jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Claudia Florio | Antonio Medici | Roberta Aveta | L. W. Esposito | Andrea Favazzi | Flavio Belvedere | Armando Zarrelli | María Sarno
Source: Scientific Reports (article, 2025-10-14)
Field: Chemistry — Analytical Chemistry

The potential of near infrared (NIR) spectroscopy coupled to principal component analysis (PCA) for product and tanning process control of innovative leathers The tanning industry faces significant challenges in quality control due to the complex transformations of leather, the anisotropic nature of the raw material, and the increasing adoption of innovative processes and materials in the tanning methods. In this study, it was possible to evaluate the applicability of a Non-Destructive Testing (NDT) technique such as near infrared (NIR) spectroscopy applied to the new generation of tanning products and processes as a potential technique for supporting product and process quality control activities. A microNIR sensor was employed to analyse intermediate leather samples, nano-functionalised finishing products, and tanning waters. By means of Principal Component Analysis (PCA), it was possible to differentiate tanned products with traditional processes and innovative methods. The same chemometric model was applied for process control when using nanostructured substances which helped to assess how effectively the nanostructured agents were incorporated into the final material. These results demonstrated how NIR spectroscopy coupled with chemometric models can provide real-time insights into traditional and innovative tanning processes, optimise resource consumption, and support sustainability in the leather industry. Near-infrared spectroscopy ; Principal component analysis ; Process analytical technology ; Process (computing) ; Raw material ; Process control ; Spectroscopy ; Chemometrics Spectroscopy and Chemometric Analyses ; Collagen: Extraction and Characterization
Authors: Sajan Tamang | Heesung Park
Source: Journal of Physics Conference Series (article, 2025-02-01)
Field: Materials Science — Materials Chemistry

Numerical investigation on the dry low NOx of hydrogen combustion Abstract Globally, energy is predominantly generated through the combustion of fossil fuels. However, the emissions from these fuels severely impact the ecological balance and environment. As a result, there is a growing emphasis on clean and renewable energy sources as alternatives. Hydrogen is a promising and clean energy source for gas turbines, transportation, and industrial applications. Nevertheless, due to significant differences in hydrogen’s thermophysical properties, it cannot be directly integrated into conventional combustion systems. Therefore, a specialized micromix combustion model must be developed to achieve stable combustion with low dry NOx emissions. In this study, a novel micromix combustor is developed based on the cross-flow mixing of air and injected hydrogen fuel. Under this concept, hydrogen combustion occurs through diffusion-type flames, with the reaction taking place in a very short time. This micromix combustor design ensures inherently stable combustion, resistant to flashback while maintaining low dry NOx emissions. The results indicate that the stability of the flame structure and thermal NOx emissions are controlled by the operating equivalence ratios. A stable hydrogen flame was particularly formed in the shear regions between the two vortices. Thermal NOx generation was strongly influenced by the flame front temperature, with measurements ranging from approximately 0.66 to 11.14 ppm (at 15% oxygen concentration). Consequently, thermal NOx emissions increased by up to 16 times under an equivalence ratio of 0.5. NOx ; Combustion ; Environmental science ; Hydrogen ; Waste management ; Chemistry ; Engineering Catalytic Processes in Materials Science ; Advanced Combustion Engine Technologies ; Industrial Gas Emission Control
Authors: Angus G. MacGruer | Steven Johnson | Simon Peter Mekhail | Kyle J. Nutt | Miles J. Padgett | Graham M. Gibson
Source: Scientific Reports (article, 2025-03-13)
Field: Chemistry — Spectroscopy

Characterising the performance of a drone-mounted real-time methane imaging system We demonstrate a methane gas imaging system mounted to an unmanned aerial vehicle (UAV) that is shown to perform real-time detection at distances up to 10m whist airborne. Laser diodes that switch between on- and off- resonance with a <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:mrow><mml:mn>1.6</mml:mn></mml:mrow> <mml:mrow><mml:mi>μ</mml:mi> <mml:mtext>m</mml:mtext></mml:mrow> </mml:mrow> </mml:math> methane absorption line are used to flood-illuminate a scene. The scene is imaged with an infrared InGaAs camera and the differential of the on-resonance and off-resonance back-scatter images are used to reveal the gas distribution. The performance of the system was characterised against a range of back-scatter surfaces, showing promising applicability to realistic gas sensing environments. We demonstrate that the system is capable of detecting a gas concentration of 5000 ppm.metre up to a range of 13.6m. Resonance (particle physics) ; Methane ; Drone ; Computer science ; Range (aeronautics) ; Physics ; Analytical Chemistry (journal) ; Materials science ; Remote sensing ; Geology ; Chemistry ; Atomic physics Spectroscopy and Laser Applications ; Atmospheric and Environmental Gas Dynamics ; Atmospheric aerosols and clouds
Authors: Xiong Fei Ruan | Luo Li | Xiangyang Yu | Yefan Cai | Weibin Hong
Source: Frontiers in Computing and Intelligent Systems (article, 2025-01-21)
Field: Materials Science — Polymers and Plastics

