jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Zaman Yazbeck | Federico Bribiesca Argomedo | Minh Tu Pham | Bertrand Morel | V DIMITRIOU
Source: International Journal of Hydrogen Energy (article, 2025-11-28)
Field: Materials Science — Materials Chemistry

System-level monitoring and diagnosis of starvation faults in solid oxide electrolyzers International audience Oxide ; Starvation ; Solid surface Advancements in Solid Oxide Fuel Cells ; High-Temperature Coating Behaviors ; Molten salt chemistry and electrochemical processes
Authors: MULYANA YUSUF | Ghany Heryana
Source: Journal of Applied Mechanical Technology (article, 2025-12-31)
Field: Materials Science — Materials Chemistry

Review Chemical Machining Process: Principles, Types, and Applications ABSTRAK – Permesinan kimia (chemical machining) adalah proses manufaktur non-tradisional yang memanfaatkan reaksi kimia terkontrol untuk menghilangkan material secara selektif dari benda kerja. Tinjauan ini membahas secara mendalam mengenai prinsip dasar, jenis, dan aplikasi dari teknologi permesinan kimia. Proses ini melibatkan beberapa tahapan kunci, termasuk pembersihan, aplikasi maskant (pelindung), etsa kimia (etching), dan pelepasan maskant. Dibahas pula berbagai jenis utamanya, seperti chemical milling untuk pengurangan berat, chemical blanking untuk pembuatan komponen tipis, dan photochemical machining (PCM) untuk produksi komponen presisi tinggi. Ulasan ini juga menganalisis keunggulan signifikan dari proses ini, seperti kemampuan untuk mengerjakan material sulit tanpa menimbulkan tegangan mekanis dan kemampuannya menghasilkan geometri yang rumit. Di sisi lain, keterbatasan seperti laju pengikisan material yang rendah, potensi undercut, dan isu penanganan limbah kimia juga dievaluasi. Aplikasi utama dalam berbagai industri strategis, termasuk dirgantara, elektronik, dan medis, disajikan untuk menunjukkan relevansi dan pentingnya teknologi ini dalam manufaktur modern. Machining Material Selection and Properties ; Engineering and Technology Innovations ; Arduino and IoT Applications
Authors: S. Nikila | S. Harini | R. Sowmya | Attar Kubaib | Predhanekar Mohamed Imran | S. Guhanathan
Source: Research Square (preprint, 2025-08-22)
Field: Materials Science — Polymers and Plastics

Synthesis and Computational Evaluation of pH-Sensitive hydrogel networks based on Citric Acid and 1,4-Butanediol for Cationic Dye Adsorption Cationic polymerization ; Citric acid ; Adsorption ; Chemistry ; 1,4-Butanediol ; Chemical engineering ; Inorganic chemistry ; Nuclear chemistry ; Biochemistry ; Organic chemistry ; Engineering ; Catalysis Conducting polymers and applications ; Electrochemical sensors and biosensors
Authors: Hong-ji Ding | Xinghua He | Xia Yi | Wei Zhang | Qian Dang | Xuefei Wang | Guohuai Liu | Chi Zhang | Mingming Pan
Source: Journal of Materials Engineering and Performance (article, 2025-12-15)
Field: Materials Science — Materials Chemistry

First-Principles Study on Stability and Hydrogen Evolution Reaction Behavior of Mg17Al12 (001) and Mg24Y5 (001) Surfaces Electronegativity ; Adsorption ; Atom (system on chip) ; Charge density ; Hydrogen ; Hydrogen atom ; Phase (matter) Hydrogen Storage and Materials ; Magnesium Alloys: Properties and Applications ; Nanoporous metals and alloys
Authors: Hongjian Yu | Jiang Chang | Wenrui Chi | Gao Shu-zhen | Jie Liu | Yin Tang
Source: Polymers (article, 2025-06-29)
Field: Materials Science — Polymers and Plastics

