jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Qingxin Liu | Shuhua Song | Yinzhuan Ni | Mingli Yao | Ming Li | XinXIn Si
Source: Journal of the Chinese Chemical Society (article, 2026-04-12)
Field: Chemistry — Organic Chemistry

Discovery of a Novel <scp>FabI</scp> Inhibitor as Antibacterial Agents Based on Machine Learning ABSTRACT Staphylococcus aureus , a pathogen well known for its antibiotic resistance, is recognized by public health agencies as a high‐priority threat due to its remarkable ability to acquire multidrug resistance. The type II fatty acid biosynthesis (FAS‐II) pathway has emerged as a tractable and promising target for antibacterial drug discovery. Within this pathway, inhibition of enoyl‐acyl carrier protein reductase (FabI) can both suppress bacterial growth and restore the susceptibility of multidrug‐resistant strains to existing antibiotics. Although triclosan and isoniazid have been approved for bacterial infections, the variability of clinical outcomes underscores the urgent need to identify novel FabI inhibitors as backup options. Accordingly, we designed a multi‐stage computational strategy to identify FabI inhibitors from our in‐house chemical library, incorporating machine learning (ML)‐based classification models, molecular docking, ADMET property assessment, and clustering analysis. As a result, we characterized a novel chemotype, compound Y4 [N‐(2‐(4‐butoxybenzoyl)hydrazine‐1‐carbonothioyl)propionamide], as a FabI inhibitor with an IC 50 of 9.83 μM. Compound Y4 also demonstrated potent antibacterial activity against Staphylococcus aureus (MIC = 2 μg/mL) in broth microdilution assays, and molecular dynamics simulations were conducted to characterize its interactions with FabI and inform future structural optimization. In silico ; Triclosan ; Drug discovery ; Antibiotics ; Antibacterial activity ; Reductase ; Acyl carrier protein ; Pathogen ; Bacteria Antimicrobial agents and applications ; Antimicrobial Peptides and Activities ; Microbial Natural Products and Biosynthesis
Authors: Xianglin Liu | Kai Yang | Fanli Zhou | Yongxiang Liu | Hao Chen | Yijia Zhang | Dengdong Fan | Wenbo Li | Bingqiang Wang | Shixun Zhang | Pengxiang Xu | Yonghong Tian
Source: arXiv (Cornell University) (article, 2026-04-09)
Field: Materials Science — Materials Chemistry

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators The rapid advancement of deep learning is reshaping the hardware design landscape toward AI tasks, posing fundamental challenges for HPC workloads such as atomistic simulation. Here we present SMC-AI, a general algorithmic framework that extends the SMC-X method for efficient canonical Monte Carlo simulation on AI accelerators, including GPUs and NPUs, while maintaining extreme scalability. The implementation of SMC-AI on an NPU cluster reaches unprecedented performance, achieving MC simulation of 4 trillion atoms on 4096 NPU dies. This represents the largest ML-accelerated atomistic simulation reported, delivering 32X system size and 1.3X throughput than previous records, with a relatively small computational budget. Excellent strong and weak scaling efficiency are reached for both the NPU and GPU implementation. By decoupling ML models from simulation, SMC-AI creates an abstraction that facilitates integration and porting of diverse ML models, laying a foundation for the future development of scalable scientific software. Scalability ; Scaling ; Monte Carlo method ; Porting ; Abstraction ; Supercomputer ; Cluster (spacecraft) Machine Learning in Materials Science ; Parallel Computing and Optimization Techniques ; Block Copolymer Self-Assembly
Authors: Dilshod Nematov | Amondulloi Burkhonzoda | Iskandar Raufov | Sherali Murodzoda | Saidjafar Murodzoda | Sakhidod Sattorzoda | A R Ashurov | Makhsud Barot Islomzoda | Kholmirzo Kholmurodov
Source: arXiv (Cornell University) (article, 2026-04-07)
Field: Materials Science — Materials Chemistry

