jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Seyyed Amir Siadati | Mohammad Ali Ebrahimzadeh | Rezvan Yazdian‐Robati | Esmaeil Babanezhad
Source: ChemistrySelect (article, 2025-12-01)
Field: Materials Science — Materials Chemistry

A Comparative DFT Approach on α‐Phographene and Phagraphene New Carbon Allotropes for Delivery of Ibrutinib Anticancer Drug Considering the Weak Interactions Study ABSTRACT This study presents a systematic density functional theory (DFT) investigation on the adsorption and sensing behavior of the anticancer drug ibrutinib (IBR) over a range of pristine and doped nanostructures, including phagraphene, B‐α‐phagraphene, coronene, C 19 B fullerene, B 4 C 5 N 3 , and B 3 S monolayers. Through an integrative analysis of adsorption energies, charge transfer, dipole moment variation, frontier orbital alignment, topological parameters (QTAIM, electron localization function [ELF], and localized orbital locator [LOL]), the study delineates distinct interaction regimes from weak van der Waals attraction to polarization‐assisted chemisorption. Among the examined systems, C 19 B and B 3 S exhibit the strongest adsorption energies (−1.19 and −1.08 eV), highest electron transfer, and pronounced orbital hybridization, suggesting their dual capability as efficient IBR sensors and stable drug carriers. Electronic structure analyses, particularly projected density of states (PDOS) and conductivity changes, confirm that these doped frameworks induce significant modulation in electronic transport upon IBR adsorption, enabling real‐time detection prospects. The negligible adsorption, observed on pure carbon systems, highlights the essential role of heteroatom doping in enhancing interfacial reactivity. Collectively, these insights offer a coherent structure–property correlation and propose boron/sulfur functionalization as a strategic route to tailor nanomaterial surfaces for biomedical and sensing applications. The outcomes not only advance the molecular‐level understanding of drug–nanostructure interactions but also provide a theoretical foundation for designing next‐generation hybrid materials in targeted drug delivery and nanosensortechnologies. Density functional theory ; Ibrutinib ; Heteroatom ; van der Waals force ; Adsorption ; Electronic structure ; Doping ; Graphene ; Nanomaterials Boron and Carbon Nanomaterials Research ; Graphene research and applications ; Graphene and Nanomaterials Applications
Authors: Jinchao Mu | Chunfen Liu | Quanxi Zheng | Lianxin Liu | Yu Liu
Source: Journal of Engineering Science and Technology Review (article, 2025-01-01)
Field: Materials Science — Polymers and Plastics

Selection and Optimization of the Synthesis of Paliperidone Raw Material The synthesis of paliperidone suffers from a lengthy synthetic route with cumbersome steps, leading to low efficiency.The reaction system is sensitive to raw material purity and temperature, making parameter control difficult.Furthermore, product purification is complex, driving up costs and providing low yields.At the same time, the interaction of multiple parameters results in insufficient process stability, hindering large-scale production.In this study, an optimized synthetic route was proposed to address the interrelated deficiencies in the efficiency, controllability, purification, and stability of existing paliperidone synthesis processes.A multidimensional evaluation system was first established to screen the optimal candidate process.Subsequently, response surface methodology was employed to optimize key parameters, including feed ratios, reaction temperature, and solvent systems, synergistically on the basis of the above process.In the final stage, orthogonal experiments validated the optimization outcomes, culminating in the establishment of a process optimization model.Results demonstrate that, the optimized route starting from (2,4-difluorophenyl) (piperidin-4-yl) methanone hydrochloride streamlines the synthesis to include oxime formation, Williamson ether synthesis, amidation, and purification.This optimized process significantly enhanced product quality and yield, achieving a total synthesis yield of 50.69%.The product structure was confirmed by combined H-NMR, MS, and IR analysis, with related substance content exceeding 99.8%.This study provides a practical solution for addressing key technical challenges in the industrial production of paliperidone, laying a technical foundation for subsequent process scale-up and industrial optimization. Selection (genetic algorithm) ; Raw material ; Paliperidone Synthesis and properties of polymers ; Multicomponent Synthesis of Heterocycles ; Synthesis and Characterization of Pyrroles
Authors: Sharah A. Aldulmani | Afaf Y. Khormi | Abdel‐Nasser M.A. Alaghaz | Mohamed R. Shaaban
Source: Research Square (preprint, 2025-07-04)
Field: Chemistry — Organic Chemistry