Computer-Guided Development of Hyperbranched Modified Starch-Based Adhesives In this study, a novel starch-based adhesive (SBA) was proposed, which mainly involved the synthesis of a carboxyl-terminated hyperbranched polymer using bisphenol A diglycidyl ether (DGEBA) and citric acid as raw materials. Subsequently, starch was modified through hyperbranching to enhance the shear strength and water resistance of the SBA. For this purpose, the feasibility of the reaction between DGEBA and citric acid was analyzed using quantum mechanical simulations. Subsequently, both substances were simulated to synthesize carboxyl-terminated hyperbranched polymers with different ratios. Starch was modified through hyperbranching to establish various models of SBAs, and their properties were estimated using molecular dynamics simulations. Theoretical analysis indicates that a DGEBA-to-citric acid ratio of 3:7 yields a SBA with relatively optimal properties. The solubility parameter of this adhesive is 19.05 (J/cm<sup>3</sup>)<sup>1</sup>/<sup>2</sup>, suggesting strong intermolecular interactions between the hyperbranched polymer and starch. The synthesized adhesive exhibits high cohesive strength, with an estimated water contact angle of up to 138°, indicating good hydrophobicity. Furthermore, the system demonstrates favorable mechanical performance, with a shear modulus of 4.34 GPa and a bulk modulus of 8.80 GPa. Additionally, at this ratio, the SBA exhibits a relatively high interaction energy of -408.01 kcal/mol with the cellulose substrate, suggesting that the adhesive possesses favorable shear strength. Adhesive ; Materials science ; Citric acid ; Starch ; Polymer ; Hildebrand solubility parameter ; Chemical engineering ; Epoxy ; Composite material ; Dynamic mechanical analysis ; Polymer chemistry ; Organic chemistry ; Chemistry Dendrimers and Hyperbranched Polymers ; Advanced Polymer Synthesis and Characterization ; Synthesis and properties of polymers
Authors: Prasanthi Samathoti | Sai Ramya Bodagala
Source: Journal of Applied Pharmaceutical Research (article, 2025-04-30)
Field: Materials Science — Biomaterials

Advancements in smart wearable patch systems for enhanced wound healing Background: Chronic wounds afflict around 2% of the world's population and cost billions of dollars each year in medical costs. By some estimates, over 13 million people worldwide suffer from chronic wounds yearly. The absence of continuous surveillance in conventional dressings for wounds causes prolongation in the treatment and raises the danger of infection. Timely and practical assessment of wounds is key to reducing infection and healing wounds. This is possible by smart dressings with sensors continuously providing input while monitoring important wound variables involving pH, temperature, and moisture. Considering current and upcoming advancements, this paper examines how intelligent patches could transform healing. Methodology: The latest advances in the development, usage of intelligent patches, and their development by different researchers are highlighted in this review. It looks at how sensors are incorporated into these patches and provides an overview of developing intelligent wound dressings by integrating one or more sensors triggered by endogenous and exogenous stimuli. Results and Discussion: The fabrication and effectiveness of intelligent dressings have advanced significantly, but there are still issues with sensor precision and resilience, especially regarding the requirement for strict regulations. The discussion also explores the critical need to address legal and technological constraints to enhance the usefulness of such wearable gadgets in medical settings. Conclusion: Intelligent patches, a fascinating new development in wound care, enable customized therapy with continuous surveillance. Future studies should address real-world challenges to fully realize their potential to refine wound recovery outcomes in medical care. Wearable computer ; Wound healing ; Wearable technology ; Computer science ; Human–computer interaction ; Medicine ; Embedded system ; Surgery Electrospun Nanofibers in Biomedical Applications ; Wound Healing and Treatments
Authors: Галина Ф. Махаева | Irina A. Utepova | Елена В. Рудакова | N. V. Kovaleva | Natalia P. Boltneva | Elena Yu. Zyryanova | Alexandra A. Musikhina | Vladimir F. Lazarev | Snezhana A. Vladimirova | Irina V. Guzhova | I.N. Ganebnykh | T. Yu. Astakhova | Elena N. Timokhina | Олег Н. Чупахин | Rudy J. Richardson
Source: Preprints.org (preprint, 2025-10-31)
Field: Chemistry — Organic Chemistry