Rapid Textile Fibers Classification Technology Based on Near-Infrared Spectroscopy and Machine Learning The accurate identification of textile materials plays a crucial role in production control, quality inspection, and market regulation. In recent years, near-infrared (NIR) spectroscopy has been widely applied in the identification and classification of textile fibers due to its rapid, non-destructive, and efficient characteristics. Therefore, this study utilizes a handheld near-infrared spectrometer and chemometrics to provide a convenient, efficient, non-destructive, and green analytical method for the qualitative analysis of textiles. The article collects spectral data of fiber samples using a handheld NIR spectrometer and analyzes them with chemometric methods. Data preprocessing techniques, feature extraction algorithms, comprehensive sampling methods, and classification algorithms are employed to establish classification models. After ten-fold cross-validation, the optimal SG_RF model is obtained, with a classification accuracy of 93.7% on the test set and an AUC_macro of 0.928, demonstrating excellent performance. The article validates the feasibility of using near-infrared spectroscopy combined with chemometric methods for textile fiber classification, offering a rapid, non-destructive, and efficient approach for textile fiber classification. Textile ; Infrared ; Infrared spectroscopy ; Spectroscopy ; Materials science ; Computer science ; Process engineering ; Environmental science ; Engineering ; Composite material ; Chemistry ; Optics ; Physics ; Organic chemistry Textile materials and evaluations
Authors: M. Aravindh | Debabrata Barik | Rasan Sarbast Faisal | Makeshkumar Mani | Milon Selvam Dennison | A. Dinesh | Saravanan Rajendran
Source: Scientific Reports (article, 2025-10-16)
Field: Materials Science — Polymers and Plastics

Process parameter optimization for enhanced mechanical and thermal properties of kenaf/jute hybrid composites using grey fuzzy logic Research on natural fiber composites often prioritizes fiber composition over manufacturing parameters, leaving a gap in optimizing the compression molding process critical for interfacial adhesion and mechanical performance in hybrid composites. This study addresses this by applying a Grey-Fuzzy Logic approach to optimize the compression molding parameters for kenaf/Jute hybrid composites, a material chosen for its complementary strength and sustainability yet challenged by hydrophilicity and poor fiber-matrix bonding. An L16 Taguchi design was used, varying Kenaf fiber (10-25 wt%), Jute fiber (10-25 wt%), NaOH treatment (0-8 wt%), molding pressure (10-16 MPa), and temperature (100-120 °C). The results identified a singular optimal parameter set (20 wt% kenaf (KF), 25 wt% jute, 5 wt% NaOH, 10 MPa molding pressure, and a temperature of 120 °C), achieving a Grey-Fuzzy Grade of 0.888 and yielding maximum mechanical properties (48.8 MPa tensile, 90.1 MPa flexural, 33.7kJ/m<sup>2</sup> impact). Crucially, ANOVA revealed molding pressure as the second-most significant factor (29.47% contribution), a novel finding underscoring that process parameters are as vital as fiber selection. This research uniquely demonstrates that superior hybrid composite performance is not attained through fiber treatment alone but requires the synergistic optimization of material and process parameters. The validated Grey-Fuzzy model provides a robust framework for manufacturing high-performance, sustainable composites for automotive and structural applications. Material characterization further confirmed that the 5% NaOH treatment effectively removed non-cellulosic components (Fourier Transform infrared spectroscopy) (FTIR); increased crystallinity by 12% (X-Ray Diffraction); enhanced thermal stability, raising the maximum degradation temperature by 5 °C (Thermogravimetric Analysis). Taguchi methods ; Kenaf ; Compression molding ; Molding (decorative) ; Fiber ; Composite number ; Orthogonal array ; Thermal ; Thermography Natural Fiber Reinforced Composites ; Nanocomposite Films for Food Packaging ; Material Properties and Processing
Authors: Ayman M. Alneamy | K Hemalatha | Mohammed Y. Tharwan
Source: Mathematics (article, 2025-09-09)
Field: Materials Science — Materials Chemistry

