jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yajie Qian | Yanzhuo Sun | Jianqiao Xu | Pin Gao | Gang Xue | Xu Zhou | Yalei Zhang | Jiabin Chen
Source: Nature Communications (article, 2026-02-12)
Field: Chemistry — Inorganic Chemistry

Hydrated metal charge density as a universal descriptor explaining mechanistic variations in periodate activation toward pollutant degradation Although activation mechanisms of oxidants diverge significantly across different transition metals, whether the universal descriptor exists that can unify these pathways remains unknown. Herein, taking periodate (PI) as an example, we systematically explored the connection among Group VIII (8) metals (Fe(II), Ru(III), Os(III)). While all three metals activate PI effectively, Os(III) exhibits fundamentally different activation behavior compared to Fe(II) and Ru(III). PI activation by Os(III) primarily generated ·OH, promoting hydroxylated products formation; whereas high-valent metal-oxo species dominate in Fe(II) and Ru(III) systems, yielding epoxy products. Theoretical calculations indicate that Os(III) possesses a significantly higher positive charge density than that of Fe(II) and Ru(III). The high charge density of Os(III) enhances oxygen affinity, and reduces the energy barrier for single-electron transfer to water ligands, thereby promoting radical generation. Conversely, the lower charge density of Fe(II) and Ru(III) indicates a stronger affinity for electrons, favoring the oxygen atom transfer process. This work identifies metal charge density as a key descriptor modulating reaction mechanisms of oxidants and informs the design of tunable oxidation processes. Density functional theory ; Periodate ; Metal ; Charge (physics) ; Degradation (telecommunications) ; Charge density ; Oxygen ; Activation barrier Metal-Catalyzed Oxygenation Mechanisms ; Advanced oxidation water treatment ; Environmental remediation with nanomaterials
Authors: Kandasamy Sasikumar | G.Y. Lee | Ramar Rajamanikandan | Heongkyu Ju
Source: Preprints.org (preprint, 2026-01-20)
Field: Materials Science — Materials Chemistry

Advances in Carbon Dots-integrated Optical Fiber Sensors Carbon dots (CDs) have enormous potential in optical sensing applications because of their remarkable physicochemical properties. Benefiting from high specific surface area, rich active sites, bright photoluminescence, high photostability, and biocompatibility, CDs have been widely used as functional layers in optical fiber sensors, resulting in notable improvements in sensitivity, response speed, and environmental stability. This review describes recent advances in CD-integrated optical fiber sensors, with a focus on CD synthesis techniques and their integration with optical fibers for the sensing of diverse analytes, such as heavy metal ions, biomarkers, and dyes. CD-integrated fiber sensors exhibit significantly enhanced detection performance in terms of sensitivity, selectivity, repeatability, response time, and recovery time, compared to their non-CD counterparts. Finally, current challenges and future perspectives are discussed. This review aims to provide valuable insights for the design and development of novel CD-integrated optical fiber platforms for sensing chemically and biologically relevant analytes. Optical fiber ; Optical sensing ; Fiber optic sensor ; Fiber ; Focus (optics) ; Carbon fibers Carbon and Quantum Dots Applications ; Electrochemical sensors and biosensors ; Polydiacetylene-based materials and applications
Authors: Jeff Armstrong | Adam Jackson | Alin M. Elena
Source: arXiv (Cornell University) (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

High-Pressure Inelastic Neutron Spectroscopy: A true test of Machine-Learned Interatomic Potential energy landscapes Machine-learned interatomic potentials (MLIPs) promise to provide near density-functional theory accuracy at a fraction of the computational cost, offering a transformative route toward genuinely predictive chemistry. Yet their predictive validity beyond the training regime remains largely untested experimentally. Here we use pressure-dependent broadband inelastic neutron spectroscopy (INS) as a direct experimental probe of MLIP transferability. Employing a newly developed high-pressure superalloy clamp cell, we measure INS spectra of crystalline 2,5-diiodothiophene at 10~K under ambient conditions and at 1.5~GPa. A MACE-based MLIP, fine-tuned on targeted DFT data, reproduces the experimental spectra across 0--1200~cm$^{-1}$ at both pressures and remains thermodynamically stable under rigorous molecular dynamics validation at 300~K. The model captures systematic pressure-induced blue shifts arising from steric stiffening and reproduces an anomalous red shift at 453~cm$^{-1}$ driven by pressure-modified intermolecular interactions, providing direct validation of its many-body character. This constitutes the first experimental demonstration of MLIP transferability across distinct thermodynamic states using neutron spectroscopy, and establishes high-pressure INS as a stringent benchmark for predictive machine-learned potentials. Spectral line ; Neutron ; Transferability ; Interatomic potential ; Neutron spectroscopy ; Spectroscopy ; Inelastic neutron scattering ; Neutron scattering Machine Learning in Materials Science ; High-pressure geophysics and materials ; Inorganic Chemistry and Materials
Authors: Malik Muhammad Shoaib | Fatima Iftikhar | Tariq Mahmood | Khurshid Ayub | Basit Niaz
Source: Research Square (preprint, 2026-01-16)
Field: Chemistry — Inorganic Chemistry