Synthesis, spectral characterization, DFT, antimicrobial, cell cycle and molecular docking studies on benzothiazole derivatives and its nano-sized platinum (IV) mixed ligand complex Benzothiazole ; Docking (animal) ; Platinum ; Chemistry ; Combinatorial chemistry ; Antimicrobial ; Characterization (materials science) ; Ligand (biochemistry) ; Nanotechnology ; Stereochemistry ; Materials science ; Organic chemistry ; Biochemistry ; Receptor Synthesis and biological activity ; Metal complexes synthesis and properties ; Inorganic and Organometallic Chemistry
Authors: Hanzi Gao | Edgar Africano Camargo | Jude N Ubi | Xiuyuan Duan | Xiaolin Tian | HaiTeng DENG | Guojun Zheng | Shuaihua Gao
Source: Protein Science (article, 2025-12-22)
Field: Chemistry — Organic Chemistry

Hydrogen‐deuterium exchange reveals catalytically linked protein flexibility in myoglobin‐mediated intramolecular C(sp <sup>3</sup> )‐H activation A comprehensive understanding of the biophysical parameters that dictate high catalytic efficiency in enzymes is essential for advancing both fundamental enzymology and its applications. Experimental evidence suggests that protein dynamics play a pivotal role in transiently shaping active site configurations, facilitating the efficient traversal of reaction barriers. In a previous study, protein engineering led to the development of a triple mutant of myoglobin, which enabled the successful synthesis of an array of chiral flavanone compounds through myoglobin-mediated carbene transfer. To gain deeper insights into the molecular mechanisms underlying the evolution of structural dynamics that contribute to the accelerated catalytic properties, we first performed hydrogen-deuterium exchange mass spectrometry (HDX-MS) analyses on both the wild-type myoglobin and the engineered triple mutant in the presence and absence of a substrate analog to elucidate conformational changes and impacts of mutations on protein flexibility and functional dynamics. HDX-MS analysis identified distinct regions of the protein, both proximal and distal to the mutation sites, which exhibited differential HDX behaviors in response to either ligand binding or mutation, thereby providing insights into the structural and dynamic evolution of the mutant. We postulate that the mutation reconfigures the conformational ensemble of the protein, thereby promoting favorable conformational sampling and enhancing the efficiency of the catalyzed reaction. Computational studies further support this conclusion, providing additional insights into the structural and dynamic factors influencing enzymatic efficiency. This study highlights the critical role of protein structural dynamics in evolved enzymes, underscoring the potential of probing and harnessing these dynamics for advancements in protein engineering and redesign. Molecular dynamics ; Protein dynamics ; Protein engineering ; Conformational ensembles ; Active site ; Protein structure ; Rational design ; Förster resonance energy transfer ; Protein design ; Mutant Cyclopropane Reaction Mechanisms ; Enzyme Catalysis and Immobilization ; Mass Spectrometry Techniques and Applications
Authors: Raphaël Robidas | Claude Y. Legault
Source: ChemRxiv (article, 2025-08-20)
Field: Materials Science — Materials Chemistry