Influence of Flexoelectric Coupling and Interfacial Imperfection on Shear Horizontal Wave Propagation in a Piezoflexoelectric Layer over an Elastic Substrate This study analytically investigates shear horizontal (SH) wave propagation in a layered structure consisting of a piezoflexoelectric (PFE) layer bonded to an elastic substrate, considering an imperfect interface. A frequency equation is derived by applying appropriate boundary and interfacial conditions, capturing the effects of flexoelectric coupling, interface imperfections, the layer thickness, and the material properties. The resulting dispersion relation reveals that both interface imperfections and the flexoelectric strength significantly alter the phase velocity of SH waves. Numerical simulations show that increasing flexoelectric coefficients or interface imperfections lead to notable changes in dispersion behavior. Comparative analyses under electrically open (EO)- and electrically short (ES)-circuited boundary conditions demonstrate their impacts on wave propagation. These findings offer new insights into the design and analysis of piezoflexoelectric devices with realistic interface conditions. Dispersion relation ; Dispersion (optics) ; Phase velocity ; Wave propagation ; Shear (geology) ; Coupling (piping) ; Boundary value problem ; Layer (electronics) Nonlocal and gradient elasticity in micro/nano structures ; Fluid Dynamics and Vibration Analysis ; Acoustic Wave Phenomena Research
Authors: Ankit Kumar Dubey | Siva Sai Chandragiri | Abin V. Geevarghese | Bhupinder Kapoor | Monica Gulati | Pooja Rani | Gursharan Singh | Vivek P. Chavda | Rohit Gundamaraju | Himangini Bansal | Rupesh K. Gautam | Rajat Goyal | Michael P. Okoh | Bairong Shen | Rajeev K. Singla
Source: Frontiers in Pharmacology (review, 2025-10-03)
Field: Chemistry — Analytical Chemistry

Exploring the pharmacokinetics, drug-likeness, and toxicological features of anticancer flavonoids: a Boulevard to explore their clinical translational potential This investigation enhances our understanding of the translational potential of flavonoid-based therapies by highlighting these essential elements, bringing us one step closer to the development of effective and safe cancer treatments. Boulevard ; Translational research ; Translational medicine ; Preclinical research ; Translational science ; Cancer Chromatography in Natural Products ; Phytochemicals and Antioxidant Activities ; Synthesis and biological activity
Authors: Amir Hossein Namdar | Nastaran Zoghi | Aline F. Miller | Alberto Saiani | Tom Shearer
Source: Physical review. E (article, 2025-06-04)
Field: Materials Science — Biomaterials

Effects of fiber spatial distribution and relative orientation on the percolation and mechanics of stochastic fiber networks: A model of peptide hydrogels The structures of fiber networks can vary greatly due to fiber interactions during formation. We have modified the steps of generating Mikado networks to create two model classes by altering the spatial distribution and relative orientation of their fibers to mimic the structures of self-assembling peptide hydrogels (SAPHs), whose physical properties depend strongly on their fibers' interactions. The results of our models and experiments on a set of beta-sheet forming SAPHs show that modifying a network's structure affects the percolation threshold and the mechanical behavior of the material, both near percolation and at higher densities. Percolation (cognitive psychology) ; Fiber ; Self-healing hydrogels ; Statistical physics ; Materials science ; Orientation (vector space) ; Percolation threshold ; Percolation theory ; Composite material ; Topology (electrical circuits) ; Physics ; Mathematics ; Geometry ; Combinatorics ; Neuroscience ; Polymer chemistry ; Psychology ; Electrical resistivity and conductivity Supramolecular Self-Assembly in Materials ; Polydiacetylene-based materials and applications ; Hydrogels: synthesis, properties, applications
Authors: Bashar Saad | Abdalsalam Kmail
Source: Immuno (article, 2025-08-26)
Field: Chemistry — Organic Chemistry