1-Azinyl-1’-Alkenylferrocenes with Anticholinesterase, Antioxidant, and Antiaggregating Activities as Multifunctional Agents for Potential Treatment of Alzheimer’s Disease Background/Objectives: This study focused on synthesizing novel alkenyl derivatives of azinylferrocenes and evaluating their potential as Alzheimer’s disease (AD) therapeutics. Methods: 1-Azinyl-1’-acetylferrocenes were obtained by regioselective acetylation of azinylferrocenes, followed by the Wittig reaction or reduction of 1-azinyl-1’-acetylferrocenes and subsequent dehydration of the resulting alcohols. The synthesized compounds underwent the following biological activity testing relevant to AD: inhibition of acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and off-target carboxylesterase (CES); antioxidant capacity (ABTS and FRAP assays); inhibition of A42 self-aggregation (thioflavin method); blocking AChE-induced β-amyloid aggregation (propidium displacement); and cytotoxicity in SH-SY5Y and MSC-Neu cells (MTT assay). Results: Quinoline and bipyridine derivatives demonstrated effective cholinesterase inhibition, especially quinoline 7b (AChE IC₅₀ 3.32 μM; BChE IC₅₀ 3.68 μM), while acridine derivatives were poor inhibitors. Quantum chemical (QC) calculations predicted that acridine derivatives were especially prone to form stable dimers. Molecular docking into protein targets generated by an AlphaFold3 reproduction code showed that these dimers were too bulky to access enzyme active sites, yet they could bind to protein surfaces to inhibit A42 self-aggregation and displace propidium from the AChE peripheral site. All compounds showed high antioxidant activity in ABTS and FRAP assays, with quinoline derivatives being 2–4 times more potent than Trolox. QC calculations supported these findings. Quinoline and bipyridine derivatives also exhibited low cytotoxicity and scant CES inhibition. Conclusions: Overall, the synthesized ferrocenes, particularly the quinoline and bipyridine derivatives, appear promising for further research as multifunctional therapeutic agents targeting AD due to their anticholinesterase, antiaggregating, and antioxidant activities combined with low toxicity. Quinoline ; Butyrylcholinesterase ; Cytotoxicity ; Antioxidant ; Acetylcholinesterase ; Nerve agent ; Cholinesterase ; Trolox Ferrocene Chemistry and Applications ; Cholinesterase and Neurodegenerative Diseases ; Synthesis and Reactivity of Heterocycles
Authors: Hoang Cuong Phan | Minh Tien Tran | Chihun Lee | Hoheok Kim | Sehyeok Oh | Dong‐Kyu Kim | Ho Won Lee
Source: Advanced Engineering Informatics (article, 2025-11-20)
Field: Materials Science — Materials Chemistry

Parameter-aware high-fidelity microstructure generation using stable diffusion Microstructure ; Scalability ; Diffusion ; Segmentation ; Encoder ; Multiscale modeling ; Process (computing) ; Image processing ; Pattern recognition (psychology) Machine Learning in Materials Science ; Generative Adversarial Networks and Image Synthesis ; Block Copolymer Self-Assembly
Authors: Rajat Goel | Nir Goldman | Ambarish Kulkarni
Source: ChemRxiv (preprint, 2025-02-14)
Field: Materials Science — Materials Chemistry

Electronic and Geometric contributors to Hydrogen Binding in Uranium Oxide Grain Boundaries Hydrogen induced corrosion of uranium, which leads to the formation of toxic and pyrophoric \ce{UH3}, raises significant safety concerns for long-term storage of nuclear materials. Previous work suggests hydrogen diffuses through the top passivating oxide layer to initiate hydriding reactions within the underlying grain boundaries (GB). However, the atomistic mechanisms underlying this phenomenon and the structural factors that control its initiation are not well understood. To address this knowledge gap, here we use a high-throughput density function theory (DFT) workflow to investigate the adsorption of H and \ce{H2} in the defective bulk \ce{UO2}. Specifically, we exhaustively investigated the adsorption of H (107 sites) and \ce{H2} (26 sites) in three different coincidence site lattice (CSL) GBs: $\Sigma3$, $\Sigma5$, and $\Sigma9$. Compared to the binding energies in pristine \ce{UO2}, we observe significantly stronger hydrogen adsorption at these GB sites. Interestingly, we find that the trends in H and \ce{H2} adsorption vary considerably across the three GB models. In particular, while a small number of sites in $\Sigma5$ and $\Sigma9$ show exothermic adsorption of H and \ce{H2}, respectively, no such sites are found in $\Sigma3$. Further statistical analysis of these trends suggests that H adsorption, which is adsorbed as a hydride anion (i.e., \ce{H-}), is positively correlated with the value of its negative charge and depends on the number of neighboring oxygen and uranium atoms. Together, these results provide fundamental atomistic insights that could guide the development of future corrosion mitigation strategies for the storage of nuclear materials. Uranium ; Uranium oxide ; Hydrogen ; Grain boundary ; Oxide ; Materials science ; Metallurgy ; Physics ; Quantum mechanics Nuclear Materials and Properties ; Radioactive element chemistry and processing ; Nuclear reactor physics and engineering
Authors: Liang Xue | Shivani Tiwary | Mykola Bordyuh | Robert V. Stanton
Source: PROTEOMICS (article, 2025-06-30)
Field: Chemistry — Spectroscopy

