jablonkagroup/rise_ai_scientists huggingface dataset:
Source: International Journal of Corrosion and Scale Inhibition (article, 2025-12-27)
Field: Materials Science — Materials Chemistry

Corrosion rate of steel radiator components coated with keruing oleoresin Steel radiators are extensively utilized in automobiles due to their superior thermal conductivity.Nonetheless, they are susceptible to corrosion, which may result in diminished vehicle performance.This study sought to investigate the chemical constituents of steel radiator components and assess the corrosion inhibition properties of keruing oleoresin as a natural, environmentally friendly coating material.The study focused on identifying the chemical composition of steel radiator components using emission spectroscopy and evaluating the corrosion rate of these components, coated with keruing oleoresin, in distilled water conditions via electrochemical testing.The findings indicate that a 5% concentration of keruing oleoresin yields optimal corrosion inhibition, exhibiting an open circuit potential (OCP) of -0.154 V, a corrosion rate of 0.0002 mmpy, and an inhibition efficiency (IE) of 88.15%.The research illustrates the efficacy of keruing oleoresin as a natural corrosion inhibitor for steel radiators, aiding in the prevention of corrosion and the preservation of radiator performance. Corrosion ; Radiator (engine cooling) ; Anti-corrosion ; Corrosion inhibitor ; Coating Corrosion Behavior and Inhibition ; Hydrogen embrittlement and corrosion behaviors in metals ; Material Properties and Failure Mechanisms
Authors: Óscar Moreno | Imad Azzeggarh | Jason P. Holland | Albert D. Windhorst | Jordi Llop
Source: Chemistry - A European Journal (article, 2025-11-29)
Field: Chemistry — Organic Chemistry

One‐Pot Base‐Free Suzuki‐Miyaura [ <sup>11</sup> C]Methylation: Kinetic and Mechanistic Insights The Suzuki-Miyaura cross-coupling reaction is one of the most powerful approaches for forming carbon-carbon bonds in the synthesis of carbon-11-labeled positron emission tomography (PET) radiotracers. Typically, Suzuki cross-coupling is performed in the presence of a base to activate the boron reagent and sustain the catalytic cycle. Here, we investigate the capacity of the Suzuki reaction to proceed under one-pot base-free conditions for [<sup>11</sup>C]methylation reactions and elucidate the mechanistic features that enable this transformation. Conditions were optimized to successfully achieve one-pot methylation of a model substrate using [<sup>11</sup>C]CH<sub>3</sub>I in the absence of base in moderate yields. Systematic substrate studies reveal that the reaction is partly governed by the electronic properties of the boron substrate, suggesting an alternative transmetallation pathway in this case. Kinetic studies using [<sup>14</sup>C]CH<sub>3</sub>I, together with kinetic isotope effect (KIE) measurements and density functional theory (DFT) calculations, reveal that oxidative addition remains the rate-determining step through a heterolytic pathway, consistent with the formation of a cationic Pd(II) intermediate that can undergo transmetallation in the absence of base. Together, these results provide new mechanistic insights into Pd-mediated [<sup>11</sup>C]C-C bond formation under the unique stoichiometric constraints of radiochemical conditions, expanding the understanding of base-free cross-coupling reactions with [<sup>11</sup>C]CH<sub>3</sub>I. Transmetalation ; Heterolysis ; Density functional theory ; Reagent ; Cationic polymerization ; Substrate (aquarium) ; Kinetic isotope effect ; Catalysis Catalytic Cross-Coupling Reactions ; Catalytic C–H Functionalization Methods ; Organoboron and organosilicon chemistry
Authors: Yuchen Duan | Jinwen Qin | Minhua Cao
Source: E3S Web of Conferences (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Anion/Cation Co-(de)Intercalation in Ti<sub>3</sub>C<sub>2</sub>T<sub>x</sub> Modified with Cobalt Phthalocyanine for Lithium-Ion Batteries Due to the shortage of lithium resources and the requirement for high-energy density in lithium- ion batteries (LIBs), anion/cation co-(de)intercalation based on the incorporation of both anions and cations from the electrolyte is expected to be a viable solution. In this work, through cobalt phthalocyanine (CoPc) modification, Ti 3 C 2 T x MXene utilizes cationic/anionic carriers for charge storage. Specifically, during the charging process, a reversible intercalation of PF 6 - anions occurs subsequent to the removal of Li ions. By unlocking the capability of anion/cation co-(de)intercalation, the as-designed Ti 3 C 2 T x -CoPc anode exhibits significant merits in terms of storage capacity (achieving up to nearly 3-fold improvement over the Ti 3 C 2 T x ) and excellent rate performance. Our findings highlight new anion/cation co-(de)intercalation chemistry for MXenes. Intercalation (chemistry) ; Cobalt ; Lithium (medication) ; Inorganic chemistry ; Electrolyte ; Ion ; Cationic polymerization ; Chemistry ; Anode ; Materials science ; MXenes ; Physical chemistry ; Nanotechnology ; Electrode ; Organic chemistry MXene and MAX Phase Materials ; 2D Materials and Applications ; Ferroelectric and Negative Capacitance Devices
Authors: Z. X. Fan | Zhimin Huang | Yinxin Li | Xiao‐Long Hu | Siyuan Shen | Yunliang Wang | Zilan Zhong | Shuhong Liu | Shan Yang | Song Wu | Min Wu | Lei Deng
Source: ArXiv.org (preprint, 2025-11-11)
Field: Materials Science — Materials Chemistry

