jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Mohamed Abdelkader Hafiene | Hatem Ksibi
Source: Fine Chemical Engineering (article, 2025-09-22)
Field: Chemistry — Organic Chemistry

Solubility-Driven Phenol Extraction from Olive Tree Derivatives in Ethanol/Methanol: Empirical, UNIFAC &amp; ML Models This study investigates the solubility behavior and predictive modeling of six key phenolic compounds derived from olive sources—hydroxytyrosol, luteolin, oleuropein, rutin, quercetin, and verbascoside—in methanol, ethanol, and their binary mixtures (10 : 90, 50 : 50, and 90 : 10 v/v) at temperatures ranging from 20 °C to 50 °C. Experimental solubility data were compiled from previously published literature. These results showed a wide solubility range: oleuropein exhibited the highest solubility (~ 100 mg/100 g in methanol at 50 °C), followed by hydroxytyrosol (~ 78 mg/100 g), verbascoside (~ 45 mg/100 g), rutin (~ 35 mg/100 g), quercetin (~ 5 mg/100 g), and luteolin (~ 3 mg/100 g). Solubility generally increased with temperature and ethanol content, though compound-specific effects were observed. Empirical modeling using the Apelblat equation demonstrated strong agreement with experimental data (R2 &gt; 0.98; Mean Absolute Error (MAE) &lt; 5%) across all compounds. Predictive models were also developed using both the Universal Functional Activity Coefficient (UNIFAC) thermodynamic method and Machine Learning (ML) algorithms (eXtreme Gradient Boosting (XGBoost)), Random Forest (RF). While UNIFAC captured general solubility trends (R2 ≈ 0.75), it was limited by its group contribution assumptions and lack of interaction-specific parameters. In contrast, the ML models achieved higher accuracy (R2 &gt; 0.95; Root Mean Square Error (RMSE) &lt; 3.2 mg/100 g), particularly for highly soluble compounds such as oleuropein and hydroxytyrosol. Minor deviations (R2 ≈ 0.93) were observed for quercetin and luteolin due to their lower solubility and narrower data range. Pearson correlation analysis highlighted solvent composition as the dominant factor influencing solubility, with coefficients exceeding 0.90 for most compounds. Finally, the predictive insights were validated against experimental extraction efficiencies, confirming that solubility-optimized conditions (e.g., high methanol content at 50 °C) led to a 20-35% improvement in phenol recovery, demonstrating the practical relevance of this integrated analytical-modeling approach for the design of efficient extraction processes. Solubility ; UNIFAC ; Hydroxytyrosol ; Chemometrics ; Solvent ; Activity coefficient ; Extraction (chemistry) ; Oleuropein Edible Oils Quality and Analysis
Authors: Jiansong Han | Erna Jia | Yuan Gao | Bin Liu | Kelong Fan | Min Luo
Source: Nano Research (article, 2025-09-03)
Field: Materials Science — Materials Chemistry

Design of a CuFe metal–organic framework nanozyme to enhance radiotherapy efficacy via mitochondrial oxidative stress amplification and induction of ferroptosis and cuproptosis Despite advances in radiotherapy (RT), complete tumor eradication remains a clinical challenge, largely due to the insufficient activation of non-apoptotic cell death pathways such as ferroptosis and cuproptosis. To address this, we developed a bimetallic nanozyme, CuFe-MOF-TPP, comprising a CuFe-based metal–organic framework conjugated with triphenylphosphine to enhance RT sensitivity through provoking cuproptosis and ferroptosis. CuFe-MOF-TPP targeted to mitochondria, destroying redox balance by peroxidase-, oxidase-, and glutathione oxidase-like activities. These catalytic functions promoted excessive reactive oxygen species generation and glutathione depletion, leading to oxidative stress in mitochondria. This redox imbalance triggered the generation of ferrous ions, which accelerated lipid peroxidation and subsequently augmented ferroptosis. Concurrently, cuproptosis was promoted through copper ions-mediated aggregation of dihydrolipoamide S-acetyltransferase. Notably, the combination of CuFe-MOF-TPP and RT result in potent tumor suppression via the coordinated delivery of metal ions and spatiotemporally regulated catalytic activity. This strategy offers a promising approach for overcoming radioresistance by synergistically amplifying mitochondrial oxidative stress and activating ferroptosis and cuproptosis, with significant translational potential for clinical cancer therapy. Oxidative stress ; Reactive oxygen species ; Stress (linguistics) ; Mitochondrion ; Metal ; Oxidative phosphorylation ; Chemistry ; Materials science ; Cancer research ; Medicine ; Biochemistry ; Metallurgy Advanced Nanomaterials in Catalysis ; Metal-Organic Frameworks: Synthesis and Applications ; MicroRNA in disease regulation
Authors: Diana Kovaleva | Yue Xin | Mohammad Firoz Khan | Yanni K.‐Y. Chin | Anna Roujeinikova
Source: Crystals (article, 2025-06-06)
Field: Materials Science — Materials Chemistry

