jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Imran Abdalla Said | Vasit Sagan | Kyle T. Peterson | Haireti Alifu | Abuduwanli Maiwulanjiang | Abby Stylianou | Omar Al Akkad | Supria Sarkar | Noor Al Shakarji
Source: Sensors (article, 2025-01-07)
Field: Chemistry — Analytical Chemistry

Seed Protein Content Estimation with Bench-Top Hyperspectral Imaging and Attentive Convolutional Neural Network Models Wheat is a globally cultivated cereal crop with substantial protein content present in its seeds. This research aimed to develop robust methods for predicting seed protein concentration in wheat seeds using bench-top hyperspectral imaging in the visible, near-infrared (VNIR), and shortwave infrared (SWIR) regions. To fully utilize the spectral and texture features of the full VNIR and SWIR spectral domains, a computer-vision-aided image co-registration methodology was implemented to seamlessly align the VNIR and SWIR bands. Sensitivity analyses were also conducted to identify the most sensitive bands for seed protein estimation. Convolutional neural networks (CNNs) with attention mechanisms were proposed along with traditional machine learning models based on feature engineering including Random Forest (RF) and Support Vector Machine (SVM) regression for comparative analysis. Additionally, the CNN classification approach was used to estimate low, medium, and high protein concentrations because this type of classification is more applicable for breeding efforts. Our results showed that the proposed CNN with attention mechanisms predicted wheat protein content with R<sup>2</sup> values of 0.70 and 0.65 for ventral and dorsal seed orientations, respectively. Although, the R<sup>2</sup> of the CNN approach was lower than of the best performing feature-based method, RF (R<sup>2</sup> of 0.77), end-to-end prediction capabilities with CNN hold great promise for the automation of wheat protein estimation for breeding. The CNN model achieved better classification of protein concentrations between low, medium, and high protein contents, with an R<sup>2</sup> of 0.82. This study's findings highlight the significant potential of hyperspectral imaging and machine learning techniques for advancing precision breeding practices, optimizing seed sorting processes, and enabling targeted agricultural input applications. Hyperspectral imaging ; Convolutional neural network ; Artificial intelligence ; Computer science ; Estimation ; Pattern recognition (psychology) ; Remote sensing ; Engineering ; Geology Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Runsheng Liu | Lihua Li | Jian Zhou
Source: Micromachines (review, 2025-05-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

The Principle and Application of Achromatic Metalens Metalenses, as ultrathin planar optical devices based on metasurfaces, have attracted significant research interest in recent years due to their compact structure and versatile light manipulation, showing great potential to replace traditional lenses in specific applications. This review focuses on the fundamental principles of geometric and propagation phases of metalenses, introducing their applications in achromatic aberration correction, and emphasizing their advantages and limitations. We further discuss the application of multilayer metalenses in zoom optical systems and summarize methods such as topology optimization and inverse design to enhance the efficiency of metalenses. Special attention is given to comparing broadband and discrete achromatic correction, highlighting their respective working principles, design challenges, and practical implications. Additionally, recent advances in using deep learning for image-side aberration correction are briefly discussed. Finally, we highlight various practical applications of metalenses and discuss future research directions. Achromatic lens ; Broadband ; Zoom ; Computer science ; Chromatic aberration ; Planar ; Optics ; Lens (geology) ; Physics ; Computer graphics (images) ; Chromatic scale Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Optical Coatings and Gratings
Authors: Raquel A. Fernandes | Nuno Ferreira | Sandro Lopes | Beatriz Pereira de Freitas | Jorge Santos | Jorge Martins | Luísa Carvalho
Source: Polymers (article, 2025-01-16)
Field: Materials Science — Polymers and Plastics

Antioxidant Particleboards Produced from Forest By-Products with Application in the Food Packaging Industry The food packaging industry is one of the fastest growing sectors of our economy, with a large contribution to environmental concerns due to the extensive use of fossil-derived materials. Combining wood-based materials, such as particleboards, with bio-adhesives may offer a great opportunity to develop sustainable packaging solutions with active antioxidant properties. In the present work, a phenolic extract of poplar bark was produced and bio-adhesives were formulated using citric acid as a cross-linker. The impact of citric acid content on the chemical and bonding properties of bio-adhesives was evaluated. Additionally, the impact of the temperature of curing on their antioxidant capacity was also accessed. The bio-adhesives were applied in the production of particleboards, using poplar veneer particles as raw material. The composite materials exhibit high mechanical resistance, fulfilling the requirement of PB type P1, with remarkable antioxidant activity, opening a possibility to be employed in an active packaging solution. Adhesive ; Raw material ; Citric acid ; Curing (chemistry) ; Pulp and paper industry ; Food packaging ; Materials science ; Antioxidant ; Engineered wood ; Composite material ; Food science ; Chemistry ; Organic chemistry ; Engineering ; Layer (electronics) Natural Fiber Reinforced Composites ; Nanocomposite Films for Food Packaging ; Lignin and Wood Chemistry
Authors: Chil-Chyuan Kuo | Yiqing Lu | Armaan Farooqui | Song-Hua Huang
Source: Polymers (article, 2025-02-08)
Field: Materials Science — Polymers and Plastics

