jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Mazhar Iqbal | Ernane de Freitas Martins | Nevena Todorova | Zhongheng Fu | Ivan Cole | Pablo Ordejón
Source: npj Materials Degradation (article, 2026-04-01)
Field: Materials Science — Materials Chemistry

Atomistic modeling of molecular interactions with copper oxides for corrosion inhibition Abstract A detailed understanding of the adsorption mechanism of organic corrosion inhibitors is essential, as these molecules must form film barriers on the metal surface to prevent corrosion-associated electrochemical reactions. In this regard, molecular modeling approaches can be valuable; however, the works reported in the literature to date use very simple models. This mini-review discusses the different kinds of copper surface models and theoretical methods used to simulate adsorbate-surface interactions. We focus on how authors have simulated an atmospheric corrosive medium − ambient containing moisture and pollutants, leading to a thin aqueous layer on the surface containing electrolyte ions such as chloride and others − to evaluate the realistic inhibitor’s adsorption mechanism. Finally, we discuss what kind of surface models and modeling approaches should be used to address two main aspects: a realistic description of adsorbate-surface interactions and the inhibitor’s adsorption mechanism under experimental corrosive conditions. Adsorption ; Copper ; Corrosion ; Erosion corrosion of copper water tubes ; Electrolyte ; Aqueous solution ; Metal ; Electrochemistry Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Copper-based nanomaterials and applications
Authors: Anusuyadevi Kathiresan | Uttam Gupta
Source: ChemistrySelect (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

Review on the Mechanistic Aspects of Fluorescence Based Sensing With Carbon Nanomaterials in the Detection of Potential Pollutant‐ Nitroaromatics ABSTRACT Nitroaromatics are a group of noxious compounds, and they are found to be potent contaminants in soil and water bodies. In addition, nitroaromatics have the capability to bioaccumulate that tend to cause ailments because of its carcinogenic and mutagenic nature. In consequence, designing sensors to trace the existence of nitroaromatics is pivotal. Here in this review, it is attempted to scrutinize the optical sensors for the detection of nitroaromatics in recent years and categorize those articles as per the mechanistic features of detection exhibited by the nanocarbon to elude redundancy. The review is concluded with perspectives on the scope for betterment of the sensor platform for efficient detection sequence. Nanomaterials ; Carbon quantum dots ; Carbon fibers ; TRACE (psycholinguistics) ; Fluorescence ; Optical sensing Carbon and Quantum Dots Applications ; Melamine detection and toxicity ; Biosensors and Analytical Detection
Authors: Guo-Ming Weng
Source: The Global Environmental Engineers (article, 2026-03-19)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Charged Viruses as Programmable Charge Carriers for Sustainable Batteries and Supercapacitors: A Perspective As the demand for sustainable energy storage increases, alternative concepts beyond conventional inorganic charge carriers are being explored. This Perspective proposes a conceptual framework in which genetically programmable viruses function as mobile charge carriers in batteries and supercapacitors. Unlike previous virus-templated electrode studies, the present work introduces the new concept of viruses operating within the electrolyte as tunable nanoscale charge transporters. The potential advantages, including charge programmability, biodegradability, and compatibility with circular material design, are discussed alongside key technical challenges such as mobility limitations, mass transport constraints, stability, and engineering feasibility. Environmental implications, including lifecycle considerations and biosafety aspects, are also analyzed. This work aims to outline a forward-looking research direction at the interface of synthetic biology and electrochemical energy storage. Charge carrier ; Charge (physics) ; Biosafety ; Work (physics) ; Compatibility (geochemistry) ; Function (biology) ; Energy carrier ; Energy storage Supercapacitor Materials and Fabrication ; Microbial Fuel Cells and Bioremediation ; Advancements in Battery Materials
Authors: Árpád I. Toldy | Prajwal Pisal | Ondřej Krejčí | Patrick Rinke | Annukka Santasalo-Aarnio
Source: Scientific Data (article, 2026-01-03)
Field: Materials Science — Materials Chemistry

TheMeCat: Dataset of Thermocatalytic Conversion of CO2 to Methanol Data-driven materials discovery to accelerate the development of new catalysts for the green transition shows great promise, but requires machine-interpretable experimental data. For this purpose, we compiled the TheMeCat dataset for the thermocatalytic conversion of CO<sub>2</sub> to methanol. TheMeCat is curated from experimental literature sources, and designed for hybrid computational and experimental catalyst workflows. The dataset captures key catalyst features, process parameters, and methanol conversion efficiencies. Upon detailed analysis of the generated dataset and the associated variability in reported values, we perform targeted error analysis to assess consistency and reinforce the need for clear, structured reporting. Methanol ; Catalysis ; Consistency (knowledge bases) ; Process (computing) ; Key (lock) Machine Learning in Materials Science ; CO2 Reduction Techniques and Catalysts ; Catalysis and Oxidation Reactions
Authors: Ngo T. Que | Vu Dinh Huan | Le Thanh Duy | Vu N. Bao | Vũ Lê Minh | Mai Xuan Trang | Anh D. Phan | Phạm Thành Huy
Source: RSC Advances (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

