jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Sipeng Wang | Shengfu Wu | Wenchao Hao | Minghua Liu
Source: Chemistry - An Asian Journal (article, 2025-05-20)
Field: Chemistry — Organic Chemistry

Nanoaggregation‐Enhanced and Inverted Circularly Polarized Luminescence in Isomeric Schiff Base Bis(boron difluoride) Complexes To elucidate the emergence and amplification of circularly polarized luminescence (CPL) in chiral molecules and their assemblies, we designed positionally isomeric chiral V-shaped Schiff base ligands and their corresponding bis(boron difluoride) complexes. The ligands were synthesized by condensing chiral cyclohexanediamine with either 1-hydroxy-2-naphthaldehyde or 2-hydroxy-1-naphthaldehyde, followed by complexation with boron difluoride (BF<sub>2</sub>) to yield CNB1 and CNB2, respectively. While the parent Schiff bases exhibited no CPL, BF<sub>2</sub> coordination induced strong CPL signals in solution. Remarkably, upon aggregation in a mixed solvent system, CNB2 displayed enhanced and inverted CPL, whereas its isomer CNB1 showed attenuated emission. Through comprehensive characterization and singlecrystal analysis, we attribute this divergent behavior to distinct molecular packing modes: CNB2 forms tightly stacked aggregates with efficient π─π interactions, while CNB1 adopts a less ordered arrangement. This study establishes a clear correlation between subtle structural modifications, supramolecular packing, and CPL performance, offering a rational strategy for tailoring chiroptical properties through precise molecular design and controlled self-assembly. Luminescence ; Schiff base ; Supramolecular chemistry ; Boron ; Aggregation-induced emission ; Chemistry ; Solvent ; Yield (engineering) ; Molecule ; Difluoride ; Materials science ; Photochemistry ; Crystallography ; Organic chemistry ; Fluorescence ; Optoelectronics ; Optics Synthesis and Properties of Aromatic Compounds ; Luminescence and Fluorescent Materials ; Organoboron and organosilicon chemistry
Authors: Mathilde Sundberg | Trine Berthing | Pernille Høgh Danielsen | Alicja Mortensen | J. Szarek | Christelle N. Prinz | Pernille Tveden‐Nyborg | Ulla Vogel
Source: Particle and Fibre Toxicology (article, 2025-11-22)
Field: Materials Science — Materials Chemistry

Fiber length and shape-dependent differences in hepatic nanomaterial localization in mice following pulmonary exposure These findings demonstrate that the intrahepatic localization of nanomaterials is strongly influenced by fiber shape and dimensions. Fiber ; Nanomaterials ; Nanotoxicology ; Collagen fiber ; Lung Nanoparticles: synthesis and applications ; Liver physiology and pathology ; Inhalation and Respiratory Drug Delivery
Authors: Yuxin Huang | Pengfan Li | Xuewei Yu | Shiliang Feng | Yanfeng Jiang | Pingping Yu
Source: Nanomaterials (article, 2025-06-12)
Field: Materials Science — Electronic, Optical and Magnetic Materials

CNT:TiO2-Doped Spiro-MeOTAD/Selenium Foam Heterojunction for High-Stability Self-Powered Broadband Photodetector Photodetectors are critical components in modern optoelectronic systems due to their extensive applications in information conversion and image storage. Selenium (Se), an element with a low melting point, a broad spectral response, and rapid response speed, exhibits a disadvantage of high optical reflectivity, which leads to a reduction in response. Spiro-MeOTAD, featuring controllable energy bands and facile processing, has its practical application limited by inadequate thermal and environmental stability. In this study, Spiro-MeOTAD-1 with enhanced stability was prepared through the optimization of dopants (Zn(TFSI)<sub>2</sub> and CNT:TiO<sub>2</sub>) within Spiro-MeOTAD, to create a Se-F/Spiro-MeOTAD-1 heterojunction photodetector by subsequently compositing with selenium foam (Se-F). The self-powered device demonstrates exceptional photovoltaic performance within the wavelength range of 350-800 nm at 0 V bias, exhibiting a maximum responsivity of 108 mA W<sup>-1</sup>, a switching ratio of 5 × 10<sup>3</sup>, a specific detectivity of 2.96 × 10<sup>12</sup> Jones, and a response time of 20 ms/50 ms. The device also demonstrates elevated environmental stability pretreatment at 140 °C following a one-month period. The photodetection stability of the Se-F/Spiro-MeOTAD-1 flexible PD was demonstrated by its capacity to retain 76.3% of its initial light current when subjected to 70 bending cycles at 30°. This finding further substantiates the photodetection stability of the material under various bending conditions. Further verification of the applicability of Spiro-MeOTAD-1 in Se-based devices establishes a novel paradigm for designing photodetectors with enhanced performance and stability. Photodetector ; Materials science ; Doping ; Broadband ; Heterojunction ; Optoelectronics ; Selenium ; Nanotechnology ; Optics ; Physics Ga2O3 and related materials ; Perovskite Materials and Applications ; Nanowire Synthesis and Applications
Authors: Chen Cheng | Yoo‐Seong Jeong | William J. Jusko
Source: Journal of Pharmaceutical Investigation (article, 2025-09-11)
Field: Chemistry — Analytical Chemistry