Hierarchical Structure-Property Alignment for Data-Efficient Molecular Generation and Editing Property-constrained molecular generation and editing are crucial in AI-driven drug discovery but remain hindered by two factors: (i) capturing the complex relationships between molecular structures and multiple properties remains challenging, and (ii) the narrow coverage and incomplete annotations of molecular properties weaken the effectiveness of property-based models. To tackle these limitations, we propose HSPAG, a data-efficient framework featuring hierarchical structure-property alignment. By treating SMILES and molecular properties as complementary modalities, the model learns their relationships at atom, substructure, and whole-molecule levels. Moreover, we select representative samples through scaffold clustering and hard samples via an auxiliary variational auto-encoder (VAE), substantially reducing the required pre-training data. In addition, we incorporate a property relevance-aware masking mechanism and diversified perturbation strategies to enhance generation quality under sparse annotations. Experiments demonstrate that HSPAG captures fine-grained structure-property relationships and supports controllable generation under multiple property constraints. Two real-world case studies further validate the editing capabilities of HSPAG. Property (philosophy) ; Cluster analysis ; Masking (illustration) ; Mechanism (biology) ; Robustness (evolution) ; Hierarchical clustering Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Chemical Synthesis and Analysis
Authors: David R. Husbands | Çağrı Özsan | Athi Welsh | Richard J. Gammons | Angelo Frei
Source: ChemRxiv (preprint, 2025-06-06)
Field: Chemistry — Organic Chemistry

High-throughput Triazole-based Combinatorial Click Chemistry for the Synthesis and Identification of Functional Metal Complexes A new high-throughput combinatorial approach using CuAAc “Click” chemistry has been implemented to make 192 bidentate pyridyl-1,2,3-triazole ligands. This ligand library was coordinated to five metal scaffolds under mild conditions to yield 672 novel metal compounds, representing a novel methodology for the accelerated exploration of the transition metal complex chemical space. The prepared libraries have been showcased for compound discovery primarily in antimicrobial applications, with selected libraries further tested for catalytic and photophysical screening. We demonstrate the versatility of combinatorial metal complex synthesis by screening all crude mixtures for antibacterial activity and cytotoxicity, enabling the rapid identification of hit compounds. Six promising metalloantibiotics have been identified and re-synthesized, exhibiting activity against Gram-positive bacteria in the nanomolar range with favorable therapeutic windows. The reported methodology represents a significant expansion in the field of metal-based combinatorial chemistry and its application towards the systematic coverage of vast chemical spaces in the search for novel molecules with optimized properties. Click chemistry ; Throughput ; Triazole ; Identification (biology) ; Combinatorial chemistry ; Chemistry ; Metal ; Combinatorial synthesis ; Computer science ; Organic chemistry ; Biology ; Botany ; Operating system Click Chemistry and Applications ; Monoclonal and Polyclonal Antibodies Research ; Chemical Synthesis and Analysis
Authors: Yuan Chen | Jiangnan Xia | Rui Zhang | Yikai Xia | Minqiu Zhou | Yalei Fu | Ihab Ahmed | Ian Armstrong | Abhishek Upadhyay | Michael Lengden | Walter Johnstone | Paul Wright | Krikor Ozanyan | Mohamed Pourkashanian | H. McCann | Chang Liu
Source: IEEE Transactions on Instrumentation and Measurement (article, 2025-01-01)
Field: Chemistry — Spectroscopy