Composition-based machine learning for predicting and designing Mn <sup>4+</sup> -doped phosphors We present a data-driven approach to predict the excitation wavelength, emission wavelength, and crystal field energy levels (<sup>4</sup>T<sub>1</sub>, <sup>4</sup>T<sub>2</sub>) in Mn<sup>4+</sup>-doped phosphors based solely on elemental composition. For the first time, we construct the largest and most compherensive experimental dataset of Mn<sup>4+</sup>-activated phosphors to train and accurately predict the properties without relying on complex structural descriptors. Among several evaluated models, the K-Nearest Neighbors and Extra Trees Regressors achieved the highest accuracy for predicting excitation and emission wavelengths, respectively. Importantly, to evaluate generalization, we test these models on Eu<sup>3+</sup>-doped systems and achieve high predictive accuracy. An inverse design model is further developed to suggest candidate phosphor compositions for target optical outputs. By avoiding complex descriptors while preserving accuracy and interpretability, this work provides a foundation for theory-informed discovery of luminescent materials. Phosphor ; Excitation ; Construct (python library) ; Inverse ; Luminescence ; Field (mathematics) ; Energy (signal processing) Luminescence Properties of Advanced Materials ; Inorganic Chemistry and Materials ; Ammonia Synthesis and Nitrogen Reduction
Authors: Gamze Gündüz Meriç | Adife Şeyda Yargıç | Elif Yaman Çamlı
Source: Journal of Polytechnic (article, 2026-03-15)
Field: Materials Science — Materials Chemistry

Metal içerikli Katalizörler Varlığında Sodyum Bor Hidrürün Hidroliziyle Hidrojen Üretiminin İncelenmesi Fosil yakıtların neden olduğu sera gazlarının etkilerinin azaltılmasıyla sürdürülebilir bir dünya sağlamayı amaçlayan küresel anlaşmalar, hidrojen üretimi de dahil olmak üzere daha temiz, daha verimli ve yenilenebilir enerji kaynakları için araştırmaları teşvik etmektedir. Hidrojen, düşük karbonlu teknolojilerin yayılmasına güçlü bir şekilde katkıda bulunabileceği ve enerji güvenliğini sağlayabileceği için sıfır emisyona doğru uzun vadeli bir çözüm olarak kabul edilmektedir. Bu çalışma, sodyum bor hidrürün (NaBH4) hidrolizi yöntemiyle hidrojen üretimine odaklanan yayınların kapsamlı bir analizini içermektedir. NaBH4’ün hidroliz süreci kendi başına çok yavaştır, ancak birçok metal esaslı katalizör (örn. Ru, Co, vb.) hidroliz süreci sırasında mükemmel katalitik aktivite göstermektedir. Yapılan bu derleme çalışmasında NaBH4’ün hidroliz reaksiyonunu etkileyen katalizör türleri ve reaksiyon parametreleri özetlenmiştir. Literatür çalışmalarından elde edilen sonuçlara göre, metal dispersiyonunun daha iyi olabilmesi için katalizör destek malzemesinin kullanılması tavsiye edilmektedir. Katalizör destek malzemeleri ayrıca katalizör maliyetini de düşürmektedir. Destek üzerine bi-metalik katkı yapıldığında ise metallerin sinerjik etkisi dolayısıyla aktivasyon enerjilerinin düştüğü ve hidrojen üretim hızının arttığı görülmüştür. NaBH4’ün suda sınırlı çözünürlüğü nedeniyle katalizörsüz hidroliz reaksiyonlarında H2 üretim hızı nispeten zayıf olduğundan katalizör miktarı ve yüklenen metal oranı arttıkça, hidrojen üretim hızı genellikle parabolik olarak artmaktadır. Reaksiyon ortamındaki NaBH4 konsantrasyonu arttıkça, hidrojen üretim hızı parabolik olarak artmaktadır. Ancak, yüksek NaBH4 konsantrasyonlarında katalizör yüzeyinde biriken NaBO2 sebebiyle hızda azalış meydana gelmektedir. Bu sebeple her sistem için reaksiyon parametreleri optimize edilmelidir. Metal ; Image contrast ; Naxi Hydrogen Storage and Materials
Authors: Fujiang Zhang | Huaijiang Yu | Xia Han | Xiaodong Xie | Yì Wáng | Yu Liu | Li Xu | Bude Su | Jinhua Tan | Ying Zhang
Source: Arabian Journal of Chemistry (article, 2026-03-04)
Field: Materials Science — Materials Chemistry