Isolation and Preliminary X-Ray Crystallographic Characterisation of the Periplasmic Ligand-Binding Domain of the Chemoreceptor Tlp3 from Campylobacter hepaticus The Campylobacter genus includes many pathogenic species, with Campylobacter hepaticus primarily implicated in spotty liver disease in poultry. Chemotaxis is one of the well-established mechanisms of pathogenesis of Campylobacter. The chemoreceptor Tlp3, previously studied in C. jejuni, mediates responses to diverse ligands. Differences between the ligand-binding pockets of Tlp3s in C. hepaticus and C. jejuni may influence ligand specificity and niche adaptation. Here, we report a method for production of the ligand-binding domain of C. hepaticus Tlp3 (Ch Tlp3-LBD) in Escherichia coli inclusion bodies that yields crystallisable protein. Size-exclusion chromatography analysis showed Ch Tlp3-LBD is a monomer in solution. Ch Tlp3-LBD was crystallised using PEG 6000 and LiCl as the precipitants. The crystal lattice symmetry was P2221, with unit cell geometry of a = 82.0, b = 137.7, c = 56.1 Å, and α = β = γ = 90°. X-ray diffraction data have been acquired to 1.6 Å resolution using synchrotron radiation. Estimation of the Matthews coefficient (VM = 2.8 Å3 Da−1) and the outcome of molecular replacement suggested the asymmetric unit is composed of two protein molecules. This work lays the foundation for studies towards understanding the structural basis of ligand recognition by C. hepaticus Tlp3 and its role in pathogenesis. Periplasmic space ; Campylobacter ; Ligand (biochemistry) ; Isolation (microbiology) ; Domain (mathematical analysis) ; Chemoreceptor ; Crystallography ; Chemistry ; Biology ; Microbiology ; Receptor ; Biochemistry ; Bacteria ; Genetics ; Escherichia coli Enzyme Structure and Function ; Photosynthetic Processes and Mechanisms ; Endoplasmic Reticulum Stress and Disease
Authors: Yitao He | Dan Zhao
Source: arXiv (Cornell University) (preprint, 2025-01-10)
Field: Chemistry — Physical and Theoretical Chemistry

Modeling Concentration Profiles in Electrolytes by Solving 3-D Poisson-Nernst-Planck Equations via Finite Difference Method The Poisson-Nernst-Planck (PNP) equations are fundamental for modeling ion transport in electrochemical systems, capturing the intricate interplay of concentration gradients, electric fields, and ion fluxes essential for applications such as energy storage devices and other electrochemical devices. This study introduces a refined numerical framework employing the finite difference method to solve the 3-D PNP equations, enabling precise simulation of ion concentration distributions under realistic boundary conditions and applied electric fields. By rigorously addressing stability criteria and integrating advanced boundary constraints, including the Butler-Volmer equation for surface reactions, the model provides comprehensive insights into ion dynamics, particularly near electrode surfaces where electric field and reaction effects dominate. This framework significantly enhances traditional PNP modeling by accommodating varied boundary conditions, diffusion anisotropy, and complex electrochemical environments, offering a robust tool for investigating electrochemical processes and guiding the design of advanced electrochemical systems. Nernst equation ; Planck ; Poisson distribution ; Electrolyte ; Physics ; Applied mathematics ; Mathematics ; Statistics ; Quantum mechanics ; Electrode Electrostatics and Colloid Interactions
Authors: Amir Hajibabaei | William J. Baldwin | Gábor Cśanyi | Stephen J. Cox
Source: Physical Review Letters (article, 2025-01-17)
Field: Materials Science — Materials Chemistry