Distilling System Complexity to Enable Unbiased and Predictive Computational Reaction Investigations Computational modelling is a powerful tool to study chemical reactions. Currently, human guidance is nearly always required to avoid the intractable complexity of all a priori possible reaction steps, which consequently greatly limits automated predictive applications. In this work, we present novel theoretical strategies based on the concept of atomic reactivity, as well as a "neophile" kinetic model, demonstrating how they enable unbiased automated reaction modelling with molecules of size typically encountered in experimental methodologies. Our framework allows the identification of unlikely or redundant reaction steps based on first principles and previous analyses, while the neophile kinetic model separates crucial reaction intermediates from inconsequential ones. These advances significantly improved modelling efficiency, allowing us to automatically model 17 unimolecular gold(I)-catalyzed reactions of increasing complexity, starting only from the reactant and catalyst. In 10 reactions, the experimental product distribution is closely reproduced, with 5 additional cases yielding essentially correct reaction networks. Our results demonstrate that it is possible to predictively model catalytic reactions without human guidance through an innovative reformulation of the problem. Computer science ; Computational complexity theory ; Algorithm Machine Learning in Materials Science
Authors: Ruo-fan Li | Chen Hua | Xue-qing Chen | Zhong-shan Deng | Ming-hui Guo | Qian Li | Jing Liu
Source: Communications Materials (article, 2025-12-29)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Quasi-2D gallium oxide X-ray detector X-rays, characterized by their short wavelength and high penetrating power, are indispensable across numerous fields. Current X-ray detection relies heavily on amorphous selenium (a-Se) and medium bandgap semiconductors (e.g., Si, CdTe, CZT), which often face limitations including complex large-scale fabrication, high cost, and stability issues under intense irradiation. While alternative wide-bandgap materials like diamond offer excellent performance, challenges related to scalable fabrication and cost often remain. Here, we report a high-performance X-ray detector based on solution-processed quasi-two-dimensional (2D) gallium oxide (Ga₂O₃) films fabricated via a novel liquid metal nano-printing technique. Leveraging the ultra-wide bandgap and high quality of the printed Ga₂O₃, the device achieves an ultra-high sensitivity of 6050 μC/Gy/cm². We further demonstrate the practical utility of these detectors by integrating them into a functional X-ray imaging system. This work establishes liquid metal nano-printing as a vital pathway for the rapid fabrication of ultrathin, high-performance, low-power-consumption X-ray detectors. Additionally, this work enables low-dose, high-resolution X-ray imaging for medical diagnostics and non-destructive testing, demonstrating a cost-effective pathway toward portable radiation detection systems. Wide-bandgap materials are attractive for x-ray detectors, but they face issues with scalable fabrication and cost. Here, a high-performance x-ray detector based on solution-processed quasi-two-dimensional gallium is fabricated via a liquid metal nano-printing technique. Fabrication ; Detector ; Particle detector ; Gallium nitride ; Gallium ; Semiconductor ; X-ray detector Ga2O3 and related materials ; Thin-Film Transistor Technologies ; Digital Radiography and Breast Imaging
Authors: Yifan Ke | Xinming Qin | Wei Hu | Jinlong Yang
Source: Digital Discovery (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Combining DeepH with HONPAS for accurate and efficient hybrid functional electronic structure calculations with ten thousand atoms This work develops a DeepH + HONPAS interface for efficient large-scale electronic structure predictions. The method enables accurate and efficient simulations for systems with over 10 000 atoms. Density functional theory ; Hybrid functional ; Electronic structure ; Work (physics) ; Computer science ; Statistical physics ; Physics ; Quantum mechanics Machine Learning in Materials Science ; Advanced NMR Techniques and Applications ; Advanced Chemical Physics Studies
Authors: Amanda C Vitello | Howard D. Mettee | Ganesaratnam K. Balendiran
Source: Journal of Materials Science and Chemical Engineering (article, 2025-01-01)
Field: Chemistry — Organic Chemistry