Green synthesis of gold-silver nanoparticles using plant extracts and their modulatory effects on the metabolism of human gut symbiont <i>Lactobacillus</i> This study explores the biosynthesis of bimetallic nanoparticles using Camellia sinensis extract and their effects on the gut symbiont Lactobacillus gasseri . Ag/Au nanoparticles (NPs) with Ag:Au molar ratios of 4:1, 1:1, and 1:4 were characterized by uniform alloyed morphology, crystalline (111) planes, and particle sizes of 18.5–32.8 nm. Antibacterial assays revealed that Ag:Au molar ratios of 4:1 reduced L. gasseri growth by 92% and caused a 2.9-fold increase in malondialdehyde and a 46% decrease in glutathione, indicating pronounced oxidative stress. Metabolomic profiling showed significantly suppressed key metabolic products. Short-chain fatty acid (SCFA) analysis revealed a 73.4% drop in butyrate, accompanied by a 2.8-fold rise in extracellular lipopolysaccharides (LPS), indicating increased inflammatory potential. Microbial community analysis via 16S rDNA sequencing demonstrated that decreased Shannon diversity from 3.45 to 2.11 and reduced Lactobacillus abundance from 42.3% to 11.4%, while Escherichia and Streptococcus populations expanded. In contrast, Ag/Au nanoparticles with Ag:Au molar ratios of 1:4 caused minimal shifts in both microbial composition and function. These findings demonstrate that the Ag content critically determines nanoparticle-microbiota interactions, with silver-rich formulations disrupting metabolic activity, ecological balance, and redox homeostasis. Gold-rich nanoparticles NPs, by contrast, exhibit superior compatibility with probiotic taxa and preserve gut-relevant metabolic functions. This highlights the potential of green-synthesized, Au-dominant nanomaterials in microbiome-preserving biomedical and nutritional applications. Nanoparticle ; Bacteria ; Metabolism ; Molar ratio ; Nanomaterials ; Malondialdehyde ; Biosynthesis ; Metabolic pathway ; Gut flora Nanoparticles: synthesis and applications ; Gold and Silver Nanoparticles Synthesis and Applications ; Tea Polyphenols and Effects
Authors: Savan K Raj | Prem P. Sharma | Dominika Bury | Agnieszka Jastrzębska | Vaibhav Kulshrestha
Source: RSC Sustainability (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

Application of MXenes for emerging contaminant removal and water purification: a revolutionary approach Emerging water contaminants, including dyes, heavy metals, pharmaceuticals, per- and poly-fluoroalkyl substances (PFAS), and micro- and nano-plastics, pose critical challenges for environmental sustainability and human health. MXenes ; Sustainability ; Water pollution ; Water supply ; Water treatment ; Human health MXene and MAX Phase Materials ; Membrane Separation Technologies ; Ammonia Synthesis and Nitrogen Reduction
Authors: Xiaohui Yuan | Yalong Liang | Bang Lu | Gaochao Zhao | Pei Li
Source: Materials (article, 2026-02-28)
Field: Materials Science — Materials Chemistry

