jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: J. M. Maldonado | C. Drischler | R. J. Furnstahl | Petar Mlinarić
Source: Physical review. C (article, 2025-06-30)
Field: Chemistry — Spectroscopy

Greedy emulators for nuclear two-body scattering Applications of reduced basis method emulators are increasing in low-energy nuclear physics because they enable fast and accurate sampling of high-fidelity calculations, enabling robust uncertainty quantification. In this paper, we develop, implement, and test two model-driven emulators based on (Petrov-)Galerkin projection using the prototypical test case of two-body scattering with the Minnesota potential and a more realistic local chiral potential. The high-fidelity scattering equations are solved with the matrix Numerov method, a reformulation of the popular Numerov recurrence relation for solving special second-order differential equations as a linear system of coupled equations. A novel error estimator based on reduced-space residuals is applied to an active learning approach (a greedy algorithm) to choosing training samples ("snapshots") for the emulator and contrasted with a proper orthogonal decomposition (POD) approach. Both approaches allow for computationally efficient offline-online decompositions, but the greedy approach requires much fewer snapshot calculations. These developments set the groundwork for emulating scattering observables based on chiral nucleon-nucleon and three-nucleon interactions and optical models, where computational speed-ups are necessary for Bayesian uncertainty quantification. Our emulators and error estimators are widely applicable to linear systems. Scattering ; Physics ; Computer science ; Optics Advanced NMR Techniques and Applications ; Nuclear physics research studies ; Crystallography and Radiation Phenomena
Authors: Oliver Weismantel | Lakshani J. Weerarathna | Tanja Junkers
Source: ACS Applied Polymer Materials (article, 2025-01-02)
Field: Materials Science — Materials Chemistry

Autonomous Size-Targeting for Block Copolymer Nanoparticles Using the combination of flow synthesis with online dynamic light scattering (DLS) analysis for particle size characterization and fully autonomous computer control allows for reproducible and targetable synthesis of nanoparticles from block copolymer (BCP) solutions by rapid mixing with water in a defined micromixer environment. Using Bayesian optimization (BO), nanoparticle sizes become programmable and preselectable, and a wide range of sizes can be obtained per used BCP. Specifically, we show for a series of polystyrene-b-poly(N,N-dimethyl acrylamide) and polystyrene-b-poly(poly(ethylene glycol) methyl ether acrylate) BCPs how particles spanning from 130 to 280 nm can be systematically targeted, with sizes between 100 and 1000 nm being at least in principle also achievable. Further, Pareto fronts for the individual synthesis parameters overall flow rate, water volume fraction, and polymer concentration are obtained from the established routines and presented. This BO approach highlights the efficacy of autonomous flow platforms in achieving precise control over polymer self-assembly processes, offering an optimal production window for the development and optimization of polymeric nanostructures in diverse fields, such as drug delivery and materials science. Materials science ; Copolymer ; Nanoparticle ; Polystyrene ; Dynamic light scattering ; Polymer ; Ethylene glycol ; Nanotechnology ; Particle size ; Chemical engineering Block Copolymer Self-Assembly ; Advanced Polymer Synthesis and Characterization ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Bo Song | Tao Liu | Mingyan Zhao | Yan Cui | Junghui Chen | Zoltán K. Nagy | Rolf Findeisen
Source: Industrial & Engineering Chemistry Research (article, 2025-04-22)
Field: Materials Science — Materials Chemistry

Surrogate Modeling with Sensitivity-Based Experiment Design and Process Optimization of Seeded Cooling Crystallization: A Case Study on β-Form LGA To facilitate quality-by-design (QbD) of seeded cooling crystallization, a novel surrogate modeling and process optimization method is proposed in this paper, based on the design of experiments (DoE) with sensitivity analysis on the process operating conditions. To overcome the deficiency of the crystal growth kinetic model related to the population balance equation, which could not reflect the explicit relationship between the process operating conditions (e.g., initial solution supersaturation and cooling rate) and product crystal size distribution (CSD), a surrogate model is established by using the Gaussian process regression (GPR) approach, based on experimental data from a permitted range of operating conditions. Correspondingly, a swarm-based metaheuristic algorithm named beluga whale optimization (BWO) is adopted to determine proper hyperparameters in the surrogate model. By analyzing the global sensitivity analysis (GSA) of product CSD with respect to these operation conditions, a sensitivity-based DoE is developed to reduce the number of batch experiments required for implementation. Based on the established surrogate model, a comprehensive quality criterion is introduced to optimize these operating conditions, which takes into account the information entropy of product CSD together with the desired product yield and size range. The seeded cooling crystallization process of the β-form l-glutamic acid is tested to verify the effectiveness and merits of the proposed modeling and optimization method. Sensitivity (control systems) ; Seeding ; Crystallization ; Process engineering ; Process (computing) ; Surrogate model ; Design of experiments ; Process optimization ; Biological system ; Computer science ; Materials science ; Environmental science ; Chemical engineering ; Thermodynamics ; Mathematical optimization ; Mathematics ; Engineering ; Statistics ; Physics ; Biology Crystallization and Solubility Studies ; Process Optimization and Integration ; Fluid Dynamics and Mixing
Authors: Jun Yin | Honghao Chen | Ju Qiu | Wentao Li | Peng He | Jiali Li | Iftekhar A. Karimi | Xiaocheng Lan | Tiefeng Wang | Xiaonan Wang
Source: Nature Computational Science (article, 2025-09-09)
Field: Materials Science — Materials Chemistry