Symmetry Breaking in the Superionic Phase of Silver Iodide In the superionic phase of silver iodide, we observe a distorted tetragonal structure characterized by symmetry breaking in the cation distribution. This phase competes with the well known bcc phase with a symmetric cation distribution, at an energetic cost of only a few meV/atom. The small energy difference suggests that these competing structures may both be thermally accessible near the superionic transition temperature. We also find that the distribution of silver ions depends on the low-temperature parent polymorph, with memory persisting in the superionic phase on the nanosecond timescales accessible in our simulations. Furthermore, simulations on the order of 100 ns reveal that even at temperatures where the bcc phase is stable, significant fluctuations toward the tetragonal lattice structure remain. Our results are consistent with many "anomalous" experimental observations and offer a molecular mechanism for the "memory effect" in silver iodide. Tetragonal crystal system ; Silver iodide ; Iodide ; Ion ; Phase transition ; Lattice (music) ; Condensed matter physics ; Chemical physics ; Materials science ; Phase (matter) ; Atom (system on chip) ; Nanosecond ; Molecular dynamics ; Physics ; Chemistry ; Nanotechnology ; Inorganic chemistry ; Quantum mechanics ; Silver halide Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides ; Quantum Dots Synthesis And Properties
Authors: Xiangnian Ou | Yueqiang Hu | Dian Yu | Shu‐Lin Liu | Shaozhen Lou | Zhiwen Shu | Wenzhi Wei | Man Liu | Jianxiong Li | Tianhai Chang | Na Liu | Huigao Duan
Source: Nature Communications (article, 2025-12-08)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Meta-optics redefines microdisplay: monolithic color LCoS without polarization dependency Liquid crystal on silicon (LCoS) panels are pivotal to high-resolution optical projection and imaging displays, yet their inherent polarization sensitivity and reliance on multi-chip architectures for color reproduction constrain the upper limit of light utilization, increase system complexity and restrict broader applicability. Here, we demonstrate a monolithic color meta-LCoS prototype that integrates dual-layer metasurfaces to achieve polarization-insensitive, full-color amplitude modulation on a single chip. Polarization sensitivity is eliminated via a synergistic design combining metasurface-enabled polarization conversion and voltage-controlled liquid crystal phase modulation, achieving a high-contrast, polarization-insensitive optical switch. By embedding red, green, and blue metasurface subpixels and meticulously designed off-axis angles, enabling direct color synthesis through a unified device. We showcase a 64-pixel monochrome and a 9-pixel color prototype capable of dynamically projecting diverse patterns under unpolarized illumination. Fully compatible with existing LCoS fabrication processes, our device significantly reduces system complexity and cost, offering transformative applications in next-generation projectors and AR/VR displays. Liquid crystal on silicon ; Polarization (electrochemistry) ; Embedding ; Fabrication ; Polarizer ; Liquid crystal ; Monochrome ; Phase modulation ; Modulation (music) Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Advanced Wireless Communication Technologies
Authors: Jie Rong Soh | Mun Kou Lai | Tze Chuen Yap
Source: Advances in Polymer Technology (article, 2025-01-01)
Field: Materials Science — Polymers and Plastics

Development and Feasibility of In Situ Coconut Fibre‐Reinforced PLA via MEX‐TRB/P This study aims to evaluate the feasibility of embedding coconut fibre (CF) as reinforcement into polylactic acid (PLA) for the fabrication of bio‐composites using material extrusion‐thermal reaction bonding of polymer (MEX‐TRB/P) 3D printing. Traditional natural fibre‐reinforced composites rely on premixed filaments or other additive manufacturing (AM) techniques, which limit control over fibre placement and distribution. As sustainability becomes an increasingly important focus in materials engineering, natural fibres and biodegradable polymers like PLA present a promising path toward eco‐friendly manufacturing. However, no standardised method exists to manually integrate fibres onto polymer during MEX‐TRB/P 3D printing. In this project, CFs were chemically treated using sodium hydroxide (NaOH) to remove surface impurities to improve fibre‐matrix adhesion. The treated fibres were then oven‐dried and embedded into the PLA matrix during the MEX‐TRB/P 3D printing process via a new fabrication approach, where the print was paused at specific layers to insert fibre strands between layers of molten PLA. Each strand has four fibres, and the strands were placed perpendicular to the direction of the impact force. Five composite types were fabricated, which are neat PLA, 1‐layer untreated, 3‐layer untreated, 1‐layer treated and 3‐layer treated bio‐composites. Impact strengths of the composites were determined using the Izod impact test. The results showed a significant increase in impact resistance with the inclusion of fibres. Compared to neat PLA (9.75 J/m), untreated 1‐layer and 3‐layer composites recorded 12.34 and 14.72 J/m, which showed a 26.6% and 51.0% increase compared to neat samples, respectively. Meanwhile, treated 1‐layer and 3‐layer composites reached 13.66 and 14.99 J/m, showing a 40.1% and 53.7% increase compared to neat samples, respectively. Fracture analysis confirmed ductile failure with strong fibre‐matrix adhesion, especially in treated samples. This study introduces the first reported method of embedding CFs directly into an MEX‐TRB/P 3D‐printed PLA composite. The results demonstrate the potential of this newly proposed method to produce strong and sustainable composites. Polylactic acid ; Polymer ; Fabrication ; Composite number ; Fiber ; Izod impact strength test ; Sodium hydroxide ; Perpendicular Natural Fiber Reinforced Composites ; Additive Manufacturing and 3D Printing Technologies ; Fiber-reinforced polymer composites
Authors: Yang Cai | Xiao-Lei Cui | Chunhuan Guo | Fengchun Jiang | Piaoping Yang
Source: Materials (article, 2025-04-29)
Field: Materials Science — Materials Chemistry