Machine Learning-Enhanced Laser Absorption Spectroscopy for Harsh-Environment Combustion Diagnosis Laser absorption spectroscopy (LAS) has been widely adopted as a diagnostic tool for reactive flow-field monitoring in industrial combustion applications. Despite various advancements in LAS signal processing schemes, these harsh environments inevitably impose noise and interference on the LAS measurement data, thus increasing inaccuracy and uncertainty in combustion analysis. This article proposes a machine learning (ML)-enhanced LAS methodology that significantly mitigates noise-induced distortions in absorption spectra, yielding a more accurate representation of the original spectral sequence through continuous measurements. The proposed method is a novel architecture that integrates a denoising autoencoder (DAE) with a long short-term memory (LSTM) network for enhanced LAS signal analysis. Developed entirely using in situ experimental data, this approach ensures strong portability for industrial combustion diagnostics, where multisource measurement noise is difficult to model or quantify. To validate the proposed method, we conducted a combustion experiment on an auxiliary power unit (APU), a full-scale commercial gas turbine aeroengine, focusing on exhaust temperature measurements using our advanced LAS technique. The experimental results demonstrate the efficacy of the proposed method in recovering high-fidelity absorption spectra from the noise-contaminated data, enabling more convenient, accurate, and stable APU exhaust temperature measurements with a standard deviation below <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$7.9~^{\circ }$ </tex-math></inline-formula>C. This indicates its significant potential in industrial combustion diagnostics, offering a reliable tool for precise analysis and assessment in harsh environments. Spectroscopy ; Materials science ; Combustion ; Absorption (acoustics) ; Laser ; Ultrafast laser spectroscopy ; Optoelectronics ; Optics ; Environmental science ; Computer science ; Physics ; Chemistry ; Composite material Spectroscopy and Laser Applications ; Water Quality Monitoring and Analysis
Authors: Maximilian Schebek | Jing He | Emil Hoffmann | Yuanqi Du | Frank Noé | Jutta Rogal
Source: ArXiv.org (article, 2025-12-30)
Field: Materials Science — Materials Chemistry

Assessing generative modeling approaches for free energy estimates in condensed matter The accurate estimation of free energy differences between two states is a long-standing challenge in molecular simulations. Traditional approaches generally rely on sampling multiple intermediate states to ensure sufficient overlap in phase space and are, consequently, computationally expensive. Boltzmann Generators and related generative-model-based methods have recently addressed this challenge by learning a direct probability density transform between two states. However, it remains unclear which approach provides the best trade-off between efficiency, accuracy, and scalability. In this work, we review and benchmark selected generative approaches for condensed-matter systems, including discrete and continuous normalizing flows for targeted free energy perturbation and FEAT (Free Energy Estimators with Adaptive Transport) combined with the escorted Jarzynski equality, using coarse-grained monatomic ice and Lennard-Jones solids as benchmark systems. All models yield highly accurate free energy estimates and, depending on the system, may require fewer energy evaluations than traditional methods. Continuous flows and FEAT are most efficient in energy evaluations, whereas discrete flows have substantially lower inference cost. By releasing all data together with our results, we enable future benchmarking of free energy estimation methods in condensed-phase systems. Free energy perturbation ; Benchmark (surveying) ; Estimator ; Context (archaeology) ; Scalability ; Metadynamics ; Energy (signal processing) Machine Learning in Materials Science ; Block Copolymer Self-Assembly ; Quantum many-body systems
Authors: Khushi R Kamble | Vaibhav V Chavhan | Sanchit R Motghare | Aparna Kulkarni | Gitanjali R. Shinde
Source: Cureus Journal of Computer Science. (article, 2025-09-08)
Field: Materials Science — Materials Chemistry