Optoelectronic and Thermoelectric Properties of High-Performance AlSb Semiconductors This study presents a comprehensive first-principles investigation of the optoelectronic and thermoelectric properties of aluminum antimonide (AlSb) in its cubic (F-43m) and hexagonal (P63mc) phases. Structural optimization was performed using the SCAN functional, and all electronic and optical properties were evaluated using the modified Becke-Johnson potential combined with the Hubbard correction (mBJ+U), which best describes the band-edge electronic structure, explicitly accounting for the contribution of the d-states of the Sb half-core, which cannot be adequately accounted for by conventional functionals and may be overestimated by hybrid approaches. Both AlSb phases are found to be quasi-direct bandgap semiconductors, with calculated band gaps of 1.71 eV for the cubic phase and 1.50 eV for the hexagonal phase, in good agreement with available experimental data. The optical response reveals strong absorption in the visible and ultraviolet regions, moderate reflectivity, and high refractive indices, indicating pronounced light-matter interaction characteristic of III-V semiconductors. The hexagonal phase exhibits enhanced low-energy optical absorption due to its reduced symmetry and narrower band gap. Thermoelectric analysis demonstrates large negative Seebeck coefficients, thermally activated carrier generation, and a monotonic increase of the power factor with carrier concentration for both phases. The cubic phase shows higher power factor values due to enhanced carrier mobility, whereas the hexagonal phase benefits from reduced thermal conductivity, which is favorable for thermoelectric performance at elevated temperatures. These results establish AlSb as a multifunctional semiconductor with tunable optoelectronic and thermoelectric properties and highlight the importance of an accurate treatment of Sb d-electron effects for reliable property prediction. Thermoelectric effect ; Antimonide ; Band gap ; Semiconductor ; Hexagonal phase ; Seebeck coefficient ; Phase (matter) ; Absorption (acoustics) Advanced Thermoelectric Materials and Devices ; Heusler alloys: electronic and magnetic properties ; 2D Materials and Applications
Authors: Xue Liu | Dario Calvani | Christopher Leist | Max Makurat | Adéla Melcrová | Meng He | Douwe Scholma | G. J. Agur Sevink | Francesco Buda | Yannick Hermans | Jan Philip Hofmann | Haoyuan Qi | Xinliang Feng | Wouter Roos | Ute Kaiser | Grégory F. Schneider
Source: Science Advances (article, 2026-01-02)
Field: Materials Science — Materials Chemistry

Monolayer nanocrystalline graphene synthesized from pyrolyzing a Langmuir monolayer of a polyaromatic hydrocarbon Bulk carbon materials can be synthesized through the modulation of precursor structures, stacking mode, and the optimization of pyrolysis conditions. The structure of two-dimensional (2D) carbon materials, however, is mainly driven by the pyrolysis temperature, pressure, and organic gas flow rates. Here, we report the synthesis of a centimeter-sized nanocrystalline graphene monolayer from pyrolyzing a Langmuir monolayer of a hexa(terpyridine)hexaphenylbenzene polyaromatic hydrocarbon (PAH) yielding a 2D carbon material with a thickness of 0.36 ± 0.07 nm. By designing the amphiphilic PAHs and reducing intermolecular π-π stacking interactions, a monolayer of horizontally aligned PAH was obtained at the water-air interface. During the pyrolysis, the monolayer served as a molecularly thin solid carbon source, leading to the controlled preparation of an electrically insulating nanocrystalline graphene monolayer. Our work proposes a 2D carbon material formed from the initial assembly of PAH monolayer at the water-air interface and subsequent pyrolysis and offers a modular strategy for designing nanocrystalline 2D films. Monolayer ; Stacking ; Nanocrystalline material ; Pyrolysis ; Graphene ; Carbon fibers ; Langmuir ; Hydrocarbon Graphene research and applications ; Covalent Organic Framework Applications ; Surface Chemistry and Catalysis
Authors: Muyun Lihan | Shashank Pant | Adedolapo Ojoawo | Chad M. Rienstra | Emad Tajkhorshid
Source: The Journal of Physical Chemistry B (article, 2026-03-27)
Field: Chemistry — Spectroscopy