Experimental Enthalpies of Combustion of Organic Materials and The Correlation with Total Number of Bonds, Their Molecular Surface and Volume Properties Experimentally determined heats of combustion of 21 random diverse organic materials are measured using traditional oxygen bomb calorimetry, as internal energy difference, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>Δ</mml:mi> <mml:mi>U</mml:mi></mml:math> , and enthalpy change, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>Δ</mml:mi> <mml:mi>H</mml:mi></mml:math> , reveal trends that correlate with their molecular properties which are calculated from the crystal structures. The R<sup>2</sup> values between <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>Δ</mml:mi> <mml:mi>H</mml:mi></mml:math> and total number of covalent bonds, vdW volume, molecular volume, vdW surface area, molecular surface area, solvent accessible surface area and molecular weight are 0.95, 0.91, 0.91, 0.89, 0.87, 0.85 and 0.79, respectively. Oxygen content of the substances increases, rise of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>Δ</mml:mi> <mml:mi>H</mml:mi></mml:math> reflected whereas this pattern breaks down when another element is introduced instead. The linear correlations between <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>Δ</mml:mi> <mml:mi>U</mml:mi> <mml:mo>,</mml:mo> <mml:mspace></mml:mspace> <mml:mi>Δ</mml:mi> <mml:mi>H</mml:mi></mml:math> and the structure based molecular properties at molecule level described above are not limited, restricted or deviated by the type of elements, H, C, N, O, Cl that make up the materials or molecular class of substance. Materials science ; Volume (thermodynamics) ; Combustion ; Thermodynamics ; Surface (topology) ; Chemical engineering ; Physical chemistry Chemical Thermodynamics and Molecular Structure ; Thermal and Kinetic Analysis ; Energetic Materials and Combustion
Authors: A. Tabynbayeva | Aliya Satayeva | N. S. Akhmetov | Куаныш Тастамбек | Жандос Тауанов
Source: NNC RK Bulletin (article, 2025-12-08)
Field: Materials Science — Materials Chemistry

COMPOSITE MEMBRANES BASED ON MXene AND NANOCELLULOSE: PROPERTIES AND WATER PURIFICATION EFFICIENCY The scarcity of water resources and the deterioration of water quality have become critical environmental and social challenges. Rivers, lakes, and groundwater are increasingly contaminated due to industrial, agricultural, and domestic activities, with pollutants including heavy metals, organic dyes, pharmaceutical residues, microplastics, and pathogenic microorganisms. Such contamination disrupts ecosystems, threatens biota, and poses risks to human health. Conventional water treatment methods, such as sedimentation, chlorination, adsorption, and ion-exchange resins, are often insufficient for the complete removal of complex or highly concentrated pollutants. Consequently, membrane-based technologies have emerged as a promising approach, offering molecular-level separation, low energy consumption, and environmentally safe operation. Recently, composite membranes based on MXene and nanocellulose have attracted significant attention. MXenes, twodimensional carbides and nitrides derived from MAX phases, possess a layered structure, high electrical conductivity, hydrophilicity, and functional surface groups, enhancing ion separation efficiency and adsorption of organic contaminants. Nanocellulose, a biodegradable nanomaterial, improves the mechanical strength, stability, and biocompatibility of membranes, while also increasing selectivity and antifouling performance. The combination of MXene and nanocellulose exhibits a synergistic effect: nanocellulose prevents aggregation of MXene layers, and strong interfacial interactions protect membranes from defects. This synergy enables efficient removal of salts, heavy metals, organic dyes, pharmaceutical residues, and microplastics, while the layered structure and functional groups ensure long-term stability and high performance. This review highlights the properties of MXene and nanocellulose, methods for fabricating composite membranes, their structural characteristics, and potential applications in water purification. The study underscores the potential of nextgeneration membrane technologies as environmentally safe, highly efficient, and durable solutions for sustainable water treatment, demonstrating both scientific significance and practical relevance. Nanocellulose ; Portable water purification ; Membrane ; Composite number ; Biofouling ; Water treatment ; MXenes ; Biocompatibility ; Ultrafiltration (renal) MXene and MAX Phase Materials ; Membrane Separation Technologies ; Nanomaterials for catalytic reactions
Authors: Dr. Basharat Hamid
Source: International Journal of Advances in Science and Technology Perspectives (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Next-Generation Nanomaterials for High-Performance Energy Storage and Sustainable Power Systems The accelerating global energy demand and the transition toward renewable power systems have intensified the search for advanced energy storage technologies. Conventional battery systems, although widely adopted, face significant limitations in terms of energy density, charge–discharge rates, lifecycle stability, and environmental impact. Next-generation nanomaterials offer a transformative pathway for overcoming these constraints by enabling superior electrochemical performance through structural engineering at the nanoscale. This paper examines the role of emerging nanomaterial classes—including graphene derivatives, MXenes, metal–organic frameworks (MOFs), nanoscale solid electrolytes, and engineered nanocomposites—in enhancing the efficiency, reliability, and sustainability of modern energy storage systems. Through a multidisciplinary analysis integrating material science, electrochemistry, sustainability engineering, and scalable manufacturing, the study outlines a holistic framework for future energy storage innovation. The findings provide actionable insights for researchers, industries, and policymakers aiming to accelerate the deployment of sustainable power systems worldwide. Sustainability ; Energy storage ; Renewable energy ; Software deployment ; Electrochemical energy storage ; Scalability ; Electric power system ; Efficient energy use ; Energy transition MXene and MAX Phase Materials ; Advancements in Battery Materials ; Dielectric materials and actuators
Authors: Ajmal Shah
Source: Biomedical Journal of Scientific & Technical Research (article, 2025-06-11)
Field: Materials Science — Biomaterials