Mechanical Properties of Aluminum Alloy Tubes Fabricated Through Surface Mechanical Grinding Treatment and Graphene Lubrication Under Biaxial Stress States To enhance the mechanical properties of 6063-T4 aluminum alloy tubes, surface mechanical grinding treatment was conducted under graphene-assisted lubrication. The effects of rotational speed and cooling conditions on the mechanical properties of aluminum alloy tubes under biaxial stress were systematically explored. It was found that increasing the rotational speed and cooling rate facilitates the formation of finer lamellar grains, higher-density nano-precipitates, and a reduced dislocation density on the tube surface. These microstructural characteristics significantly contribute to an increased yield strength and sustained strain hardening capacity during bulging deformation. This study proposes an innovative approach for improving the strength and toughness of light alloy components during integral forming, providing meaningful insights for future engineering applications. Materials science ; Alloy ; Lubrication ; Composite material ; Grinding ; Toughness ; Metallurgy ; Deformation (meteorology) ; Strain hardening exponent ; Aluminium Microstructure and mechanical properties ; Aluminum Alloys Composites Properties ; Surface Treatment and Residual Stress
Authors: He Zhu | Xinyue Xing | Xiaoman Yao | Mfoniso Udofa | Xiaoqi Wu | Otobong Donald Akan | Yanxia Xing | Mei Yu | B. Li | Lizeng Peng | Mengliu Zhu
Source: Journal of Food Processing and Preservation (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

Spectroscopy Analysis of Prickly Ash Samples From Different Regions: A Food Fingerprint Study Background: Fingerprinting Chinese red prickly ash ( Zanthoxylum bungeanum or Dahongpao) samples helped establish baseline qualities and components. These data will provide valuable insights into determining the extent to which cultivation practices and locations may affect a plant’s output, providing insight into maximizing its agricultural potential and ensuring consistent quality. Methods: In this paper, we evaluated prickly ash samples from eight regions, all in the Shandong, Sichuan, Shaanxi, and Gansu provinces, using Fourier‐transform infrared spectroscopy (FTIR) technologies. Gas chromatography–mass spectrometry (GC‐MS) was used to analyze the volatile components from prickly ash extract and powder samples, and they were compared with the NIST database. Results: Data from sample analysis yielded 91 volatile flavour components. Lastly, 14 compounds were identified as fingerprints with harvest site bias based on the GC‐MS data, principal component analysis (PCA), hierarchical cluster analysis (HCA), and orthogonal partial least squares discriminant analysis (OPLS‐DA) models. Conclusion: Data from this comprehensive analysis contributes to the growing body of knowledge regarding the quality of prickly ash samples. Our findings underscore the critical role that cultivation practices play in the quality of plants—which could influence both traditional medical and modern culinary art usages. Fingerprint (computing) ; Food science ; Chemistry ; Spectroscopy ; Computer science ; Artificial intelligence ; Physics Heavy Metals in Plants ; Isotope Analysis in Ecology ; Spectroscopy and Chemometric Analyses
Authors: Huagui Huang | Qiwei Hu | Biao Xu | Jiali Zheng | Shimin Xu | Xinyi Ren
Source: Chinese Journal of Mechanical Engineering (article, 2025-09-12)
Field: Materials Science — Materials Chemistry