Olive Oil Polyphenols in Cancer: Molecular Mechanisms and Therapeutic Promise Olive oil, a cornerstone of the Mediterranean diet, is increasingly recognized not only for its cardiovascular benefits but also for its potential role in cancer prevention and therapy. Among its bioactive constituents, several phenolic compounds—tyrosol, hydroxytyrosol, oleuropein, oleacein, and oleocanthal—have demonstrated promising anticancer activities in various experimental models. These compounds act synergistically through diverse mechanisms, including antioxidant, anti-inflammatory, and immunomodulatory effects, as well as modulation of cell proliferation, apoptosis, angiogenesis, and metastasis. Notably, oleocanthal selectively induces cancer cell death via lysosomal membrane permeabilization, while hydroxytyrosol and oleuropein exhibit potent radical-scavenging and anti-proliferative properties. This review synthesizes findings from in vitro, in vivo, and clinical studies on the anticancer potential of these polyphenols, with emphasis on their mechanisms of action and possible applications in cancer prevention and adjunctive therapy. Given the established link between obesity and cancer development, clinical studies examining the metabolic, anti-inflammatory, and immunomodulatory effects of olive polyphenols in populations with obesity or prediabetes provide valuable insights into their potential to influence cancer-related pathways indirectly. However, direct clinical evidence in cancer patients remains limited and preliminary, underscoring the need for focused, well-controlled trials with cancer-specific endpoints. Furthermore, it critically evaluates the translational relevance of these findings, highlighting gaps in clinical research and future directions. Literature was retrieved from Google Scholar, PubMed, and ScienceDirect using keywords such as cancer, immunomodulatory, anti-inflammatory, olive, tyrosol, hydroxytyrosol, oleuropein, oleacein, and oleocanthal. Given the rising global cancer burden and the favorable safety profiles of these natural molecules, elucidating their molecular actions may support the development of novel integrative therapeutic strategies. Polyphenol ; Olive oil ; Cancer ; Medicine ; Pharmacology ; Traditional medicine ; Chemistry ; Food science ; Biochemistry ; Internal medicine ; Antioxidant Edible Oils Quality and Analysis ; Phytochemicals and Antioxidant Activities ; Cholesterol and Lipid Metabolism
Authors: Weimin Ning | Mingxuan Li | Lei Jiang | Yang Mei | Mao-Yan Liu | Yong Liu
Source: Nanomaterials (article, 2025-05-22)
Field: Materials Science — Materials Chemistry

Endophytic Bacterial Community Structure and Function Response of BLB Rice Leaves After Foliar Application of Cu-Ag Nanoparticles Bacterial leaf blight (BLB) is a destructive disease caused by <i>Xanthomonas oryzae pv. oryzae</i> (<i>Xoo</i>). It has been proven that BLB adversely influences the growth and production of rice, resulting in substantial losses in yield. Nanoparticle-antimicrobial compounds possess excellent physicochemical properties, which have generated groundbreaking applications in protecting rice against BLB attacks. However, there is less research focused on the interaction between nanoparticles and the microbiome of BLB rice leaves, particularly the structure and function of endophytic bacteria, which are essential to plant health and pathogenesis. Therefore, the study explored how Cu-Ag nanoparticles influenced the endophytic bacteria's composition and functions in healthy and BLB rice leaves. The data demonstrated that the relative abundance of beneficial bacteria, <i>Burkholderiales</i>, <i>Micrococcales</i>, and <i>Rhizobiales</i>, increased after the introduction of Cu-Ag nanoparticles on the leaves of BLB rice. The examination of PAL activity demonstrated that nanoparticles limited the spread of <i>Xoo</i> in rice leaves. Furthermore, endophytic community functional prediction demonstrated that nanoparticles may regulate the physiological process associated with potential stress resistance and growth-promoting function in the endophytic communities. This investigation may enhance the understanding of interactions between nanoparticles and the composition of rice endophytic microbiome, which can contribute to the exploration and application of nanomaterials in crop pathogen management. Xanthomonas oryzae ; Xanthomonas oryzae pv. oryzae ; Bacteria ; Oryza sativa ; Endophyte ; Microbiome ; Crop ; Botany ; Biology ; Chemistry ; Agronomy ; Biochemistry Nanoparticles: synthesis and applications ; Plant Pathogenic Bacteria Studies ; Plant-Microbe Interactions and Immunity
Authors: Emanuela Salviati | Dominika Luptáková | Anna Nilsson | Mohammadreza Shariatgorji | Pietro Campiglia | Nikita Tjernström | Erika Roman | Per E. Andrén
Source: Journal of Neurochemistry (article, 2025-06-01)
Field: Chemistry — Spectroscopy