Software for Corrosion Protection Methods for Various Metals in Different pH Environments Corrosion remains a critical issue affecting the strength, efficiency, and lifespan of metallic components across numerous industries. Traditional corrosion prevention strategies often rely on outdated, generic approaches that fail to account for the specific properties of metals and the diverse environmental conditions - particularly varying pH levels - in which they operate. This lack of precision results in increased maintenance costs, production delays, and safety risks. To address these limitations, this study proposes a dynamic, user-centric system that provides accurate and customized corrosion prevention strategies. By allowing users to select parameters such as metal type and environmental pH, the system generates tailored recommendations based on a continuously updated database of peer-reviewed research. It also resolves the challenge of fragmented information by integrating current scientific findings into a single, intuitive platform. The proposed solution enhances the accessibility and applicability of corrosion prevention knowledge for both industrial professionals and researchers. Its ability to deliver rapid, data-driven suggestions not only reduces the risk of corrosion but also minimizes repair costs and improves operational efficiency. With potential applications across industries where material durability is critical, this system bridges the gap between research and practice while supporting informed decision-making and modern corrosion management. Corrosion ; Durability ; Software ; Corrosion prevention ; Production (economics) ; Key (lock) Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Smart Materials for Construction
Authors: Lakomiec, Mateusz
Source: KTH Publication Database DiVA (KTH Royal Institute of Technology) (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Atomistic investigation of the metallic nuclear fuel UMo: a preliminary study in the context of research reactors This work presents an investigation of the mechanical properties of uranium-molybdenum(UMo) nuclear fuel through atomistic simulations, combining classical molecular dynamicsand ab initio calculations.Classical molecular dynamics (CMD) calculations, leveraging the angular dependent potential(ADP) developed by Starikov et al.[1], were first employed to compute the density and elasticconstants of two uranium phases, molybdenum, and UMo alloy across different temperatures.This initial set of results was then compared to existing experimental data, showing overallagreement although some discrepancies were observed. Complementary ab initio simulationswere also performed at 0 K, and provided additional data on bulk moduli and atomic volumes,also displaying reasonable agreement with existing experimental data. Those calculationsserved as a reference point for the next steps of our investigation.We then proposed the development of Spectral Neighbor Analysis Potentials (SNAP), for purematerials and for the alloy. Those interatomic potentials were developed using an activelearning tool (MLACS) that combines both ab initio and CMD simulations. These SNAPpotentials reproduced the density, uranium density and elastic constants of U-10Mo (a targetedcomposition for usage as nuclear fuel in research reactors), with high accuracy, validating theiruse for atomistic simulations of this alloy. However, performance for other compositions wasless consistent, likely due to limited training data.Overall, the developed SNAP potentials provide with a reliable foundation for moleculardynamics studies of U-10Mo, while additional ab initio data and broader compositionalcoverage is required for more general usage for the potentials. Ab initio ; Context (archaeology) ; Experimental data ; Molecular dynamics ; Ab initio quantum chemistry methods ; Work (physics) ; Interatomic potential ; Uranium Nuclear Materials and Properties ; Rare-earth and actinide compounds ; Nuclear reactor physics and engineering
Authors: Mehpara Adygezalova Mehpara Adygezalova
Source: ETM Equipment Technologies Materials (article, 2025-11-22)
Field: Chemistry — Organic Chemistry

RESEARCH UNIVERSAL COMBINED INHIBITOR FOR THE OIL AND GAS INDUSTRY The inhibiting efficiency of a multifunctional combined inhibitor against hydrogen sulfide and carbon dioxide corrosion of St3 carbon steel was investigated using the gravimetric method in model formation water MI. Corrosion tests were carried out in sealed vessels with a volume of 0.5 L using flat steel specimens (St3) with dimensions of 30 × 20 × 1 mm. A combination of gossypol resin and MARZA was used as the multifunctional inhibitor, with diesel fuel and kerosene serving as solvents. It was established that when kerosene is used as the solvent, the protective efficiency of the inhibitor varies in the range of 75–96 %, while with diesel fuel it reaches 80–100 %. The study demonstrated that the use of the combined inhibitor in MI water containing hydrogen sulfide and carbon dioxide ensures a corrosion rate of approximately 0.04 g/m²·h during 24-hour tests at an inhibitor concentration of no less than 70 mg/L. With increased exposure time, a similar level of corrosion resistance can be achieved at a lower inhibitor concentration of 50 mg/L. A comparable trend was observed both in carbon dioxide and in hydrogen sulfide–carbon dioxide environments. Keywords: imitation, hydrogen sulfide, carbon dioxide, polarization resistance, electrochemical impedance spectroscopy, steel ductility, solid-phase diffusion, inhibition, hydrogen. Corrosion ; Kerosene ; Carbon dioxide ; Carbon steel ; Corrosion inhibitor ; Hydrogen sulfide ; Diesel fuel ; Gravimetric analysis Synthesis of Tetrazole Derivatives ; Corrosion Behavior and Inhibition ; Material Properties and Applications
Authors: Zhuocheng Xie | Julien Guénolé | Hexin Wang | Joé Petrazoller | Fatim-Zahra Mouhib | Antoine Guitton | Thiebaud Richeton | Stéphane Berbenni | Talal Al‐Samman
Source: Journal of Magnesium and Alloys (review, 2025-12-11)
Field: Materials Science — Biomaterials