Interpretable Machine Learning with Prediction Uncertainty Quantification for d33 in (K0.5Na0.5) NbO3-Based Lead-Free Piezoelectric Ceramics The accelerated discovery of high-performance lead-free piezoelectric ceramics is hindered by the vast compositional space and the limited interpretability of conventional machine learning (ML) models. Here, we propose a physics-informed and interpretable ML framework with integrated uncertainty quantification to predict and understand the piezoelectric coefficient <i>d</i><sub>33</sub> of (K<sub>0.5</sub>Na<sub>0.5</sub>) NbO<sub>3</sub> (KNN)-based ceramics. A curated dataset of 1113 experimental samples is used to construct 65 descriptors by decoupling A-site and B-site ionic contributions. Pearson correlation analysis reduces these to an optimized 11-dimensional feature set for training deep neural networks, Wide & Deep networks, and residual networks. A Bayesian neural network further provides predictive uncertainty, which quantitatively reflects the confidence of machine-learning-based <i>d</i><sub>33</sub> predictions rather than experimental measurement uncertainty. To achieve physical interpretability, SHapley Additive exPlanations (SHAP) are combined with the Sure Independence Screening and Sparsifying Operator (SISSO) to derive a compact analytical descriptor revealing that sintering temperature, B-site electronic anisotropy, and A-site ionic displacement jointly govern <i>d</i><sub>33</sub>. The proposed framework achieves high accuracy (R<sup>2</sup> ≈ 0.81) while offering transparent design rules for next-generation lead-free piezoelectrics. Interpretability ; Uncertainty quantification ; Artificial neural network ; Support vector machine ; Bayesian probability ; Piezoelectricity ; Correlation coefficient ; Residual ; Pattern recognition (psychology) Machine Learning in Materials Science ; Ferroelectric and Piezoelectric Materials ; Advanced Sensor and Energy Harvesting Materials
Authors: Jordan De Jesus Silva | Scott R. Docherty | Jasper Clarysse | Maksym Yarema | Vanessa Wood | Christophe Copéret
Source: Helvetica Chimica Acta (article, 2026-02-16)
Field: Materials Science — Materials Chemistry

Mapping Alkyne Chemical Space—Classifying the Reactivity of Alkynes in Semihydrogenation and beyond Using a Data Science Framework ABSTRACT A data science framework that integrates DFT featurization, dimensionality reduction, and hierarchical clustering is employed to study the chemical space of commercially available alkynes, highlighting the differentiation of over 2700 structures into 6 subsets. Referencing the substrate scope of a recent publication, the selected molecules are shown to be representative of the alkyne chemical space by covering each of the 6 clusters. Logistic regression classification allows the categorization of the tested alkynes according to their propensity to hydrogenate under milder or harsher reaction conditions. This categorization identified highly chemically shielded alkynes with low total dipole as the easiest to hydrogenate, likely by breaking the cylindrical symmetry of the alkyne. In summary, we identify potential reasons for the difference in reactivity of alkyne substrates in Ni 3 Zn nanocrystal catalyzed semi‐hydrogenation and present a useful workflow and alkyne data set for studying catalytic reactions in general. Alkyne ; Chemical space ; Curse of dimensionality ; Categorization ; Workflow ; Reactivity (psychology) ; Data set ; Cheminformatics ; Set (abstract data type) Machine Learning in Materials Science ; Asymmetric Hydrogenation and Catalysis ; Catalysis and Oxidation Reactions
Authors: Fan Xue | Liang Chen | Xindong Zhu | Jianrong Zeng | He Zhu | Si Lan
Source: Rare Metals (article, 2026-01-21)
Field: Materials Science — Materials Chemistry

Optimizing the Surface Coordination of Pd‐Cu Nanoalloy Through Chemical Ordering to Enhance Hydrogenation Selectivity ABSTRACT Precise control of chemical ordering in bimetallic nanocatalysts offers a route to decouple activity and selectivity in acetylene hydrogenation, but direct atomic‐scale evidence linking surface order to catalytic performance is scarce. Here, we tune Pd‐Cu nanoalloys from chemically disordered to highly ordered states by composition control and targeted H 2 thermal treatment. Under near‐industrial conditions, all catalysts reach full acetylene conversion between 100°C and 120°C, whereas the ethylene selectivity enhances with the chemical ordering increasing. By combining synchrotron X‐ray absorption fine structure (XAFS) with X‐ray total scattering and reverse Monte Carlo (RMC) simulation, three‐dimensional atomic models are reconstructed to quantitatively map surface coordination. Compared with the chemically disordered Pd‐Cu nanocatalyst, the highly ordered PdCu shows an increase in average surface Pd‐Cu coordination and an expansion of mean surface Pd‐Pd separations. These structural features weaken ethylene binding and suppress re‐adsorption, rationalizing the enhanced selectivity. Our study provides direct atomic‐scale evidence connecting chemical order to catalytic selectivity and opens the way for guiding the precise design of bimetal nanocatalysts. Bimetallic strip ; Bimetal ; Selectivity ; Nanomaterial-based catalyst ; Acetylene ; Catalysis ; Ethylene Catalytic Processes in Materials Science ; Catalysis for Biomass Conversion ; Advanced Chemical Physics Studies
Authors: Assyl Boshkayeva | Abay Massakbayev | Galiya Sayakova | Serzhan Mombekov | Rustam Yussupov | Tanagul Arystanova | Aigul Tazhiyeva | Galiya Ibadullayeva | Nazym Pushkarskaya | Meruyert I. Tleubayeva | Gulbarshyn Aitzhanova | Farida Kayupova | Kaldanay Kozhanova
Source: Journal Of Advanced Pharmacy Education And Research (article, 2026-01-01)
Field: Chemistry — Organic Chemistry