Probing Solution Dynamics of Tissue Factor Using Molecular Dynamics Simulations Guided by NMR Chemical Shifts Structure and dynamics of proteins are key to understanding their roles in biological systems and provide a framework for rational development of novel therapeutics. Here, we combine NMR chemical shifts (CSs), X-ray crystal structures, and molecular dynamics (MD) simulations to characterize the extracellular domain of human tissue factor, i.e., soluble tissue factor (sTF), a protein that is involved in the initiation of the blood clotting process by forming a complex with the coagulation factor VIIa (fVIIa). Starting with the X-ray structures, solution NMR CSs were incorporated as restraints in CS-guided MD simulations to obtain structures in agreement with the NMR solution data of the protein. Our results reveal a dynamic ensemble of configurations in a loop that is key to sTF interaction with fVIIa. Key residues have been identified in the fVIIa-binding loop with divergent backbone and/or side-chain configurations to account for the loop dynamics. We demonstrate that the resulting structural ensemble from the incorporation of solution NMR CSs provides a better description of sTF dynamics in solution. The integrated approach used in this study can be applied to provide a better molecular guide for therapeutics that specifically target sTF. Dynamics (music) ; Molecular dynamics ; Chemical shift ; Chemical Dynamics ; Rotational dynamics Advanced NMR Techniques and Applications ; Electron Spin Resonance Studies ; NMR spectroscopy and applications
Authors: Chao Wang | Haowei Hu | Qin Li | Lin Guo | Mingyang Yang
Source: RSC Advances (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

Interfacial ion aggregation at SiO <sub>2</sub> nanoparticles enhances thermal energy storage of chloride molten salts: a molecular dynamics study Adding 8 amorphous SiO 2 nanoparticles to NaCl-KCl overcomes low thermal conductivity and limited specific heat capacity. MD simulations show 7.08% and 8.25% gains. Negatively charged SiO 2 induces ordered cation layers, enhancing energy transport. Nanoparticle ; Amorphous solid ; Molecular dynamics ; Thermal conductivity ; Chloride ; Ion ; Thermal Thermal Expansion and Ionic Conductivity ; Phase Change Materials Research ; Thermal properties of materials
Authors: Shikuan Shao | Victor Fernandez-Gonzalez | Xiaochuan Wang | Blake Pylipow | Claudia Herrera | Xiaohu Xia
Source: Advanced Science (article, 2026-02-26)
Field: Materials Science — Materials Chemistry

Peroxidase‐Mimicking Nanozymes for Rapid Detection of Infectious Diseases Infectious diseases pose a critical global health threat, and rapid and sensitive diagnostics are essential for effective intervention. Conventional methods are often slow, costly, and require centralized instrumentation and trained personnel, limiting timely decision-making. Peroxidase-mimicking nanozymes (PMNs) have emerged as powerful alternatives to natural peroxidases, enabling the development of rapid, sensitive, and robust diagnostic platforms. The superior performance of these platforms is rooted in the well-defined structural and compositional features of PMNs, which endow them with high peroxidase-like activity to catalyze substrate oxidation into easily detectable signals. Furthermore, the unique physicochemical properties of PMNs support the design of simplified workflows, miniaturized point-of-care devices, and novel sensing logics that are inaccessible to conventional protein enzymes. This review highlights structure-activity relationships guiding PMN design, synthetic strategies for constructing these nanozymes, their integration into biosensing platforms for infectious disease detection, and the role of artificial intelligence in PMN design and biosensing applications. By focusing on the interplay between PMN materials and sensing technologies, we illustrate how these systems advance rapid, sensitive, and cost-effective diagnostics. We also provide our perspective on the broader societal impact of PMN-enabled infectious disease diagnostics, along with the challenges and opportunities that shape their translation toward practical clinical use. Limiting ; Infectious disease (medical specialty) ; Human health ; Instrumentation (computer programming) ; Biosensor Advanced Nanomaterials in Catalysis ; Nanocluster Synthesis and Applications ; Advanced biosensing and bioanalysis techniques
Authors: Yamin Ben-Shimon | Barak Hirshberg | Yohai Bar‐Sinai
Source: npj Computational Materials (article, 2026-04-13)
Field: Materials Science — Materials Chemistry