SurFF: a foundation model for surface exposure and morphology across intermetallic crystals Intermetallic ; Foundation (evidence) ; Surface (topology) ; Experimental data ; Surface energy ; Morphology (biology) Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Inorganic Chemistry and Materials
Authors: Yiwen Zheng | Vikas Varshney | Aniruddh Vashisth
Source: Macromolecules (article, 2025-04-21)
Field: Materials Science — Polymers and Plastics

Accelerated ReaxFF Simulations of Vitrimers with Dynamic Covalent Adaptive Networks Vitrimers are a novel class of sustainable polymers with dynamic covalent adaptive networks driven by bond-exchange reactions between different constituents, making vitrimers reprocessable and recyclable. Current modeling approaches of bond-exchange reactions fall short in realistically capturing the complete reaction pathways, which limits our understanding of the viscoelastic properties of vitrimers. This research addresses these limitations by extending and employing the Accelerated reactive molecular dynamics (ReaxFF) technique, thus enabling a more accurate representation of vitrimer viscoelastic behavior at the molecular level. Bayesian optimization is employed to select force field parameters within the Accelerated ReaxFF framework, and an empirical function is proposed to model temperature dependence, thereby controlling the reaction probabilities under varying temperatures. The extended framework is employed to simulate nonisothermal creep behavior of vitrimers under different applied stress levels, heating rates, and numbers of reactions. The simulation results agree with experimental findings in the literature, validating the robustness of the framework. ReaxFF ; Covalent bond ; Molecular dynamics ; Chemistry ; Nanotechnology ; Computational chemistry ; Statistical physics ; Chemical physics ; Materials science ; Physics ; Organic chemistry Polymer composites and self-healing ; Fuel Cells and Related Materials ; Polymer Nanocomposites and Properties
Authors: Ping Yi | Yufeng Wu | Juntao Wang | Qilei Liu | Yafeng Xing | Yue Lu | Cunfei Ma | Liyuan Duan | Jingnan Zhao | Qingwei Meng
Source: Organic & Biomolecular Chemistry (article, 2025-01-01)
Field: Chemistry — Organic Chemistry

Photocatalytic acceptorless dehydrogenation of flavanones by cationic Eosin Y as a bifunctional catalyst We report the first example of photocatalytic acceptorless dehydrogenation using cationic Eosin Y as a bifunctional photocatalyst, without metal catalysts or HAT reagents. Under Bayesian optimized conditions, a wide range of flavones were synthesized in moderate to excellent yields, many of which were reported with biological activities. Mechanistic studies suggest that flavones likely form through two HAT processes, with hydrogen release occurring <i>via</i> photoredox. Bifunctional ; Cationic polymerization ; Dehydrogenation ; Eosin Y ; Photocatalysis ; Catalysis ; Eosin ; Chemistry ; Reagent ; Photochemistry ; Organic chemistry ; Medicine ; Staining Radical Photochemical Reactions ; Catalytic C–H Functionalization Methods ; Asymmetric Hydrogenation and Catalysis
Authors: Aik Rui Tan | Johannes C. B. Dietschreit | Rafael Gómez‐Bombarelli
Source: The Journal of Chemical Physics (article, 2025-01-15)
Field: Materials Science — Materials Chemistry

