and bonds within lattice structures (Xie and Grossman, 2018; Park and Wolverton, 2020; Schmidt et al., 2021). These representations, however, lack the capacity to describe multi-scale and hierarchical features inherent in complex microstructures. This paper investigates the theoretical foundations of hypergraphs and superhypergraphs in materials science, which generalize classical graphs by enabling hyperedges, superedges, or supervertices to simultaneously connect multiple vertices. It further examines the relevance of graph-theoretical approaches in material sciences by introducing and formalizing the concepts of Grain Boundary HyperNetworks, Grain Boundary SuperHyperNetworks, and Crystal SuperHyperGraphs. For each structure, we provide precise mathematical definitions, construct detailed examples based on polycrystalline and crystalline material systems, and analyze fundamental properties such as multi-level connectivity, nesting depth, and combinatorial complexity. By integrating hyperstructure theory with the modeling of material architectures, this work establishes a robust framework for multi-scale and hierarchical analysis in materials science. Perspective (graphical) ; Hypergraph ; Grain boundary ; Mathematics ; Sociology ; Materials science ; Combinatorics ; Geometry ; Composite material Machine Learning in Materials Science ; Fiber-reinforced polymer composites ; Graphene research and applications
Authors: Essam Alkhnaifes | Erik Svensson Grape | A. Ken Inge | Felix Steinke | Tobias A. Engesser | Norbert Stock
Source: Inorganic Chemistry (article, 2025-04-07)
Field: Chemistry — Inorganic Chemistry

CAU-52: An Iron Metal–Organic Framework Containing Furandicarboxylate Linker Molecules The V-shaped linker molecule 2,5-furandicarboxylic acid (H<sub>2</sub>FDC), which can be derived from lignocellulosic biomass, was used in a systematic screening with various iron salts and led to the discovery of a new iron-based metal-organic framework (Fe-MOF) with the composition [Fe<sub>3</sub>(μ<sub>3</sub>-O)(FDC)<sub>3</sub>(OH)(H<sub>2</sub>O)<sub>2</sub>]·5H<sub>2</sub>O·H<sub>2</sub>FDC, designated as CAU-52 (CAU = Christian-Albrechts-Universität zu Kiel). The crystal structure of CAU-52 was determined using 3D electron diffraction (3D ED) and further refined by Rietveld refinement against powder X-ray diffraction (PXRD) data. CAU-52 contains the well-known trinuclear [Fe<sub>3</sub>(μ<sub>3</sub>-O)]<sup>7+</sup> cluster as the inorganic building unit (IBU) that is six-connected by FDC<sup>2-</sup> ions to form the <b>pcu</b> net. The connectivity leads to two types of cubic cages, similar to the ones observed in soc-MOFs. Comprehensive characterization of the title compound, including N<sub>2</sub> and water vapor sorption measurements, confirmed its chemical composition. CAU-52 exhibits microporosity toward nitrogen with a type-I isotherm (77 K), yielding a specific surface area of <i>a</i><sub>s,BET</sub> = 1077 m<sup>2</sup>/g. The H<sub>2</sub>O sorption measurement at 298 K leads to an isotherm that exhibits three steps. The water sorption capacity was determined to be 390 mg/g, and it decreases slightly in subsequent sorption cycles. The MOF is stable up to 250 °C in air and chemically resistant in various solvents. Chemistry ; Linker ; Molecule ; Organic molecules ; Metal ; Combinatorial chemistry ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Magnetism in coordination complexes ; Metal complexes synthesis and properties
Authors: Muhammad Ali Butt | Daniel Pastor Abellán | Ryszard Piramidowicz
Source: Laser & Photonics Review (article, 2025-11-12)
Field: Materials Science — Materials Chemistry