CoSpred: Machine Learning Workflow to Predict Tandem Mass Spectrum in Proteomics In mass spectrometry-based proteomics, the use of deep learning algorithms can help improve the identification rates of peptides and proteins through the generation of high-fidelity theoretical spectrum which can be used as the basis of a more complete spectral library than those presently available, especially for unobserved protein/genetic variants. Here we focus on providing an end-to-end user-friendly machine learning workflow, which we call Complete Spectrum Predictor (CoSpred). Using CoSpred users can create their own machine learning compatible training dataset and then train a machine learning model to predict both backbone and non-backbone ions. For the model a transformer encoder architecture is used to predict the complete MS/MS spectrum from a given peptide sequence. In addition to the transformer model provided in the package, the code is built modularly to allow for alternate ML models to be easily "plugged in," allowing for spectrum prediction optimization given different experimental conditions. The CoSpred workflow (preprocessing→training→inference) provides a path for state-of-art ML capabilities to be more accessible to proteomics scientists. Computer science ; Workflow ; Artificial intelligence ; Preprocessor ; Machine learning ; Transformer ; Proteomics ; Chemistry ; Engineering ; Database Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Shuo Cao | Ao Wang | Zheyong Fan | Hua Bao | Ping Qian | Ye Su | Yu Yan
Source: ArXiv.org (preprint, 2025-05-19)
Field: Materials Science — Materials Chemistry

Lattice thermal conductivity of 16 elemental metals from molecular dynamics simulations with a unified neuroevolution potential Metals play a crucial role in heat management in electronic devices, such as integrated circuits, making it vital to understand heat transport in elementary metals and alloys. In this work, we systematically study phonon thermal transport in 16 metals using the efficient homogeneous nonequilibrium molecular dynamics (HNEMD) method and the recently developed unified neuroevolution potential version 1 (UNEP-v1) for 16 metals and their alloys. We compare our results with existing ones based on the Boltzmann transport equation (BTE) approach and find that our HNEMD results align well with BTE results obtained by considering phonon-phonon scattering only. By contrast, HNEMD results based on the conventional embedded-atom method potential show less satisfactory agreement with BTE ones. Given the high accuracy of the UNEP-v1 model demonstrated in various metal alloys, we anticipate that the HNEMD method combined with the UNEP-v1 model will be a promising tool for exploring phonon thermal transport properties in complex systems such as high-entropy alloys. Thermal conductivity ; Non-equilibrium thermodynamics ; Boltzmann equation ; Phonon ; Molecular dynamics ; Thermal ; Multiscale modeling ; Boltzmann constant Thermal properties of materials ; Machine Learning in Materials Science ; Thermal Expansion and Ionic Conductivity
Authors: Junlong Gao | Xiaobo Pang | Yulan Li
Source: International Journal of Nanomedicine (article, 2025-12-01)
Field: Materials Science — Materials Chemistry

Nanozymes Targeting Redox Imbalance: A Novel Weapon for Immunomodulation and Organ Protection in Sepsis Sepsis remains a major challenge in critical care, with high mortality despite ongoing improvements in treatment. The early uncontrolled burst of reactive oxygen and nitrogen species (RONS) and cytokine storms form a vicious cycle, ultimately leading to multiple organ dysfunction syndrome (MODS). The absence of effective therapies to interrupt this process is likely a key reason for poor outcomes. In recent years, the emergence of nanozymes has represented a transformative breakthrough in addressing this challenge. With strong antioxidant capacity, high stability, and low cost, nanozymes surpass conventional antioxidants and offer a promising therapeutic strategy for sepsis, especially through effective redox regulation. Nanozymes not only efficiently scavenge diverse RONS but also inhibit hyperactivated inflammatory pathways, thereby breaking the fatal vicious cycle between oxidative stress and cytokine storms. This provides a novel approach for immunomodulation and organ protection in sepsis. This review summarizes the key role of redox imbalance in sepsis progression and the therapeutic potential of nanozymes targeting redox imbalance, discusses their in vivo metabolic distribution and biosafety, and outlines prospects for future clinical translation and development. The objective is to provide insights that facilitate the development of innovative therapies targeting the RONS-inflammation axis in sepsis. Sepsis ; Oxidative stress ; Cytokine storm ; Bench to bedside ; Cytokine ; Inflammation ; Mediator ; Reactive oxygen species ; Review article Advanced Nanomaterials in Catalysis ; Nanoplatforms for cancer theranostics ; Nanoparticles: synthesis and applications
Authors: Muhammad Zahid Abbas | Muhammad Zahid Khan | Hafiz Muhammad Atif | Asim Shahzad | Jamaluddin Mahar
Source: Indus journal of bioscience research. (article, 2025-06-30)
Field: Chemistry — Organic Chemistry