Dft Based Photophysical Assessment of Novel 2-substituted-3-pyridin-2-yl-benzo-[d][1,3]-azaphosphole P-oxide for Organic Optoelectronic Applications Hyperpolarizability ; OLED ; Acceptor ; Organic electronics ; Organic semiconductor ; Charge (physics) ; Pyridine ; Charge carrier Synthesis and characterization of novel inorganic/organometallic compounds ; Organic Light-Emitting Diodes Research ; Organometallic Complex Synthesis and Catalysis
Authors: Nidhi Katendra Katendra | Suman Chandel Chandel | Dipesh Kumar | Vinay Sagar Verma Verma | Neha Mandle Mandle
Source: Indian Journal of Pharmaceutical Chemistry and Analytical Techniques (article, 2026-02-24)
Field: Materials Science — Materials Chemistry

&lt;b&gt;Quantum Dots in Materia Medica: Emerging Tools for Bioimaging and Targeted Drug Delivery&lt;/b&gt; Quantum dots (QDs) have revolutionized biomedical sciences by offering exceptional optical, electronic, and chemical versatility for simultaneous imaging, diagnostics, and targeted drug delivery. These semiconductor nanocrystals (2–10 nm), with their size-dependent fluorescence, high quantum yield, and superior photostability compared to conventional organic dyes, enable multiplexed bioimaging, real-time drug tracking, and precisely controlled theranostic applications. The tunable surface chemistry of QDs allows functional modification with targeting ligands, therapeutic agents, and biocompatible coatings, facilitating receptor-mediated targeting and stimuli-responsive drug release across diverse disease contexts. Advanced synthesis strategies—including colloidal, hydrothermal, and green (biogenic) methods—have enabled the production of eco-friendly alternatives to heavy-metal-based QDs, such as carbon quantum dots, graphene QDs, and silicon-based systems, which maintain superior optical performance while minimizing cytotoxicity concerns. Functionally, QDs act as multifunctional nanocarriers via mechanisms including fluorescence resonance energy transfer (FRET), pH-responsive release, enzyme-triggered activation, and light-mediated delivery. Pharmacokinetically, QD biodistribution is governed by size, surface charge, and coating, with optimal formulations achieving prolonged circulation and tissue-specific accumulation. Clinical successes in tumor imaging, gene delivery tracking, and theranostic platforms underscore their translational potential. However, challenges including long-term toxicity from heavy metals, physicochemical stability in biological fluids, batch-to-batch reproducibility, and regulatory standardization remain critical barriers. The integration of artificial intelligence for imaging interpretation and predictive pharmacokinetic modeling, alongside advances in biodegradable and personalized QD engineering, represents the next frontier. Collectively, quantum dots epitomize the convergence of materials science, molecular pharmacology, and digital health—transforming precision diagnostics and therapy into seamlessly integrated, patient-centric nanomedicines. Quantum dot ; Nanocarriers ; Drug delivery ; Biodistribution ; Biocompatible material ; Targeted drug delivery ; Förster resonance energy transfer ; Carbon quantum dots Carbon and Quantum Dots Applications ; Graphene and Nanomaterials Applications ; Nanoplatforms for cancer theranostics
Authors: Tanumoy Banerjee | Ingrid Xhafa | Matthew A. H. Wittman | Cullen M. Quine | Sarah Shulda | Thomas Gennett | Hanna Breunig
Source: ChemRxiv (article, 2026-03-26)
Field: Materials Science — Materials Chemistry