Exploring the frontiers of penicillin pharmaceuticals: a comprehensive review of advancements and innovations Penicillin and its derivatives have remained a cornerstone in combating bacterial infections for decades. However, growing concerns about bacterial resistance and the limitations of conventional penicillin production methods underscore the need for innovative approaches. The aim of this review is to address the challenge of developing penicillin and related compounds by proposing a novel approach to improving the quality of medicines to meet healthcare demand. The discovery and optimization of m Penicillin ; Antibiotic resistance ; Quality (philosophy) ; Penicillin resistance ; Cornerstone Synthesis of β-Lactam Compounds ; Antimicrobial agents and applications ; Historical Medical Research and Treatments
Authors: H. Y. Chen | Jingying Tan | Qing Li | Lei Han
Source: ChemRxiv (article, 2026-04-07)
Field: Materials Science — Materials Chemistry

Cryogenic Synthesis of Metal-Organic Framework Nanozymes with Enhanced Activity and Specific Recognition Capability Conventional metal-organic framework (MOF) synthesis typically relies on energy-intensive processes. Here, we establish a cryogenic synthesis strategy that operates at sub-zero temperatures to produce MOFs with unique catalytic and morphological properties. This approach not only simplifies the synthesis process and eliminates the need for high-temperature, high-safety equipment, but also successfully synthesizes cerium-based MOF (Ce-MOF) with single peroxidase (POD)-like activity. Compared to conventional heating methods, the cryogenic synthesis retains similar structural characteristics while imparting unique properties to Ce-MOFs. As the cryogenic synthesis temperature gradually decreases, the rod-like size of Ce-MOFs is significantly reduced. Furthermore, the extension of the freezing time promotes splitting and longitudinal growth, leading to the formation of the well-defined rodshaped Ce-MOF. Ce-MOF synthesized by heating exhibit minimal POD-like activity, whereas cryogenic synthesis produces Ce-MOFs with a more than 58-fold enhancement in specific activity, which increases as the synthesis temperature decreases, accompanied by improved sensitivity toward pyrithiobac-sodium (PTB). Notably, the Ce-MOF lacks oxidase-like activity, thus avoiding oxygen interference in colorimetric detection. Moreover, the white color, single-activity and specific PTB recognition of Ce-MOF enable the development of portable PTB test swabs with high sensitivity, selectivity, and O2 tolerance. The cryogenic synthesis technology also exhibits a certain degree of universality in the preparation of other MOF nanomaterials. This work establishes an unconventional low-temperature synthesis strategy for MOF-based nanomaterials with promising applications. Nanomaterials ; Catalysis ; Cryogenic temperature ; Process (computing) Advanced Nanomaterials in Catalysis ; Metal-Organic Frameworks: Synthesis and Applications ; Nanocluster Synthesis and Applications
Authors: Sungryong Kim | Jin Han Kwon | Juyoung Kang | Hong Chul Moon
Source: Advanced Materials (article, 2026-02-06)
Field: Materials Science — Materials Chemistry

Functional Polymers for Ionic Thermoelectrics: Multiscale Design Strategies for Ion Dynamics, Mechanics, and Energy Harvesting The efficient conversion of dissipated heat into useful electrical energy has emerged as a promising approach for sustainable energy technologies. Ionic thermoelectrics (iTEs) are particularly attractive because they generate substantial thermo-voltages, effectively harvest low-grade heat, and offer advantages such as cost-effectiveness, easy scalability, and remarkable performance. Unlike liquid-state platforms, quasi-solid-state iTEs exhibit properties that are critically governed by the polymer matrix and polymer-ion interactions, which are closely related to the overall device performance. Consequently, the use of functional polymers effectively improves the characteristics and performance of quasi-solid-state iTEs. Therefore, this paper highlights the impact of the polymer matrix on performance and mechanical properties in iTEs from molecular-, micro-, to macro-scale engineering. Particular emphasis is placed on clarifying the role of polymers at various scales to provide an in-depth understanding of performance enhancement. Furthermore, the current challenges and prospective research directions are discussed, offering guidance toward the development of next-generation iTE-based energy harvesting platforms. Energy harvesting ; Ionic bonding ; Polymer ; Thermoelectric effect ; Ion ; Thermoelectric materials ; Matrix (chemical analysis) ; Energy transformation ; Current (fluid) Advanced Thermoelectric Materials and Devices ; Dielectric materials and actuators ; Advanced Sensor and Energy Harvesting Materials