Machine Vision and Deep Learning for Enhanced Grading and Classification of Surface Wear on Hot-Rolling Work Rolls Abstract The wear of work rolls significantly affects the production efficiency and product quality. However, existing methods for wear assessment fail to effectively quantify work roll surface wear conditions, thereby affecting the quality control of steel strips and maintenance strategies for rolls. To accurately assess the wear conditions of hot-rolling work rolls, this study initially established an apparatus for capturing high-precision roll surfaces images. Subsequently, a quantitative assessment of common surface wear morphologies was conducted, and a hot-rolling work roll surface wear dataset was constructed. The MobileNetV2 convolutional neural network (CNN), augmented by transfer learning, was employed to develop a MobileNetV2-wear detection and classification (WDC) surface wear grading model. A comparison with mainstream CNN models revealed that the MobileNetV2-WDC model achieved high-speed (21.92 ms) and accurate (96.86%) grading with minimal model parameters (2.27 M) and size (27 M), meeting the industrial efficiency and practicality requirements. A visual analysis of the model classification errors was conducted, outlining paths for further optimization. This study provides an efficient and accurate solution for detecting and grading surface wear on hot-rolling work rolls, enhancing product quality and extending the lifespan of rolls. Convolutional neural network ; Grading (engineering) ; Artificial neural network ; Deep learning ; Work (physics) ; Transfer of learning Metal Alloys Wear and Properties ; Lubricants and Their Additives ; Erosion and Abrasive Machining
Authors: Sebastian Kricke | C. Drechsel | Carolin Schmidt | Susann Zahn | Harald Rohm | Jens‐Peter Majschak | H. Köhler
Source: Heat and Mass Transfer (article, 2025-08-16)
Field: Chemistry — Analytical Chemistry

Analysis of complex interdependencies between soil-specific properties and cleaning behavior in the food industry by using a decision tree Abstract Plate heat exchangers are commonly used for food processing, but tend to foul rapidly. Frequent cleaning guarantees product safety and quality, but accounts for high consumption of water, chemicals, energy, and time. Targeted soil characterization is essential for cleaning cost reduction. The effects of soil properties on cleaning are difficult to estimate since the interdependencies are complex. Principal component analysis and a decision tree were used to comprehend this complexity. A variety of carbohydrates formed the basis of the statistical exploration (eight native and modified starches, guar gum, xanthan, pudding, and whey protein isolate). Method adjustments allowed the characterization of soils during contact with different cleaning fluids. Solubility, fluid binding capacity, swelling-induced thickness increase, rheological properties, and pull-off forces were characterized. The cleaning time was obtained from planar channel flow experiments. The decision tree revealed an ordered relevance of the soil properties on cleaning. The effects are largely determined by the active cleaning mechanisms, which were quantified to help explain the results. Interdependence ; Materials science ; Decision tree ; Tree (set theory) ; Computer science ; Process engineering ; Data mining ; Mathematics Spectroscopy and Chemometric Analyses
Authors: Marianna Ntorkou | Constantinos K. Zacharis
Source: Molecules (review, 2025-08-31)
Field: Chemistry — Spectroscopy

Applications of Hydrophilic Interaction Chromatography in Pharmaceutical Impurity Profiling: A Comprehensive Review of Two Decades Hydrophilic Interaction Liquid Chromatography (HILIC) has emerged as a powerful and versatile analytical technique for the separation and quantification of polar and ionizable compounds, particularly in the field of pharmaceutical impurity profiling. Over the past two decades, HILIC has gained increasing attention due to its compatibility with mass spectrometry, enhanced retention of hydrophilic impurities, and ability to resolve structurally similar degradation products and process-related impurities that are often inadequately retained by reversed-phase chromatography. This comprehensive review presents a critical overview of HILIC-based methodologies applied to impurity profiling in pharmaceutical analysis from early 2005 to the present. Emphasis is placed on the application of HILIC to both small-molecule drugs and large biomolecules. Additionally, the review categorizes analytical configurations into four main groups based on their operational principles and use cases, offering insights into method selection and performance characteristics. This article serves as a valuable resource for researchers and regulatory scientists seeking to apply HILIC in modern impurity profiling and quality control of pharmaceutical products. Profiling (computer programming) ; Chromatography ; Chemistry ; Impurity ; Nanotechnology ; Materials science ; Computer science ; Organic chemistry Analytical Chemistry and Chromatography ; Microfluidic and Capillary Electrophoresis Applications ; Protein purification and stability