Machine learning the entropy to estimate free energy differences without sampling transitions Thermodynamic phase transitions, a central concept in physics and chemistry, are typically controlled by an interplay of enthalpic and entropic contributions. In most cases, the estimation of the enthalpy in simulations is straightforward but evaluating the entropy is notoriously hard. As a result, it is common to induce transitions between the metastable states and estimate their relative occupancies, from which the free energy difference can be inferred. However, for systems with large free energy barriers, sampling these transitions is a significant computational challenge. Dedicated enhanced sampling algorithms require significant prior knowledge of the slow modes governing the transition, which is typically unavailable. We present an alternative approach, which only uses short simulations of each phase separately. We achieve this by employing a recently developed deep learning model for estimating the entropy and hence the free energy of each metastable state. We benchmark our approach by calculating the free energies of crystalline and liquid metals. Our method features state-of-the-art precision in estimating the melting transition temperature in Na and Al without requiring any prior information or simulation of the transition pathway itself. Metastability ; Entropy (arrow of time) ; Thermodynamic integration ; Benchmark (surveying) ; Phase transition ; Sampling (signal processing) ; Energy (signal processing) ; Enthalpy Machine Learning in Materials Science ; Quantum many-body systems ; Material Dynamics and Properties
Authors: Yadgar Hussein Shwan
Source: Research Square (preprint, 2026-04-13)
Field: Materials Science — Materials Chemistry

Comprehensive First-Principles Study of Thermoelectric, Electronic, Optical, and Stability Properties in Two-Dimensional BiClO Phonon ; Thermal stability ; Heat capacity ; Density functional theory ; Thermal ; Band gap ; Semiconductor ; Electronic band structure ; Electronic structure ; Dispersion (optics) Advanced Thermoelectric Materials and Devices ; Heusler alloys: electronic and magnetic properties ; Copper-based nanomaterials and applications
Authors: Rui Zheng | Saad Aldin Mohamed | Quan Liu | Xiaoyu Wu | Jianwen Jiang
Source: Journal of Materials Chemistry A (article, 2026-01-01)
Field: Chemistry — Inorganic Chemistry

CO <sub>2</sub> adsorption-induced anisotropic mechanical response in an 8-fold interpenetrated diamondoid metal–organic framework Hybrid Monte Carlo/molecular dynamics simulations are applied to explore CO 2 -induced structural transition of a flexible MOF. Monte Carlo method ; Anisotropy ; Diamondoid ; Molecular dynamics ; Compression (physics) Metal-Organic Frameworks: Synthesis and Applications ; Carbon Dioxide Capture Technologies ; Magnetism in coordination complexes
Authors: Biyuan Liu | Yonglin Zhang | Yue Zhao | Prabhat Prakash | Liyuan Huai | Hancheng Ma | Zhengtang Luo | W.A. Goddard | Jinglei Yang
Source: ACS Catalysis (article, 2026-03-17)
Field: Chemistry — Organic Chemistry

Interfacial Polymerization of TEPA and HMDI: The Role of Water The interfacial polymerization (IP) between tetraethylenepentamine (TEPA) and 4,4'methylenebis (cyclohexyl isocyanate) (HMDI) at the inorganic-organic solvent interface happens so fast that it is difficult to control the reaction and the morphology of the polymer. Through quantum mechanical (QM) calculations and molecular dynamics (MD) simulations, we clarify the catalytic effect of water on the rapid IP process in the organic phase. QM results reveal that a single water molecule acts as a proton transfer bridge by establishing hydrogen bonds with both TEPA and HMDI, and the hydrogen bonds lower the free energy barriers from 15.1-16.6 kcal·mol<sup>-1</sup> (in the absence of a single water molecule) to 2.3-3.1 kcal·mol<sup>-1</sup> (in the presence of a single water molecule) in implicit hexadecane. The interaction energy analysis, performed via the fine-tuned MACE FF, indicates that HMDI preferentially resides in the hexadecane phase, while TEPA is more likely to diffuse across the interface. The result provides an energy-based perspective for the partition in the IP process, and experimental observations confirm that polymerization occurs toward the organic phase. These findings provide direct evidence that a single water molecule facilitates IP, offering critical insights for the rational design and precise control of polymerization at the interface to enable improved regulation of reaction kinetics and polymer morphology. Polymerization ; Catalysis ; Hydrogen bond ; Molecule ; Polymer ; Solvent ; Radical polymerization ; Hexadecane Advanced Polymer Synthesis and Characterization ; Hydrogels: synthesis, properties, applications ; Photopolymerization techniques and applications
Authors: Nil Kanatha Pandey | Hong Huy Tran | Edward B. Steager | David P. Cormode | Hyun Koo
Source: Trends in biotechnology (article, 2026-04-01)
Field: Materials Science — Materials Chemistry