Enhanced sampling of robust molecular datasets with uncertainty-based collective variables Generating a dataset that is representative of the accessible configuration space of a molecular system is crucial for the robustness of machine-learned interatomic potentials. However, the complexity of molecular systems, characterized by intricate potential energy surfaces, with numerous local minima and energy barriers, presents a significant challenge. Traditional methods of data generation, such as random sampling or exhaustive exploration, are either intractable or may not capture rare, but highly informative configurations. In this study, we propose a method that leverages uncertainty as the collective variable (CV) to guide the acquisition of chemically relevant data points, focusing on regions of configuration space where ML model predictions are most uncertain. This approach employs a Gaussian Mixture Model-based uncertainty metric from a single model as the CV for biased molecular dynamics simulations. The effectiveness of our approach in overcoming energy barriers and exploring unseen energy minima, thereby enhancing the dataset in an active learning framework, is demonstrated on alanine dipeptide and bulk silica. Sampling (signal processing) ; Computer science ; Statistics ; Data mining ; Econometrics ; Mathematics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Mass Spectrometry Techniques and Applications
Authors: Qizhen Hong | Massimiliano Bartolomei | Fernando Pirani | Quanhua Sun | Cecilia Coletti
Source: The Journal of Chemical Physics (article, 2025-03-19)
Field: Chemistry — Spectroscopy

The many faces of vibrational energy relaxation in N2(<i>v</i>) + O(1D) collisions: Dynamics on 1Π and 1Δ potential energy surfaces Complete datasets of rate coefficients for the vibrational quenching of molecular nitrogen by collision with electronically excited atomic oxygen O(1D) over a wide temperature range are calculated for the first time. Such data are important ingredients in the modeling of non-local thermal equilibrium conditions that characterize the atmosphere, media of astronomical interest, and cold and hot plasmas, where O(1D), also formed when O2 molecules break, represents a significant fraction of the gas mixture. To this end, we developed analytical potential energy surfaces (PESs) for the 1Π and 1Δ electronic states of the N2-O(1D) system to accurately describe the interaction in the long, medium, and first repulsive range of intermolecular distances, the most effective regions in inelastic collisions under a variety of conditions of interest. The derived PESs are used to calculate the vibration-to-translation (V-T) and vibration-to-electronic (V-E) energy transfer rates by mixed quantum-classical dynamics and by the Landau-Zener formulation, respectively. In addition, the datasets are extended to cover the entire N2 vibrational ladder by using the Gaussian process regression. The results show that at low temperatures, where V-E relaxation dominates, N2 vibrational quenching by O(1D) collisions is faster than by O(3P) collisions. Excited state ; Relaxation (psychology) ; Quenching (fluorescence) ; Atomic physics ; Intermolecular force ; Vibrational energy relaxation ; Potential energy ; Range (aeronautics) ; Chemistry ; Molecular dynamics ; Thermal ; Thermal equilibrium ; Excitation ; Physics ; Molecule ; Materials science ; Thermodynamics ; Computational chemistry ; Quantum mechanics ; Fluorescence Spectroscopy and Laser Applications ; Atmospheric Ozone and Climate ; Atmospheric chemistry and aerosols
Authors: Jie Tong | Dongfeng Yang
Source: Journal of Food Composition and Analysis (article, 2025-10-09)
Field: Chemistry — Analytical Chemistry

A near-infrared spectroscopy method for detecting corn starch content based on UVE-LightGBM feature selection Feature selection ; Partial least squares regression ; Random forest ; Linear regression ; Regression ; Pattern recognition (psychology) ; Mean squared error ; Regression analysis ; Chemometrics ; Principal component analysis Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Guanxing Li | Xiaojuan Hu | Chen Zou | Songda Li | Zhongkang Han | Wentao Yuan | Ze Zhang | Yong Wang
Source: Nature Communications (article, 2025-07-01)
Field: Materials Science — Materials Chemistry