Iron Oxide Nanoparticles: Synthesis and Functionalization for Biomedical Applications Iron oxide (Fe₂O₃) nanoparticles have garnered significant attention in biomedical research due to their unique magnetic properties, biocompatibility, and versatile surface chemistry. This review explores various synthesis methods for Fe₂O₃ nanoparticles, including co-precipitation, thermal decomposition, and hydrothermal techniques, with a focus on controlling particle size, shape, and crystallinity. Surface modification ; Nanoparticle ; Iron oxide nanoparticles ; Nanotechnology ; Materials science ; Chemistry ; Chemical engineering ; Engineering Nanoparticle-Based Drug Delivery
Authors: Fernando Fajardo-Rojas | Ryther Anderson | Katherine Ardila | Alexander J. Pak | Diego A. Gómez‐Gualdrón
Source: ChemRxiv (preprint, 2025-06-12)
Field: Chemistry — Inorganic Chemistry

Interactions of Common Synthesis Solvents with MOFs Studied via Free Energies of Solvation: Implications on Stability and Polymorph Selection Solvents are central to metal-organic framework (MOF) solvothermal synthesis. However, how solvent-MOF interplay impacts MOF stabilization individually and across polymorphs is not well understood. To address this knowledge gap, here we perform data-driven analysis of 20,532 heats of adsorption at dilute conditions (∆Hads) and 447 free energies of solvation (∆Fsol) for four solvents. Namely, dimethylformamide (DMF), water (H2O), methanol (MeOH), and n-hexane (C6) (which was used as control). To accelerate data collection, we developed a protocol to extrapolate ∆Fsol from calculations with the MOFs only partially solvated. Free energies were obtained via thermodynamic integration. We found ∆Fsol and ∆Hads to be only moderately correlated due to solvent-solvent interactions coming into play when the MOF is solvated. In any case, trends in ∆Fsol were ultimately explained on the basis of solvent kinetic diameter and polarity, as well as MOF void fraction (Vf) and functionalization polarity. For instance, the correlation between ∆Fsol and Vf was one of the strongest correlations presented in this study (more so as solvent size increases), indicating that small-pore MOFs are more easily stabilized by solvation than large-pore MOFs. We also found that solvation-induced MOF stabilization became more pronounced as solvent kinetic diameter (polarity) decreased (increased). We found differences in this solvation-induced stabilization between polymorphs capable of overcoming inherent (i.e., in vacuum) differences in polymorph stability, causing the most stable polymorph to “switch.” We found the probability to cause “switches” to increase as solvent kinetic diameter (polarity) decreased (increased). Inspection of multivariate linear regression coefficients suggested that differences in solvation-induced stabilization in polymorphs can be primarily explained by their differences in density, void fraction and, to a lesser extent, volumetric surface area. Solvation ; Selection (genetic algorithm) ; Stability (learning theory) ; Computational chemistry ; Chemistry ; Chemical physics ; Materials science ; Organic chemistry ; Solvent ; Computer science ; Machine learning Metal-Organic Frameworks: Synthesis and Applications