Computer-Aided Analysis of Oxino-bis-Pyrazolederivative as a Potential Breast Cancer Drug Based on DFT, Molecular Docking, and Pharmacokinetic Studies: Compared with the Standard Drug Tamoxifen Breast cancer is the most often diagnosed and deadliest type of cancer in the world. Thiophene derivatives are available with various biological and pharmacological properties. In the current study, Computer assisted toxicity and pharmacokinetics prediction has been considered by pharmaceutical industries as an efficient way of choosing the potential drug. This study aimed at evaluating the in-silico pharmacokinetic properties (ADME) and toxicity and drug likeness of eight drugs. This work applies SwissADME, Pro Tox II, molinspirastion, and ADMETlab web applications and a quantum chemical investigation using density function theory (DFT) was utilized to explore the structural characteristics of thiophene derivatives, and the breast cancer inhibitory properties were revealed through molecular docking simulation. The optimization of the lead molecule was initially performed using DFT/B3LYP approach with a 6-31++(d,p) base set. The simulated electrostatic potential was performed to evaluate the reactivity of the lead molecule, and the molecular reactivity and stability were evaluated through HOMO-LUMO analysis based on energy gap, chemical potential (μ), electronegativity (χ), hardness (η), and softness (S) values. Then molecular docking research was used to assess the interaction of thiophene derivatives against the breast cancer target proteins, and pharmacokinetic evaluation was used to evaluate the drug-likeness property of the lead molecule. The leading molecules showed no violation against Lipinski’s rule, and the highest binding affinity was observed against HER-2 (PDB ID: 2IOK) with a docking score of -9.45Kcal/mol. Drug ; Pharmacokinetics ; Tamoxifen ; Breast cancer ; Docking (animal) ; Medicine ; Pharmacology ; Oncology ; Cancer ; Internal medicine Synthesis and biological activity ; Computational Drug Discovery Methods ; Estrogen and related hormone effects
Authors: Bachelor of Pharmacy | Asma Islam
Source:  (article, 2025-06-24)
Field: Chemistry — Analytical Chemistry

DEVELOPMENT AND VALIDATION OF A STABILITY-INDICATING HPLC METHOD FOR A WIDELY USED DRUG (E.G., METFORMIN, AMLODIPINE, OR ACETAMINOPHEN) UNDER ICH FORCED DEGRADATION CONDITIONS This study developed and statistically validated a stability-indicating high-performance liquid chromatography (HPLC) method for a widely used pharmaceutical drug under International Council for Harmonisation (ICH) forced degradation conditions. A quantitative, experimental, laboratory-based research design was applied to generate numerical evidence supporting method specificity, precision, accuracy, sensitivity, and robustness. Forced degradation was conducted under acidic, alkaline, oxidative, thermal, and photolytic stress environments to produce representative degradation profiles for analytical evaluation. The developed HPLC method achieved consistent separation between the intact drug and its degradation products across all stress conditions, confirming its stability-indicating capability. Descriptive analysis indicated stable analytical performance, with composite assay values demonstrating moderate-to-high consistency and acceptable dispersion. Reliability assessment showed strong internal consistency, with Cronbach’s alpha values ranging from 0.84 to 0.91 and composite reliability values between 0.85 and 0.92. Convergent validity was supported by average variance explained values exceeding 0.58 for all constructs, while discriminant validity was confirmed through factor-based measurement assessment. Correlation analysis revealed statistically significant positive associations among the core constructs, with correlation coefficients ranging from 0.54 to 0.62, remaining below thresholds associated with construct redundancy. Regression results demonstrated that analytics capability significantly predicted smart manufacturing integration (β = 0.55, p &lt; .001) and directly influenced supply chain resilience (β = 0.48, p &lt; .001). When manufacturing integration was included as a mediator, it showed a strong positive relationship with resilience (β = 0.43, p &lt; .001), and the analytics–resilience coefficient decreased to β = 0.24, indicating partial mediation. The explained variance in resilience increased from 36% to 49% with mediator inclusion. Collinearity diagnostics confirmed estimation stability, with variance inflation factors below 2.0. Overall, the findings provided robust quantitative evidence supporting the analytical validity and statistical reliability of the developed stability-indicating HPLC method for regulatory and quality control applications. Forced degradation ; Reliability (semiconductor) ; Degradation (telecommunications) ; Correlation coefficient ; Linear regression ; Resilience (materials science) ; Analysis of variance ; High-performance liquid chromatography ; Drug ; Quantitative analysis (chemistry) Analytical Methods in Pharmaceuticals ; Protein purification and stability ; Pesticide Residue Analysis and Safety