Periodic one-dimensional subsurface channels induced by ordered oxygen vacancies on CeO2 (110) The distribution and interaction of oxygen vacancies (V<sub>O</sub>s) critically influence the properties of metal oxides, especially ceria, which is widely used in high-temperature industrial applications. However, V<sub>O</sub> behavior at elevated temperatures remains poorly understood due to the complexity of their interactions and the lack of predictive models. Here, we uncover a periodic one-dimensional subsurface channel on CeO<sub>2</sub> (110), formed by ordered V<sub>O</sub> distributions at high temperatures. This discovery is enabled by in-situ scanning transmission electron microscopy (STEM), first-principles calculations, and a compressed sensing-assisted cluster expansion model. Strong repulsive interactions between neighboring V<sub>O</sub>s drive their ordering, which relieves local stress from V<sub>O</sub>s and polarons and promotes channel formation. A large band gap between the occupied O 2p and unoccupied Ce 4 f band centers helps stabilize this structure. The resulting subsurface channel features sub-nanometer pores and polaron accumulation, enabling directional proton transfer and provides insights into the high catalytic activity of ceria in hydrogenation reactions. These findings not only offer a deeper understanding of V<sub>O</sub> interactions and their underlying mechanisms but also suggest strategies for tailoring V<sub>O</sub> behavior in metal oxides for advanced catalytic and energy applications. Oxygen ; Chemical physics ; Materials science ; Chemistry Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions ; Semiconductor materials and devices
Authors: Nazerke Kydyrbay | Mergen Zhazitov | Muhammad Abdullah | Zhexenbek Toktarbay | Yerbolat Tezekbay | Tolagay Duisebayev | Olzat Toktarbaiuly
Source: Molecules (review, 2025-06-23)
Field: Materials Science — Surfaces, Coatings and Films

Utilization of SiO2 Nanoparticles in Developing Superhydrophobic Coatings for Road Construction: A Short Review The application of superhydrophobic (SH) coatings in road construction has attracted growing attention due to their potential to improve surface durability, reduce cracking, and enhance skid resistance. Among various materials, SiO<sub>2</sub> nanoparticles have emerged as key components in SH coatings by contributing essential surface roughness and hydrophobicity. This review paper analyzes the role of SiO<sub>2</sub> nanoparticles in enhancing the water-repellent properties of coatings applied to road surfaces, particularly concrete and asphalt. Emphasis is placed on their influence on road longevity, reduced maintenance, and overall performance under adverse weather conditions. Furthermore, this review compares functionalization techniques for SiO<sub>2</sub> using different hydrophobic modifiers, evaluating their efficiency, cost effectiveness, and scalability for large-scale infrastructure. In addition to highlighting recent advancements, this study discusses persistent challenges-including environmental compatibility, mechanical wear, and long-term durability-that must be addressed for practical implementation. By offering a critical assessment of current approaches and future prospects, this short review aims to guide the development of robust, high-performance SH coatings for sustainable road construction. Nanoparticle ; Nanotechnology ; Materials science ; Business Surface Modification and Superhydrophobicity ; Polymer Nanocomposites and Properties ; Aerogels and thermal insulation
Authors: Harsh P. Chavda | Kevin J. Liang | Tanner J. Megna | Olivia R. Taylor | Grace Kim | Angie López | Ana Bahamonde
Source: ACS Catalysis (article, 2025-06-09)
Field: Chemistry — Organic Chemistry

Indole Photocatalysts and Secondary Amine Ligands Enable Nickel-Photoredox C(sp <sup>2</sup> )–Heteroatom Couplings Nickel-photochemical C(sp<sup>2</sup>)-heteroatom coupling reactions have emerged as a powerful tool for constructing diverse molecular architectures. However, most existing methods rely on expensive photocatalysts or specialized ligands, limiting their practicality and scalability. Here, we introduce a photocatalytic initiation strategy driven by inexpensive indoles, eliminating the need for designer photocatalysts. Additionally, we demonstrate the effectiveness of highly tunable secondary amine ligands in facilitating coupling while suppressing side reactions that sequester the Ni catalyst off-cycle. Our approach enables a broad range of amination and etherification reactions with good yields and functional group tolerance, providing a scalable platform for C-N and C-O couplings that relies on a readily available photocatalyst and cost-effective, modular ligands. Finally, mechanistic investigations suggest that the reaction operates via an unconventional aryl radical-initiated Ni(I/III) catalytic cycle, distinguishing it from traditional Ni-photoredox processes. This initiation mode, in which aryl radicals are generated under mild conditions compatible with organometallic catalysis, is expected to serve as a generalizable platform for other synthetic transformations beyond Ni-catalyzed processes. Heteroatom ; Nickel ; Catalysis ; Amine gas treating ; Indole test ; Chemistry ; Photoredox catalysis ; Combinatorial chemistry ; Photocatalysis ; Photochemistry ; Organic chemistry ; Ring (chemistry) Radical Photochemical Reactions ; Catalytic C–H Functionalization Methods ; Sulfur-Based Synthesis Techniques
Authors: Victoire Delattre | Remi Olivier Labeille | Nicholas Slade Shropshire | Kyra G. Kaiser | B.S. Kirkland | Keith Zvoch | Ioana Pavel
Source: Journal of Chemical Education (article, 2025-01-31)
Field: Chemistry — Physical and Theoretical Chemistry