Can nanozymes make the leap to the clinic? Advances, hurdles, and prospects Key (lock) ; Scalability ; Translational research ; Proof of concept Advanced Nanomaterials in Catalysis ; Nanoplatforms for cancer theranostics ; Nanocluster Synthesis and Applications
Authors: Anja Voigt | Christian Strauch | Tom Höfken | Mirco Wahab | Wiebke Hadwich | Conrad Hübler | Stefanie Schneider | Felix A. Plamper | Christopher Barner-Kowollik
Source: Soft Matter (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

Following the Formation of Single-Chain Nanoparticles Generated by Interblock Crosslinking within Diblock Copolymers: A Monte Carlo Simulation Study with Adjustable Interaction Strength between the Blocks We investigated the folding and crosslinking of diblock copolymers with interblock-crosslinkable units in dilute solution. We used a bead-spring model for the polymer and Monte Carlo simulations for the crosslinking.... Monte Carlo method ; Nanoparticle ; Polymer ; Copolymer ; Folding (DSP implementation) ; Kinetic Monte Carlo ; Dynamic Monte Carlo method Block Copolymer Self-Assembly ; Advanced Polymer Synthesis and Characterization ; Advanced Physical and Chemical Molecular Interactions
Authors: Lukas Drexler | Cristina Duran | Sílvia Osuna | Reinhard Sterner
Source: ACS Catalysis (article, 2026-03-23)
Field: Materials Science — Materials Chemistry

The Discovery of <i>N</i> <sup>2</sup> , <i>N</i> <sup>2</sup> -Dimethylguanine Hydrolases Unravels General Molecular Principles of Enzyme Evolvability and Promiscuity The widespread use of xenobiotics has driven the rapid emergence of microbial degradation pathways. A prominent example is enzymes involved in the catabolism of the herbicide atrazine, which have evolved within the last few decades. Recently, we provided evidence that the second enzyme of the atrazine biodegradation pathway, hydroxyatrazine ethylaminohydrolase (AtzB), has evolved from a progenitor enzyme of the amidohydrolase superfamily (AtzB-CQNN) with guanine deaminase (GuaD) activity. However, the catalytic efficiency for guanine hydrolysis by AtzB-CQNN is several orders of magnitude lower than that of prototypical GuaDs. In this study, we report a much higher catalytic efficiency of AtzB-CQNN for the hydrolysis of the guanine analogue <i>N</i> <sup>2</sup>,<i>N</i> <sup>2</sup>-dimethylguanine (<i>k</i> <sub>cat</sub>/<i>K</i> <sub>M</sub> ∼10<sup>5</sup>-10<sup>6</sup> M<sup>-1</sup>s<sup>-1</sup>). This enzymatic activity has not been described up to now and appears to be the native function of AtzB-CQNN, as well as that of several AtzB homologues termed NdmH. An active site alanine scan of an NdmH enzyme allowed us to identify residues important for substrate binding and catalysis and to propose an enzymatic reaction mechanism. The comparative characterization of NdmHs and canonical GuaDs revealed an extended substrate scope and high evolvability of NdmH enzymes. A comprehensive computational evaluation, including conservation, covariance, and flexibility studies, as well as conformational landscape reconstruction and correlation-based shortest path map analysis, showed that this enhanced substrate promiscuity and evolvability of NdmHs compared with GuaDs are linked to a higher structural heterogeneity of the active site, which facilitates their functional diversification to act on xenobiotics. Evolvability ; Promiscuity ; Enzyme ; Substrate specificity ; Catalysis ; Drug discovery ; Protein–protein interaction Enzyme Structure and Function ; Metal-Catalyzed Oxygenation Mechanisms ; Biochemical and Molecular Research