Atomic-scale modeling of defects in magnesium and its alloys: A review International audience Magnesium ; Magnesium alloy ; Microstructure ; Work (physics) Magnesium Alloys: Properties and Applications ; Microstructure and mechanical properties ; Advanced Electron Microscopy Techniques and Applications
Authors: 鋭璽 張 | Ruixi Zhang
Source: Institutional Repositories DataBase (IRDB) (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Low friction of nitrogen-doped diamond-like carbon coating due to acidic liquid film and nitrogen-doped graphite oxide generated by dielectric barrier discharge in ambient air Coating ; Ambient pressure ; Oxide ; Graphite ; Dielectric Diamond and Carbon-based Materials Research ; Plasma Applications and Diagnostics ; Surface Modification and Superhydrophobicity
Authors: Wencheng Lu | Michael Hutcheon | Mads F. Hansen | Kapildeb Dolui | Shubham Sinha | Mihir Ranjan Sahoo | Chris J. Pickard | Christoph Heil | Anna Pakhomova | Mohamed Mézouar | Dominik Daisenberger | Stella Chariton | Vitali B. Prakapenka | Matthew Julian | Rohit P. Prasankumar | Timothy A. Strobel
Source: ArXiv.org (preprint, 2025-05-28)
Field: Materials Science — Materials Chemistry

Prediction and Synthesis of Mg$_4$Pt$_3$H$_6$: A Metallic Complex Transition Metal Hydride Stabilized at Ambient Pressure The low-pressure stabilization of superconducting hydrides with high critical temperatures ($T_c$s) remains a significant challenge, and experimentally verified superconducting hydrides are generally constrained to a limited number of structural prototypes. Ternary transition-metal complex hydrides (hydrido complexes)-typically regarded as hydrogen storage materials-exhibit a large range of compounds stabilized at low pressure with recent predictions for high-$T_c$ superconductivity. Motivated by this class of materials, we investigated complex hydride formation in the Mg-Pt-H system, which has no known ternary hydride compounds. Guided by ab initio structural predictions, we successfully synthesized a novel complex transition-metal hydride, Mg$_4$Pt$_3$H$_6$, using laser-heated diamond anvil cells. The compound forms in a body-centered cubic structural prototype at moderate pressures between 8-25 GPa. Unlike the majority of known hydrido complexes, Mg$_4$Pt$_3$H$_6$ is metallic, with formal charge described as 4[Mg]$^{2+}$.3[PtH$_2$]$^{2-}$. X-ray diffraction (XRD) measurements obtained during decompression reveal that Mg$_4$Pt$_3$H$_6$ remains stable upon quenching to ambient conditions. Magnetic-field and temperature-dependent electrical transport measurements indicate ambient-pressure superconductivity with $T_c$ (50%) = 2.9 K, in reasonable agreement with theoretical calculations. These findings clarify the phase behavior in the Mg-Pt-H system and provide valuable insights for transition-metal complex hydrides as a new class of hydrogen-rich superconductors. Ambient pressure ; Hydride ; Ternary operation ; Superconductivity ; Quenching (fluorescence) ; Palladium hydride ; Hydrogen ; Ab initio ; Hydrogen storage Hydrogen Storage and Materials ; Metallurgical and Alloy Processes ; High-pressure geophysics and materials