Technical Advancements and Applications in Predictive Modeling of Polyurethane Foaming Height Various polyurethane foams (i.e., rigid, flexible, and spray polyurethane foams) offer diverse applications due to their unique properties, including thermal insulation, cushioning, and seamless gap filling. These foams provide solutions across industries such as construction, automotive, and refrigeration. However, the foaming process presents several challenges that may result in various defects in the final products. This work provides innovative predictive techniques for polyurethane foam expansion and applications in advanced manufacturing processes. The foaming height of the third polyurethane foaming agent (PU-3) closely aligned with the experimentally measured values. The relationship between foaming height and time is influenced by the type and concentration of catalysts, as well as the blowing agents used. However, simulations using Moldex 3D Version 2024 revealed a nonlinear relationship between foaming height and time, characterized by three distinct foaming rates. Zone B demonstrated the highest foaming rate, followed by Zone C, while Zone A showed the lowest rate. The foaming height and rate were significantly influenced by the foaming angle, with smaller angles enhancing both parameters. At a mold temperature of 30 °C and with an expansion coefficient of 35, the predicted foaming height of the polyurethane agent achieved an average accuracy of approximately 96% across four foaming angles. Based on these experimental findings, this study introduces three mechanisms involved in the foaming process of polyurethane foam components. Polyurethane ; Materials science ; Blowing agent ; Foaming agent ; Composite material ; Cushioning ; Mold Polymer Foaming and Composites ; Polymer composites and self-healing ; Injection Molding Process and Properties
Authors: Vincent Chung | Aron Walsh | David J. Payne
Source: Digital Discovery (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Solid-state synthesizability predictions using positive-unlabeled learning from human-curated literature data We present a human curated dataset on solid-state reactions of ternary metal oxides. Applications of this dataset include outlier detection of text-mined datasets, synthesis data analysis, and synthesizability prediction. Computer science ; Outlier ; Ternary operation ; Data mining ; Anomaly detection ; State (computer science) ; Information retrieval ; Artificial intelligence ; Algorithm Machine Learning in Materials Science ; Computational Drug Discovery Methods ; X-ray Diffraction in Crystallography
Authors: Jakub Sitek | W. Sitek | Ben R. Conran | Xiaochen Wang | C. McAleese | Anna Kaleta | S. Kret | Iwona Pasternak | Mariusz Zdrojek | Włodek Strupiński
Source: Scientific Reports (article, 2025-08-05)
Field: Materials Science — Materials Chemistry

Technological limitations of solid-source chemical vapor deposition of van der Waals heterostructures The large-scale synthesis of van der Waals heterostructures (vdWHSs) is required to adopt these materials in electronic devices. However, the repeatable and controllable growth of vdWHSs has proven challenging. Here, we investigate the technological aspects of solid-source chemical vapor deposition (CVD) of two-dimensional heterostructures, with WS<sub>2</sub>/graphene and MoS<sub>2</sub>/graphene as examples. We show that by modification of one variable at least one another is unintentionally altered. For example, change in the growth pressure influences the evaporation rate of sulfur and shifts the position of one of the growth zones. We also perform a statistical screening of the 11 process parameters, indicating which of them impact the evaporation of the precursors. The screening indicates that the evaporation depends on weight of growth promoter (NaCl), growth temperature, precursors temperature, time difference between main and sulfur growth zones reaching the set temperatures, pressure, carrier gas flow, and process time. Finally, the five consecutive, identical growth processes show the seemingly inherent variability in synthesizing vdWHSs. We suggest that the high but limited airtightness of the CVD system or the substrate features can cause repeatability issues. Our study can facilitate future research on van der Waals heterostructures growth. Heterojunction ; Chemical vapor deposition ; van der Waals force ; Graphene ; Evaporation ; Materials science ; Nanotechnology ; Substrate (aquarium) ; Vapor pressure ; Deposition (geology) ; Chemical engineering ; Chemical physics ; Chemistry ; Thermodynamics ; Optoelectronics ; Molecule ; Organic chemistry ; Physics 2D Materials and Applications ; Graphene research and applications ; MXene and MAX Phase Materials
Authors: A. Helmer | Rajeev Gupta
Source: Emergent Materials (article, 2025-08-13)
Field: Materials Science — Biomaterials