Preserving Neuronal Chemical Messengers: Heat Stabilization Versus Snap Freezing for Improved <scp>MALDI</scp> Mass Spectrometry Imaging of Brain Tissues One of the main challenges in analyzing chemical messengers in the brain is the optimization of tissue sampling and preparation protocols. Limiting postmortem time and terminating enzyme activity is critical to identify low-abundance neurotransmitters and neuropeptides. Here, we used a rapid and uniform conductive heat transfer stabilization method that was compared with a conventional fresh freezing protocol. Together with a selective chemical derivatization method and an optimized quantitation approach using deuterated internal standards, we spatially mapped neurotransmitters and their related metabolites by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) in rat brain tissue sections. Although the heat stabilization did not show differences in the levels of dopamine, norepinephrine, and serotonin, their related metabolites 3,4-dihydroxyphenylacetaldehyde, 3,4-dihydroxyphenylacetic acid, homovanillic acid, 3-methoxy-4-hydroxyphenylacetaldehyde, dihydroxyphenylethyleneglycol, and 5-hydroxyindoleacetic acid were all significantly lower, indicating reduced neurotransmitter postmortem turnover ratios. Heat stabilization enabled detection of an increased number and higher levels of prodynorphin, proenkephalin, and tachykinin-derived bioactive neuropeptides. The low-abundant C-terminal flanking peptide, neuropeptide-γ, and nociceptin remained intact and were exclusively imaged in heat-stabilized brains. Without heat stabilization, degradation fragments of full-length peptides occurred in the fresh frozen tissues. The sample preparation protocols were furthermore tested on rat brains affected by acute anesthesia induced by isoflurane and medetomidine, showing comparable results to non-anesthetized animals on the neurotransmitters level without significant changes. Our data provide evidence for the potential use of heat stabilization prior to MALDI-MSI analyses to improve the examination of the in vivo state of neuronal chemical messengers in brain tissues not impacted by prior acute anesthesia. Chemistry ; Neuropeptide ; Biogenic amine ; Homovanillic acid ; Mass spectrometry imaging ; Neurotransmitter ; Mass spectrometry ; Metabolite ; Monoamine neurotransmitter ; Serotonin ; Biochemistry ; Chromatography ; Internal medicine Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Chromatography ; Metabolomics and Mass Spectrometry Studies
Authors: Hashem O. Alsaab | Yusuf S. Althobaiti
Source: Scientific Reports (article, 2025-10-03)
Field: Chemistry — Spectroscopy

Intelligence modeling of solubility of raloxifene and density of solvent for green supercritical processing of medicines for enhanced solubility In this study, a dataset for solubility of raloxifene and CO<sub>2</sub> density was analyzed using different regression models to reveal the correlation between inputs and drug solubility via supercritical processing. The models were developed and analyzed for their accuracy in predicting the process variables. Three models of Elastic Net Regression (ENR), Orthogonal Matching Pursuit (OMP), and Gaussian Process Regression (GPR) are optimized for the dataset of drug. For CO<sub>2</sub> density estimation, GPR turned out to be the best R<sup>2</sup>, which confirmed a robust correlation. Therefore, the GPR model can be considered the most accurate and reliable for predicting CO<sub>2</sub> density in this context. Regarding solubility, both the ENR and OMP models demonstrated similar performance with high R<sup>2</sup> of 0.89062 and 0.89125, respectively. However, GPR outperformed the others with an impressive R<sup>2</sup> of 0.97755, a lower RMSE of 3.3221E-01, and a relatively lower AARD% of 7.08009E + 00. Hence, the GPR model is recommended for accurate solubility predictions of raloxifene. Overall, the GPR model consistently demonstrated excellent predictive performance for both CO<sub>2</sub> density and solubility, making it the preferred choice for modeling these relationships. Solubility ; Supercritical fluid ; Raloxifene ; Kriging ; Regression ; Ground-penetrating radar ; Partial least squares regression ; Mean squared error Analytical Chemistry and Chromatography ; Phase Equilibria and Thermodynamics ; Crystallization and Solubility Studies
Authors: Ji Yeong Ham | Yong-Tae Kim | Suong Tuyet Thi Ha | Bong-Su Choi | Byung-Chun In
Source: Horticultural Science and Technology (article, 2025-01-22)
Field: Chemistry — Analytical Chemistry

Rapid Estimations of the Postharvest Quality and Longevity of Cut Roses using Vis/NIR Spectroscopy Postharvest ; Longevity ; Cut flowers ; Environmental science ; Quality (philosophy) ; Horticulture ; Biology ; Physics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Phytochemicals and Antioxidant Activities