Meta-analysis of levamisole absorption and disposition across diverse species using a minimal physiologically-based pharmacokinetic model The online version contains supplementary material available at 10.1007/s40005-025-00770-6. Disposition ; Absorption (acoustics) ; Pharmacokinetics ; Levamisole Analytical Methods in Pharmaceuticals ; Pharmacogenetics and Drug Metabolism ; Antibiotics Pharmacokinetics and Efficacy
Authors: Zirui Fan | Julio A. Chirinos | Xiaochen Yang | Juan Shu | Yujue Li | Joan M. O’Brien | Walter R. Witschey | Daniel J. Rader | Ruben C. Gur | Bingxin Zhao
Source: medRxiv (preprint, 2025-01-15)
Field: Chemistry — Spectroscopy

The landscape of plasma proteomic links to human organ imaging Plasma protein levels provide important insights into human disease, yet a comprehensive assessment of plasma proteomics across organs is lacking. Using large-scale multimodal data from the UK Biobank, we integrated plasma proteomics with organ imaging to map their phenotypic and genetic links, analyzing 2,923 proteins and 1,051 imaging traits across multiple organs. We uncovered 5,067 phenotypic protein-imaging associations, identifying both organ-specific and organ-shared proteomic relations, along with their enriched protein-protein interaction networks and biological pathways. By integrating external gene expression data, we observed that plasma proteins associated with the brain, liver, lung, pancreas, and spleen tended to be primarily produced in the corresponding organs, while proteins associated with the heart, body fat, and skeletal muscle were predominantly expressed in the liver. We also mapped key protein predictors of organ structures and showed the effective stratification capability of plasma protein-based prediction models. Furthermore, we identified 8,116 genetic-root putative causal links between proteins and imaging traits across multiple organs. Our study presents the most comprehensive pan-organ imaging proteomics map, bridging molecular and structural biology and offering a valuable resource to contextualize the complex roles of molecular pathways underlying plasma proteomics in organ systems. Proteomics ; Biology ; Computational biology ; Human Protein Atlas ; Phenotype ; Bioinformatics ; Gene ; Protein expression ; Genetics Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Artificial Intelligence in Healthcare
Authors: Constantinos Valagiannopoulos
Source: Nanomaterials (article, 2025-05-25)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Causality Implications for Absorption by EM Metasurfaces A causal electromagnetic (EM) metasurface is backed by a lossless substrate and partially absorbs obliquely incoming rays. The integral of the absorbed power along the entire frequency axis is analytically evaluated, and the obtained sum rules indicate the global absorption by such a generic configuration. The beneficial influence of the plasma frequency and damping factor on the total absorbance score as well as the opposite effect of the angle of excitation, is noted. An overall lossless behavior at the incidence direction where the propagating waves into the substrate turn into evanescent is identified, once the magnetic field is parallel to the interface. The reported results can be useful in the tailoring of spectrally dependent absorption by a whole class of planar structures and, accordingly, in the forward and inverse design of lossy photonic metasurface setups. Lossless compression ; Lossy compression ; Absorption (acoustics) ; Absorbance ; Planar ; Optics ; Excitation ; Physics ; Electromagnetic radiation ; Electromagnetic field ; Inverse ; Materials science ; Computer science ; Mathematics ; Geometry ; Quantum mechanics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Plasmonic and Surface Plasmon Research
Authors: Ankur Khapre | Jayanta Hazarika | Rajadurai Chandrasekar
Source: Nature Communications (article, 2025-11-27)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Organic crystal active waveguide as an all-angle signal receiver and transmission platform for encrypted visible light communication Organic crystal waveguides, known for their excellent versatility in active and passive light-guiding, offer a promising alternative to conventional optical media in visible light communication (VLC) systems. As an example, here we show the use of an organic crystal, 2,2'-((1E,1'E)-hydrazine-1,2-diylidenebis(methaneylylidene))diphenol (SAA) with high photoluminescence quantum yield (≈25%), as an active optical waveguide medium for the real-time and error-free data communication in the visible spectral range. Employing the optical properties of SAA, the versatility of the organic crystal to modulate signals via dual active and passive waveguiding is demonstrated. The crystal's unique capability as an all-angle signal receiver for data transmission is demonstrated utilizing a microcontroller unit with ON-OFF keying modulation, surpassing the performance of conventional optical fibers. A prototypical real-time data transfer device is realized, capable of transmitting streams directly from the serial interface and reconstructing grayscale images with high fidelity. Overall, this work demonstrates implementation of organic crystal waveguide-based innovative VLC platform, offering a compact and efficient solution for next-generation photonic communication technologies. Visible light communication ; SIGNAL (programming language) ; Data transmission ; Visible spectrum ; Transmission (telecommunications) ; Keying ; Waveguide ; Optical communication ; Photonic crystal Nonlinear Optical Materials Research ; Luminescence and Fluorescent Materials ; Photonic and Optical Devices
Authors: Jun-Feng Zhao | Junliang Zhang | Hao Su | Yu Zhang | Kai Li | Haijuan Mei | Changwei Wu | Qingfeng Zhu | Weiping Gong
Source: Materials (article, 2025-08-12)
Field: Materials Science — Ceramics and Composites