Spontaneous passivation in a Rare-Earth-Free Mg4(TiZnSn)3 Multi-Principal element alloy Abstract Mg 4 (TiZnSn) 3 , a rare-earth-free Mg-based multi-principal element alloy, was synthesized via high-energy ball milling and cold compaction. Potentiodynamic polarization in 0.1 M NaCl revealed spontaneous passivation with a corrosion current density of 8.96 ± 0.83 µA/cm 2 and a nobler than Mg corrosion potential of -1058.35 ± 15.91 mV SCE . X-ray photoelectron spectroscopy confirmed the formation of a mixed oxide film containing ZnO, SnO 2 , and TiO 2 , contributing to the observed passivity. The alloy also exhibited improved mechanical performance, with a hardness of 5.06 ± 0.41 GPa and Young’s modulus of 109.24 ± 10 GPa. These results demonstrate that tailored multi-element alloying and powder metallurgy can synergistically enhance both corrosion resistance and mechanical properties in Mg alloys. Passivation ; Rare-earth element ; Rare earth ; Alloy ; Element (criminal law) ; Principal (computer security) ; Materials science ; Chemistry ; Metallurgy ; Composite material ; Computer science Magnesium Alloys: Properties and Applications ; Aluminum Alloys Composites Properties ; MXene and MAX Phase Materials
Authors: Zhuangzhuang Tian | Ziyi Chen | Qing Wang | Xin Gao | Wei Wei
Source: Water (article, 2025-10-17)
Field: Chemistry — Analytical Chemistry

Citric Acid-Modified Sepiolite as an Efficient and Sustainable Adsorbent for the Removal of Methylene Blue from Aqueous Solutions Eco-friendly clay-based adsorbents with low cost and high adsorption capacity for toxic dyes have attracted significant attention. In this study, a novel citric acid-modified sepiolite (CA-SEP) composite was developed for the efficient removal of methylene blue (MB) from aqueous solutions. The morphological, crystalline, and structural properties of the composite were characterized using XRD, FTIR, SEM, and BET analyses. Compared to pristine SEP, CA-SEP exhibited a 2.6-fold increase in adsorption capacity for MB and demonstrated excellent reusability. The effects of key parameters—including solution pH (2.0–10.0), contact time (0–300 min), adsorbent dosage (0.2–2.0 g/L), and initial MB concentration (10–150 mg/L)—on adsorption performance were systematically investigated. Modeling results indicated that the Sips isotherm provided the optimal fit for the equilibrium data. In kinetic studies, the adsorption process was best described by the pseudo-second-order model. The maximum adsorption capacity of CA-SEP for MB was estimated to be 40.61 mg/g. Moreover, the adsorbent retained high removal efficiency after five adsorption-desorption cycles, demonstrating good regenerability. These results indicate that CA-SEP is a highly efficient, sustainable, and economically viable adsorbent for the elimination of MB from contaminated water. Adsorption ; Methylene blue ; Sepiolite ; Aqueous solution ; Citric acid ; Composite number ; Langmuir adsorption model Dye analysis and toxicity ; Water Quality Monitoring and Analysis
Authors: Ramakrishna T. Bhatt | Sreeramesh Kalluri | K. N. Lee | Joshua Stuckner
Source: International Journal of Applied Ceramic Technology (article, 2025-01-06)
Field: Materials Science — Ceramics and Composites

Fatigue durability of an environmental barrier coating–coated two‐dimensional woven SiC/SiC composite at elevated temperatures in a steam environment Abstract Sustained‐peak low‐cycle fatigue tests in a steam environment were conducted on uncoated and environmental‐barrier‐coated SiC‐fiber‐reinforced SiC‐matrix (SiC/SiC) composites at 1204 and 1315°C with an R ratio of 0.5 at maximum stresses from 69 to 138 MPa for up to 500‐h run‐out or failure. The composites were fabricated by the melt‐infiltration process and contained Sylramic‐iBN SiC fibers. The run‐out specimens were tensile tested at room temperature to measure residual tensile properties. Computed tomography, microstructural analysis, and fractography of the failed specimens were conducted. Results indicate that at a constant temperature and stress, mechanical cycling causes environmental barrier coating (EBC) damage with increasing exposure time. Moreover, at a fixed exposure time and stress, damage increases with increasing temperature. Breaching of the EBC followed by moisture‐assisted damage and crack growth within the SiC/SiC substrate dictates durability of EBC SiC/SiC composites. The damage and failure mechanisms of the composites are discussed. Materials science ; Composite material ; Durability ; Composite number ; Ultimate tensile strength ; Coating ; Fractography ; Temperature cycling ; Ceramic matrix composite ; Stress (linguistics) ; Residual stress ; Thermal Advanced ceramic materials synthesis ; Advanced materials and composites ; Thermal properties of materials
Authors: Qian Wang | Xiao Liu | Yifan Su | Yibo Shi | Kai Feng | Lin Liu | Wei Sun | Yongqiang Dong | Jiani Ma | Xuebo Chen
Source: Advanced Optical Materials (article, 2025-05-27)
Field: Materials Science — Materials Chemistry