Techno-economic perspective on emerging cryogenic and noncryogenic boil-off hydrogen compression systems Boil-off hydrogen (BOH) loss from liquid hydrogen (LH2) storage and transfer infrastructure poses a critical challenge to the use of hydrogen in emerging aviation, space, and heavy-duty mobility applications.As LH2 infrastructure expands, it becomes paramount to identify strategies to minimize BOH loss, enhance exergy efficiency, and reduce hydrogen leakage-related safety issues.This work presents a detailed comparison of cryogenic and non-cryogenic BOH management, including three new process designs with heat integration for BOH recovery and compression up to 700 bars: multi-stage mechanical compression, metal-hydride (MH)-based compression, and an integrated re-liquefaction-vaporization system.Specifically, this work describes a thermally integrated three-stage mechanical compressorintercooler system; a two-stage MHbased BOH compression architecture using different AB2 hydrides (magnesium-based and Ti-Zr-Mn-based); and a cryogenic re-liquefaction cycle coupled with stages of cryopump and a vaporization setup, all operating at the initial BOH condition of 2 bar, 60 K (#213 C).A thorough techno-economic analysis (TEA) framework is developed, capturing the effects of process, economic, and operational parameters.While mechanical systems are dominated by initial capital cost and energy price, MH systems are sensitive to hydride cost and relevant thermodynamic parameters like reversible hydrogen uptake and cycle life.The reliquefaction-vaporization pathway offers the lowest cost of capture and compression, especially at higher discharge pressures, and is sensitive to annual throughput and plant operational lifetime.MH compression Posted on 26 March 2026 -CC-BY-NC-ND 4.0 -This is a preprint and has not been peer reviewed. Hydrogen storage ; Liquid hydrogen ; Exergy ; Work (physics) ; Hydrogen ; Capital cost ; Process integration ; Cryogenics ; Hydride Hydrogen Storage and Materials ; Chemical Looping and Thermochemical Processes ; Hybrid Renewable Energy Systems
Authors: Sven Erik Peters | Yang Xu | Felix Gerlich | Prof. Dr. Lutz Ackermann
Source: Synlett (article, 2026-01-22)
Field: Chemistry — Organic Chemistry

Tuning Proton-Electron Synergy for Electrooxidative Alkyne Annulation: Mechanistic Insights and Synthetic Application Abstract Electrooxidative catalysis surfaced as a resource-economic and increasingly viable platform toward sustainable organic synthesis. It challenges the paradigm of using stoichiometric chemical reagents with the aid of electricity to enable traceless electron and proton transfers. Thereby, molecular synthesis can be inherently connected to the hydrogen evolution reaction, while avoiding waste formation in the form of stoichiometric by-products. Alkynes represent a widely occurring structural motif of outstanding relevance in molecular synthesis. The direct exploitation of alkynes toward the activation of otherwise inert C─H bonds sets the stage for innovative dehydrogenative annulations, allowing for the rapid construction of structurally complex compounds. Specifically, the merger with earth-abundant metal catalysis constitutes a promising advancement in the light of green chemistry, bearing unique potential to redefine chemical processing. Catalysis ; Alkyne ; Reagent ; Stoichiometry ; Hydrogen bond ; Molecular machine ; Organic synthesis ; Chemical synthesis Radical Photochemical Reactions ; Metalloenzymes and iron-sulfur proteins ; Catalytic C–H Functionalization Methods
Authors: Jiamin Sun | Guangyuan Feng | Karol Strutyński | Gangamallaiah Velpula | Shaoxuan Yuan | Manuel Melle-Franco | Kunal Mali | Steven De Feyter
Source: Journal of the American Chemical Society (article, 2026-03-10)
Field: Materials Science — Materials Chemistry

Mechanistic Insights into Layered Growth of Imine-Linked Bilayer 2D Covalent Organic Frameworks The crystallinity and stacking order of two-dimensional covalent organic frameworks (2D COFs) critically govern their physical properties and performance. However, direct molecular-resolution insight into the growth of layered 2D COFs remains elusive, particularly for imine-linked systems. Herein, an imine-linked bilayer 2D COF is constructed at the solid-liquid interface, enabling time-dependent scanning tunneling microscopy (STM) visualization of interlayer growth. STM imaging reveals a layered growth mechanism involving defect-mediated nucleation, lattice-guided directional propagation, cross-defect growth, and oriented domain coalescence. This growth pathway gives rise to local ordered-on-disordered stacking embedded within predominantly AA stacking domains. These findings provide direct molecular-level insights into layered growth under surface-confined conditions and offer a conceptual perspective for considering stacking disorder in bulk imine-linked COFs. Stacking ; Bilayer ; Scanning tunneling microscope ; Covalent bond ; Perspective (graphical) ; Crystallinity ; Non-covalent interactions ; Atomic force microscopy Covalent Organic Framework Applications ; Surface Chemistry and Catalysis ; Pickering emulsions and particle stabilization
Authors: Fatiha Mebarki | Ahmed Bouaoune | Abderrhmane Bouafia | Souhaila Meneceur
Source: Journal of Sol-Gel Science and Technology (article, 2026-04-10)
Field: Materials Science — Materials Chemistry