Multiscale Finite Element Analysis of Warping Suppression in Microelectronics with Graded SiC/Al Composites High-power microelectronic packaging faces critical thermomechanical failures under rapid thermal cycling, primarily due to interfacial stress concentration and warping in conventional homogeneous heat sinks. To address this challenge, this study proposes a novel functionally graded SiC/Al composite with a tailored thermal expansion coefficient (CTE) gradient, designed to achieve adaptive thermal expansion matching between the chip and heat sink. Through multiscale finite element analysis, the stress-strain behavior and warping characteristics of homogeneous (Cu and Al) and gradient materials were systematically investigated. The results show that the gradient SiC/Al design significantly reduces the peak thermal stress and maximum warping deformation. The progressive CTE transition effectively mitigates abrupt interfacial strain jumps and extends device lifespan under extreme thermal loads. This advancement positions gradient SiC/Al composites as a key enabler for next-generation high-density packaging and power electronics requiring cyclic thermal stability. The study provides both theoretical insights into thermomechanical coupling and practical guidelines for designing robust electronic packaging solutions. Image warping ; Materials science ; Thermal expansion ; Microelectronics ; Composite material ; Finite element method ; Temperature gradient ; Temperature cycling ; Heat sink ; Electronic packaging ; Thermal ; Mechanical engineering ; Structural engineering ; Computer science Advanced ceramic materials synthesis ; Aluminum Alloys Composites Properties ; Thermal properties of materials
Authors: Rahul Sheshanarayana | Fengqi You
Source: Journal of Chemical Information and Modeling (article, 2025-09-26)
Field: Materials Science — Materials Chemistry