Mid‐Infrared Integrated Photonics: Material Platforms and Emerging Applications ABSTRACT Mid‐infrared (MIR) integrated photonics plays a pivotal role in a range of scientific and technological applications due to the unique absorption features of many molecules within this spectral range (2–20 µm). These wavelengths are particularly useful for sensitive chemical and biological sensing, as well as in environmental surveillance, medical diagnostics, and industrial process control. Advances in material platforms such as chalcogenide glasses, silicon, germanium, and graphene have significantly enhanced the performance and miniaturization of MIR integrated photonic devices. In this review, we provide a comprehensive analysis of various material platforms utilized in MIR integrated photonics. Additionally, the review explores the broad range of potential applications of MIR integrated photonics, including but not limited to environmental sensing, molecular spectroscopy, free‐space communication, and thermal imaging. The capabilities of MIR integrated photonic devices for precise chemical detection, enhanced biomedical diagnostics, and industrial process supervising are highlighted, emphasizing the transformative impact of these technologies on fields such as environmental science, healthcare, and telecommunications. Photonics ; Process (computing) ; Nanomanufacturing ; Miniaturization ; Emerging technologies Phase-change materials and chalcogenides ; Spectroscopy and Laser Applications ; Photonic Crystal and Fiber Optics
Authors: Noura El‐Ahmady El‐Naggar | Shaimaa Elyamny | Ahmad G. Shitifa | Asmaa Atallah El-Sawah
Source: Scientific Reports (article, 2025-12-13)
Field: Materials Science — Biomaterials

Biofabrication, statistical optimization, and characterization of collagen nanoparticles synthesized via Streptomyces cell-free system for cancer therapy Collagen nanoparticles (CollNPs) exhibit low antigenicity, high surface area, non-toxicity, and excellent biocompatibility, making them promising for diverse biomedical applications. This study reports, for the first time, an eco-friendly, sustainable microbial-mediated biosynthesis of CollNPs using the cell-free system of Streptomyces viridochromogenes. UV-Vis spectroscopy showed a distinct absorption peak at 240 nm. A synergistic modeling approach combining Central Composite Rotatable Design (CCRD) and Artificial Neural Networks (ANN) were used to optimize biosynthesis parameters. The ANN identified the predicted optimal conditions at pH 7, collagen concentration 20 mg/mL, incubation time 115 h, and temperature 32 °C, with a theoretical maximum yield of 19.87 mg/mL. Experimental validation confirmed the model's accuracy, yielding 19.1 mg/mL Sv-CollNPs, closely matched the theoretical prediction ANN exhibited higher predictive accuracy than CCRD, confirming its robustness for process optimization. TEM revealed hollow, spherical Sv-CollNPs with an average diameter of 30.41 nm. FTIR analysis identified NH, CH, C = O, and OH functional groups contributing to nanoparticles formation and stabilization. The ζ-potential was - 19.4 mV, indicating good colloidal stability. The Sv-CollNPs displayed strong antioxidant and anti-hemolytic activities, alongside notable anticancer activity . The IC<sub>50</sub> values were 7.94 ± 0.6 µg/mL (MCF-7), 13.89 ± 1.0 µg/mL (HepG2), and 22.06 ± 1.6 µg/mL (HCT116). In vivo experiments were conducted on six groups (n = 8 per group). Treatment with native collagen, Sv-CollNPs, and DOX reduced EAC tumor growth by 65.66%, 83.84%, and 85.86%, respectively. The combined treatment of Sv-CollNPs and DOX achieved the highest tumor inhibition (97.98%), exceeding the effects of the individual treatments. In conclusion, this study introduces S. viridochromogenes as a novel microbial source for collagen nanoparticles biosynthesis and demonstrates the superior predictive performance of ANN-based modeling. The findings reveal that biosynthesized Sv-CollNPs, especially when combined with DOX, exhibit strong therapeutic potential and represent an eco-friendly, innovative strategy for anticancer nanomedicine development. Response surface methodology ; In vivo ; Nanoparticle ; Central composite design ; Biosynthesis ; Streptomyces ; Fourier transform infrared spectroscopy ; Cancer therapy ; Yield (engineering) Collagen: Extraction and Characterization ; Seaweed-derived Bioactive Compounds ; Wound Healing and Treatments
Authors: Mian Li | Hongmei Yin | Fei Gu | Yanjun Duan | Zhuang Wang | Kang Han | Xiaojun Jin
Source: Processes (article, 2025-08-22)
Field: Chemistry — Analytical Chemistry