ZnO nanoparticles synthesized by co-precipitation method: characterization and application in dye photodegradation and petroleum wastewater remediation via hydrocarbon degradation and heavy metal adsorption Petroleum wastewater, contaminated with organic dyes, hydrocarbons, and heavy metals (e.g., As, Cd, Pb, Zn), poses significant ecological and health risks, demanding effective remediation. This study details the synthesis of ZnO nanoparticles (NPs) via co-precipitation, optimized with calcination at 500 °C for 3 h to boost crystallinity. Characterization via UV-Vis spectrophotometry revealed a strong absorption peak at 310 nm and a 3.08 eV bandgap, ideal for photocatalysis. X-ray diffraction (XRD) confirmed a hexagonal wurtzite structure with a 23 ± 4 nm crystallite size, while FTIR identified Zn-O modes at 418 cm⁻¹ and 833 cm⁻¹. SEM displayed asymmetric particles (peaking at 60–70 nm), and a -27.6 mV zeta potential indicated excellent colloidal stability. Thermogravimetric analysis (TGA-DSC) showed a 14.3% mass loss up to 1000 °C, with an endothermic peak at 685 °C, reflecting thermal stability. Photocatalytically, ZnO NPs degraded 97.5% of methylene blue in 60 min (kapp = 0.06637 min⁻¹) and removed 93.3% oil-in-water, 91.4% chemical oxygen demand, and 97.7% total suspended solids from petroleum wastewater in 30 min. They also achieved >99.9% heavy metal adsorption, with 100% removal for Be, Cr, Mo, Sb, and Se. These results establish ZnO NPs as a potent, sustainable solution for wastewater treatment, tackling diverse pollutants. Thermogravimetric analysis ; Photodegradation ; Zeta potential ; Calcination ; Adsorption ; Wastewater ; Fourier transform infrared spectroscopy ; Nanoparticle ZnO doping and properties ; Advanced Photocatalysis Techniques ; Magnesium Oxide Properties and Applications
Authors: Leonardo Bertolucci Coelho | Daniel Torres | Miguel Bernal | Loïc Malet | Aleksei Makogon | Frédéric Kanoufi | Viacheslav Shkirskiy | Jon Ustarroz
Source: Corrosion Science (article, 2026-02-12)
Field: Materials Science — Metals and Alloys

Oxygen effects on passive film evolution and metastable pitting in 316L stainless steel using SECCM Corrosion ; Pitting corrosion ; Oxygen ; Dissolution ; Electrochemistry ; Metastability ; Aeration ; Limiting oxygen concentration Hydrogen embrittlement and corrosion behaviors in metals ; Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability
Authors: Yang Lin | Wengang Bu | Pengfei He | Jingjin He | Xiubing Liang | Zulai Li | Yehua Jiang | Xingjun Liu | Jing Feng | Xiaoyu Chong
Source: Journal of Advanced Ceramics (article, 2026-02-01)
Field: Materials Science — Materials Chemistry

Entropy enhancing toughness of diborides: First-principles insights and experimental validation The intrinsically low toughness and high brittleness of diboride ceramics are major limitations restricting their widespread application. Toughness can be enhanced through increased configurational entropy; however, the physical mechanisms underpinning this entropy-induced toughening remain poorly understood. In this study, a comprehensive approach from element screening to mechanistic elucidation and experimental validation is undertaken to address these gaps. First, a theory-guided element screening strategy is employed. Starting from dilute solid-solution models and integrating CALPHAD-based composition–property fitting, Ta, Nb, Mo, Hf, and V are identified for their synergistic optimization of hardness and toughness. Subsequently, the evolution of toughness with increasing configurational entropy is assessed using<em> B/G</em>, <em>K<sub>IC</sub></em>, and related metrics. The calculations are validated against available experimental data, revealing an almost monotonic trend, with the six-component system exhibiting a <em>K<sub>IC </sub></em>exceeding 5.8 MPa·m<sup>1/2 </sup>—approximately double that of the single-component counterpart. A systematic analysis of lattice distortion and crystal orbital Hamilton population is performed for diborides containing two to six alloying elements. From a bond-strength perspective, the toughening mechanism originates from increased thermodynamic disorder, which broadens and flattens the bond-strength distribution, giving rise to a “bond-strength trap.” Experimental validation is conducted on the (TiTa)B<sub>2</sub> and (TiNb)B<sub>2</sub> systems with pronounced bond-strength contrast, as well as the ternary (TiTaNb)B<sub>2</sub> system. The results corroborate the predicted electronic bonding evolution, while further analysis of phonon force constants and stacking fault energies indicates that the synergy between strengthened M–B bonds and reduced dislocation slip barriers underpins the enhanced toughness. Toughness ; Brittleness ; Population ; Ternary operation ; Fracture toughness ; Ceramic ; Structural material ; Stiffness ; Deformation mechanism MXene and MAX Phase Materials ; Advanced ceramic materials synthesis ; Boron and Carbon Nanomaterials Research
Authors: Daxue Hao | Hao Huang | Geng Li | Yu Wu | Shuming Zeng
Source: arXiv (Cornell University) (article, 2026-03-25)
Field: Materials Science — Materials Chemistry