Rethinking Retrosynthesis: Curriculum Learning Reshapes Transformer-Based Small-Molecule Reaction Prediction Retrosynthesis prediction remains a central challenge in computational chemistry, particularly when models must generalize to rare or structurally complex reactions. We present a curriculum learning (CL) framework that reshapes model training by systematically controlling reaction difficulty during learning, directly addressing the challenge of chemical generalization. In contrast to conventional generative approaches that treat all training reactions uniformly, our method introduces reactions in a chemically informed progression, gradually exposing the model to increasingly complex transformations based on synthetic accessibility, ring complexity, and molecular size. This difficulty-aware pacing allows the model to better capture reaction conditionality, preserve chemical plausibility, and avoid failure modes commonly observed in rare or underrepresented transformations. Applied across three transformer-based architectures─ChemBERTa + DistilGPT2, ReactionT5v2, and BART─the framework yields substantial performance gains. Notably, the largest improvements are observed in the BART model, which lacks any chemical domain pretraining: CL improves its top-1 accuracy from 27.0% to 75.9% (+48.9%). The remainder of our evaluations use ChemBERTa + DistilGPT2 as a representative pretrained model. In low-data regimes with only 50% of the training data, CL increases top-1 accuracy from 16.9% to 46.6% (+29.7%). Under scaffold-based splits, CL improves top-1 accuracy by up to 29%, and in structurally dissimilar settings (Tanimoto similarity <0.4), CL boosts top-1 accuracy from 18.2% to 69.4% (+51.2%), demonstrating strong robustness to distributional shifts. These improvements are achieved without auxiliary labels, templates, or reaction class supervision. Looking forward, this CL framework may aid retrosynthetic route planning for pharmaceutical intermediates, catalysts, polymers, and functional materials. Robustness (evolution) ; Curriculum ; Retrosynthetic analysis ; Generative grammar ; Training set ; Domain (mathematical analysis) Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Mingjun Yang | Peiyu Zhang
Source: Communications in Computational Chemistry (article, 2025-10-06)
Field: Materials Science — Materials Chemistry

The Data-Centric Paradigm in Synthetic Chemistry: AI Reaction Modeling Needs More Than Reactant-Product Pairs AI-driven reaction modeling in synthetic chemistry faces critical data gaps: the scarcity of mechanistic descriptors and inconsistent experimental protocols, leading models trained on sparse reactant-product pairs to falter in tasks like yield prediction, selectivity control, or condition optimization. Recent advances in mechanism-aware data curation, such as hybrid rule-ML frameworks and computational datasets, demonstrate progress but remain limited to small molecules (≤10 heavy atoms) or gas-phase approximations. Concurrently, robot-based highthroughput experimentation (HTE) platforms standardize protocols for a small number of reaction classes yet lack end-to-end traceability, often omitting workup and followed separation and purification steps. To bridge these gaps, we propose a closed-loop framework integrating computational chemistry, robotic HTE, and multimodal AI to resolve critical reaction modeling tasks. From the perspective of future work, the field necessitates expanded collaboration across the community to tackle complex systems, extend HTE to underrepresented reactions, and align data ontologies. Interdisciplinary collaboration is essential to transition from retrospective pattern recognition to mechanism-driven discovery, anchoring AI in datasets that encode why reactions succeed, not merely what products form.AI-driven reaction modeling in synthetic chemistry faces critical data gaps: the scarcity of mechanistic descriptors and inconsistent experimental protocols, leading models trained on sparse reactant-product pairs to falter in tasks like yield prediction, selectivity control, or condition optimization. Recent advances in mechanism-aware data curation, such as hybrid rule-ML frameworks and computational datasets, demonstrate progress but remain limited to small molecules (≤10 heavy atoms) or gas-phase approximations. Concurrently, robot-based highthroughput experimentation (HTE) platforms standardize protocols for a small number of reaction classes yet lack end-to-end traceability, often omitting workup and followed separation and purification steps. To bridge these gaps, we propose a closed-loop framework integrating computational chemistry, robotic HTE, and multimodal AI to resolve critical reaction modeling tasks. From the perspective of future work, the field necessitates expanded collaboration across the community to tackle complex systems, extend HTE to underrepresented reactions, and align data ontologies. Interdisciplinary collaboration is essential to transition from retrospective pattern recognition to mechanism-driven discovery, anchoring AI in datasets that encode why reactions succeed, not merely what products form. Scarcity ; Field (mathematics) ; Computational model ; Synthetic data ; Perspective (graphical) ; ENCODE Machine Learning in Materials Science ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Amanda Rebelo de Azevedo | Patrick C. Nobre | Mateus H. Köhler | Bernardo A. Iglesias | Vanessa Nascimento
Source: ChemistrySelect (article, 2025-06-01)
Field: Chemistry — Spectroscopy