Recent Advances and Applications of Nondestructive Testing in Agricultural Products: A Review With the rapid development of agricultural intelligence, nondestructive testing (NDT) has shown considerable promise for agricultural product inspection. Compared with traditional methods—which often suffer from subjectivity, low efficiency, and sample damage—NDT offers rapid, accurate, and non-invasive solutions that enable precise inspection without harming the products. These inherent advantages have promoted the increasing adoption of NDT technologies in agriculture. Meanwhile, rising quality standards for agricultural products have intensified the demand for more efficient and reliable detection methods, accelerating the replacement of conventional techniques by advanced NDT approaches. Nevertheless, selecting the most appropriate NDT method for a given agricultural inspection task remains challenging, due to the wide diversity in product structures, compositions, and inspection requirements. To address this challenge, this paper presents a review of recent advancements and applications of several widely adopted NDT techniques, including computer vision, near-infrared spectroscopy, hyperspectral imaging, computed tomography, and electronic noses, focusing specifically on their application in agricultural product evaluation. Furthermore, the strengths and limitations of each technology are discussed comprehensively, quantitative performance indicators and adoption trends are summarized, and practical recommendations are provided for selecting suitable NDT techniques according to various agricultural inspection tasks. By highlighting both technical progress and persisting challenges, this review provides actionable theoretical and technical guidance, aiming to support researchers and practitioners in advancing the effective and sustainable application of cutting-edge NDT methods in agriculture. Nondestructive testing ; Agriculture ; Engineering ; Computer science ; Biochemical engineering ; Medicine ; History ; Archaeology Spectroscopy and Chemometric Analyses ; Pesticide Residue Analysis and Safety ; Fault Detection and Control Systems
Authors: Lauren T. Creadore | Andrea Locaspi | Tricia M. Marchese | Matteo Pelucchi | Tiziano Faravelli | Marco J. Castaldi
Source: Fuel (article, 2025-08-29)
Field: Materials Science — Polymers and Plastics

A semi-detailed chemical kinetic model of polybutadiene pyrolysis Pyrolysis ; Polybutadiene ; Kinetic energy ; Chemistry ; Thermodynamics ; Chemical engineering ; Materials science ; Organic chemistry ; Physics ; Classical mechanics Polymer crystallization and properties ; Thermochemical Biomass Conversion Processes ; Thermal and Kinetic Analysis
Authors: Maciej Noga | Kamil Jurowski
Source: Scientific Reports (article, 2025-07-02)
Field: Chemistry — Spectroscopy

ADME of Bromo-DragonFLY as an example of a new psychoactive substance (NPS) – application of in Silico methods for prediction: absorption, distribution, metabolism and excretion Bromo-DragonFLY, a new psychoactive substance (NPS) within the phenethylamine class, is noted for its exceptional potency and prolonged psychoactive effects. Despite its severe toxic reactions and fatalities, research on its human metabolic fate remains limited. This study predicts the absorption, distribution, metabolism, and excretion (ADME) of Bromo-DragonFLY using in silico methods. Results indicate high gastrointestinal absorption and potential blood-brain barrier penetration, enhancing its central nervous system effects. The compound shows significant plasma protein binding and involves multiple cytochrome P450 isoenzymes in its metabolism, with variability in phase I and II reactions. Predicted metabolites form through epoxidation, quinone formation, UGT conjugation, and N-dealkylation, exhibiting reactivity with proteins, DNA, and glutathione, contributing to its toxicological profile. Excretion is predicted mainly via renal pathways. These insights are crucial for understanding the toxicological risks of Bromo-DragonFLY, exemplifying the challenges posed by NPS. ADME ; In silico ; Excretion ; Distribution (mathematics) ; Absorption (acoustics) ; Pharmacology ; Computational biology ; Chemistry ; Biology ; Pharmacokinetics ; Biochemistry ; Mathematics ; Materials science Analytical Chemistry and Chromatography ; Computational Drug Discovery Methods ; Metabolomics and Mass Spectrometry Studies