Coupling of phase transition, anharmonicity, and thermal transport in CaSnF$_6$ Understanding the coupling between structural phase transitions and thermal transport is essential for designing functional materials with tunable properties. Here, we investigate this interplay in CaSnF$_6$ by combining first-principles calculations with a machine-learned neuroevolution potential that enables large-scale molecular dynamics simulations across a wide temperature range. The simulations accurately capture the first-order structural phase transition and associated lattice dynamics. We show that the negative thermal expansion originates from low-energy rigid unit modes involving cooperative rotations of corner-sharing [CaF$_6$]$^{4-}$ octahedra, which induce bond-angle bending and volume contraction. At the same time, strong anharmonicity, dominated by four-phonon scattering, plays a central role in suppressing lattice thermal conductivity ($κ_L$). Crucially, non-equilibrium simulations reveal a pronounced non-monotonic anomaly in $κ_L$ near the phase transition, deviating from the conventional $\sim 1/T^α$ behavior and providing direct transport evidence of lattice reconstruction. These results establish a unified mechanism linking lattice geometry, anharmonic vibrational dynamics, and thermal transport, and highlight the potential of machine-learned potentials for bridging atomic-scale phase transitions with macroscopic transport properties. Anharmonicity ; Phase transition ; Thermal ; Lattice (music) ; Molecular dynamics ; Coupling (piping) ; Thermal conductivity Thermal Expansion and Ionic Conductivity ; Machine Learning in Materials Science ; Thermal properties of materials
Authors: Nirmal Baishnab | Ankush Kumar Mishra | Hao Liu | Esther W. Gomez | Olga Wodo | Baskar Ganapathysubramanian
Source: ChemRxiv (article, 2026-01-29)
Field: Materials Science — Materials Chemistry

Materials-Microstructure-Performance Mapping in Organic Photovoltaics Organic photovoltaics (OPVs) require joint optimization of materials parameters and active-layer microstructure to maximize device performance, including short-circuit current, 𝐽𝑠𝑐. We present a material property and microstructure-aware surrogate that predicts across diverse donor-acceptor systems and microstructures while providing calibrated uncertainties and interpretable design rules. We curate a 25k-sample, physics-informed dataset by sweeping electron and hole mobilities (𝜇𝑛, 𝜇𝑝) and exciton lifetime (𝜏𝑥) across multiple microstructure classes, and derive a compact feature set that couples materials parameters with graph-based microstructure descriptors (interfacial area, and connectivity/tortuosity) to predict 𝐽𝑠𝑐. A lightweight random-forest model achieves 𝑅2 ≥ 0.98 with ≤ 40% of the data used for training, and maintains accuracy under material-wise holdouts (i.e., material property holdouts). Partial-dependence analyses reveal regime transitions in the coupled design space: at low mobilities and short 𝐿𝑑, performance is dual-transport-limited; beyond a mobility threshold, 𝜏𝑥 (hence 𝐿𝑑) and interfacial proximity dominate 𝐽𝑠𝑐. The framework accelerates exploration of material-microstructure trade-offs, identifies whether to intervene via material (mobilities, and 𝜏𝑥) or processing (phase-separation length scale, connectivity, interfacial area), and is extensible to other organic optoelectronic systems. Code, features, and data are released to enable reproducibility and reuse. Organic solar cell ; Microstructure ; Photovoltaics ; Property (philosophy) ; Set (abstract data type) ; Feature (linguistics) ; Ranging ; Characterization (materials science) ; Extensibility Machine Learning in Materials Science ; Organic Electronics and Photovoltaics ; Block Copolymer Self-Assembly