Design, Synthesis, Photophysical, Theoretical, and Electrochemical Characterization of Novel Organochalcogen‐DHPM‐Triazole Hybrids Abstract The integration of DHPM with a 1,2,3‐triazole core or an organochalcogen moiety, as well as the development of organochalcogen‐triazole hybrids, constitutes a robust strategy for the design of novel bioactive molecules and compounds with outstanding photophysical, DFT studies, and electrochemical properties. In this study, we designed and synthesized a novel hybrid molecule integrating organochalcogen, dihydropyrimidinone (DHPM), and 1,2,3‐triazole units. Efficient and practical synthetic protocols were developed, enabling rapid access to a series of 13 important new compounds. Furthermore, the photophysical characteristics and redox processes of the newly obtained compounds were thoroughly evaluated. Characterization (materials science) ; Electrochemistry ; Hybrid ; Combinatorial chemistry ; Triazole ; Chemistry ; Nanotechnology ; Materials science ; Photochemistry ; Biology ; Organic chemistry ; Physical chemistry ; Electrode ; Botany Molecular Sensors and Ion Detection ; Organoselenium and organotellurium chemistry ; Metal complexes synthesis and properties
Authors: Akeem A. Moronkola | Kamilu Folorunsho Oyedeko | Regina J. Patinvoh | Julius Gbenga Akinbomi | Steven Wainaina | Mohammad J. Taherzadeh
Source: Biomass Conversion and Biorefinery (article, 2025-02-07)
Field: Materials Science — Biomaterials

Optimization of volatile fatty acids from food wastes for polyhydroxyalkanoates synthesis Abstract This study considered production of volatile fatty acids (VFAs) through anaerobic digestion of food wastes for subsequent usage as raw materials for polyhydroxyalkanoates (PHAs) synthesis. Four types of food wastes including yam, plantain, pineapple, and watermelon peels, as well as their combinations, were initially digested anaerobically to determine the food wastes with highest production of VFA concentration. Yam and plantain peel mix was found to produce highest VFA concentration and yield, measuring 12.78 g/l and 0.64gVFA/gVS, respectively. This necessitated the use of the mix in a semi-continuous process for VFA production. For organic loading rate ranges between 1 and 4gVS/m 3 /day, acetic acid was observed to be dominant VFA accounting for 50.62% of total VFAs produced while butyric acid accounted for 29.84%. The statistical ANOVA regression, based on the experimental values obtained when VFA was used as a carbon source for PHA production, showed that the modeling algorithms provide a reasonably solid estimate of the PHA yield with the highest expected yield of 56.15% PHAs occurring at a VFA concentration of 2 g/l. Polyhydroxyalkanoates ; Chemistry ; Food science ; Waste management ; Pulp and paper industry ; Organic chemistry ; Biotechnology ; Environmental science ; Biochemical engineering ; Business ; Biology ; Engineering ; Bacteria biodegradable polymer synthesis and properties ; Microplastics and Plastic Pollution ; Electrospun Nanofibers in Biomedical Applications
Authors: Hilal Özçeli̇k | Emine Sezer | Esra Yaşar | Timuçin Güner | Emre Dokuzparmak | Sinan Akgöl
Source: Materials Chemistry and Physics (article, 2025-11-25)
Field: Chemistry — Analytical Chemistry

Artificial intelligence-assisted design of molecularly imprinted polymers for enriching C-reactive protein Molecularly imprinted polymer ; Polymer ; Methacrylate ; Selectivity ; Zeta potential ; Nanostructure ; Molecular recognition ; Rational design Analytical chemistry methods development ; Polymer Surface Interaction Studies ; Biosensors and Analytical Detection
Authors: Aysenur Bilgin | F. Aydin | Mahmut Furkan Kalkan | Akansel Cosgun | Sakda Jampasa | Tuğba Özer
Source: Measurement (article, 2025-12-08)
Field: Chemistry — Analytical Chemistry

Molecularly imprinted polymer-based electrochemical biosensors for medical diagnostics: Artificial intelligence perspective Molecularly imprinted polymer ; Biocompatible material ; Identification (biology) ; Perspective (graphical) ; Biosensor ; Applications of artificial intelligence Analytical chemistry methods development ; Electrochemical sensors and biosensors ; Advanced biosensing and bioanalysis techniques