A Laboratory Module for Physical Chemistry and Analytical Chemistry: The Kinetics of Aspirin Hydrolysis and Its Quantitation in Pharmaceutical Tablets In this three-component laboratory module, upper-division chemistry students were introduced to the kinetics of the aspirin hydrolysis reaction and determined the concentration of its active pharmaceutical ingredient (acetylsalicylic acid-ASA) using a modern, benchtop ultraviolet-visible (UV-vis) absorption spectrophotometer. In the first component, students prepared analyte solutions from over-the-counter aspirin tablets and a relevant number of standards (n = 9-10) through both serial and parallel dilutions. In the second component, the ASA concentrations of three over-the-counter formulations (325 mg per tablet) were determined with percent differences as small as 1.1% using the Beer-Lambert law and external calibration curves. In the third component, students evaluated the reaction order (pseudo-first order), the rate constant (e.g., k <i>=</i> 3.0 × 10<sup>-4</sup> s<sup>-1</sup> at 75 °C), and the activation energy (<i>E</i> <sub>a</sub> ∼ 67.3 kJ mol<sup>-1</sup>) of the hydrolysis reaction of ASA at various temperatures (e.g., 25, 37, 50, 75, and 85 °C). The last component was completed using a student-centered instructional approach, namely, process-oriented guided-inquiry learning (POGIL), which helped refine students' research process skills and both basic and in-depth laboratory skills (weighing, solution handling, micropipetting, operation of a pH meter and a modern, benchtop absorption spectrophotometer). The student and instructor evaluations indicated a positive learning experience and high interest in this laboratory that was inspired by the quality control and quality assurance of pharmaceutical drugs. Chemistry ; Kinetics ; Hydrolysis ; Aspirin ; Chromatography ; Organic chemistry ; Chemical engineering ; Biochemistry ; Engineering Various Chemistry Research Topics ; Analytical Chemistry and Chromatography ; Analytical Methods in Pharmaceuticals
Authors: Masoumeh Kaveh Zenjanab | Aysan Salemi | Abolfazl Doustmihan | Sajjad Alimohammadvand | Rana Jahanban‐Esfahlan
Source: Scientific Reports (article, 2025-08-11)
Field: Materials Science — Polymers and Plastics

Dual-loaded niosome-dendrimer nanoplatform enhances Tirapazamine delivery to hypoxic breast cancer cells Breast cancer (BC) is one of the most common cancers in women, requiring comprehensive treatment strategies to reduce disease burden and costs. In this study, we developed an innovative dual nanoparticle system based on niosome containing PAMAM/Tirapazamine (N@P/T), and studied its efficacy combining in silico and experimental validation. Molecular docking and protein-protein interaction network analysis identified HIF1A as a central target for Tirapazamine (TPZ), revealing multiple high-confidence binding sites and interactions with key cancer-related pathways. Our synthesized N@P/T system using the thin film hydration method showed a size of ~ 200 nm, a zeta potential of - 4 mV, and a spherical morphology. Further, MTT results demonstrated that N@P/T significantly enhances anti-cancer effects compared to P/T and free TPZ, exhibiting the lowest IC50 value of 14.14 μM, which indicates superior cytotoxic efficiency compared to P/T (IC50 = 71.37 μM) and free TPZ (IC50 = 143.3 μM). Annexin-V FITC/Pi double staining showed enhanced apoptosis-promoting effects of P/T (44.28%) and N@P/T (65.33%), partially via affecting expression levels of BCL2, caspase3 and BAX. The uptake assay revealed substantial internalization of N@P/T over 90% by 4h, while real-time PCR validated the HIF1A as a target for TPZ under hypoxia-stimulated condition. Furthermore, the spheroid size test demonstrates the superior penetration capability of N@P/T, leading to significant alterations in tumor spheroid size and morphology. Our integrated computational and experimental approach demonstrates that N@P/T effectively targets hypoxic cancer cells through specific molecular interactions, offering a promising strategy for BC treatment. Tirapazamine ; IC50 ; Chemistry ; Annexin ; Apoptosis ; Cancer cell ; MTT assay ; Paclitaxel ; HIF1A ; Biophysics ; Cancer research ; Cytotoxicity ; Molecular biology ; In vitro ; Cancer ; Biochemistry ; Biology ; Medicine ; Internal medicine Dendrimers and Hyperbranched Polymers ; Nanoparticle-Based Drug Delivery ; RNA Interference and Gene Delivery