Separate Control Model for Tailoring Ultralong Organic Room‐Temperature Phosphorescence with Highly Efficient Energy Transfer to Rhodamine B Abstract Organic room‐temperature phosphorescence (RTP) materials have attracted significant attention for their promising applications, yet achieving high‐efficiency RTP molecules remains challenging. To address this, a comprehensive dataset of donor–acceptor (D–A) structured molecules is developed using D and A fragment pools. Promising phosphorescent candidates can be efficiently identified through high‐throughput screening that combines density functional theory (DFT) with high‐precision multireference perturbation theory calculations. A key innovation is the introduction of the “separate control model”, which independently optimizes both spin–orbit coupling (SOC) and the singlet‐triplet energy gap (Δ E ST ). Using this method, the phosphorescent unit 5,5‐dioxido‐10‐(phenanthren‐9‐yl)‐10H‐phenothiazin‐3‐yl)(phenyl) methanone (PPTZO‐CO), exhibits an exceptionally high intersystem crossing (ISC) rate constant of 10¹¹ s⁻¹, representing the highest value reported in organic systems to date. Remarkably, the RTP lifetime of PPTZO‐CO reaches up to 700 ms when doped into polymethyl methacrylate (PMMA). Co‐doping PPTZO‐CO with rhodamine B (RB) in PMMA yields red afterglow emission with near 100% energy transfer efficiency, the highest reported for co‐doped polymer systems. The PPTZO‐CO@PMMA system demonstrates promise in dynamic anti‐counterfeiting, showcasing its potential for practical use. Phosphorescence ; Materials science ; Energy transfer ; Rhodamine B ; Rhodamine ; Optoelectronics ; Nanotechnology ; Engineering physics ; Optics ; Fluorescence ; Organic chemistry Luminescence and Fluorescent Materials ; Organic Light-Emitting Diodes Research ; Photoreceptor and optogenetics research
Authors: Anna A. Hoser | Anders Ø. Madsen
Source: IUCrJ (article, 2025-06-06)
Field: Chemistry — Organic Chemistry

Models of thermal motion in small-molecule crystallography The Debye-Waller factor, introduced a century ago, remains a fundamental component in the refinement of crystal structures against X-ray, neutron and electron diffraction data. This review marks its centenary by exploring its applications in small-molecule crystallography. We provide a historical overview of the development of the Debye-Waller factor and its foundations in lattice dynamics. The review discusses the practical use of anisotropic displacement parameters and their role in accurate structure determination. We also address the challenges and advancements in modelling thermal motion and disorder, the role of multi-temperature measurements and modern computational approaches. Thermal motion ; Chemistry ; Computer science ; Molecule ; Small molecule ; Crystallography ; Physics ; Biochemistry Chemical Thermodynamics and Molecular Structure ; Crystallography and molecular interactions ; Molecular spectroscopy and chirality
Authors: Khawla Belazizia | Ouided Benslama | Rafika Bouchene | Fadila Berrah | Randolf D. Köhn | Gabriele Kociok‐Köhn | Mahmoud Chebbah | Mustapha Bouhenguel | Ahcene Bouchemma
Source: Journal of Molecular Structure (article, 2025-02-05)
Field: Chemistry — Organic Chemistry

Two new asymmetrically substituted 1,3,5- triazacyclohexanes: Synthesis, structural characterisation, Hirshfeld surface analysis, DFT calculations, network pharmacology- and molecular docking-based approach to explore the anti-breast-cancer potential Chemistry ; Docking (animal) ; Computational chemistry ; Breast cancer ; Stereochemistry ; Combinatorial chemistry ; Cancer Synthesis and biological activity ; Click Chemistry and Applications ; Synthesis and Characterization of Heterocyclic Compounds
Authors: Syed Shakir | Umer Rashid | Marryum | Nighat Fatima | Syeda Abida Ejaz | Ammara Fayyaz | Muhammad Zahid Ullah | Aamer Saeed | Ajmal Khan | Ahmed Al‐Harrasi | Amara Mumtaz
Source: RSC Advances (article, 2025-01-01)
Field: Chemistry — Organic Chemistry

Exploration of novel triazolo-thiadiazine hybrids of deferasirox as multi-target-directed anti-neuroinflammatory agents with structure–activity relationship (SAR): a new treatment opportunity for Alzheimer's disease It is believed that inflammation influences several physiological processes, including the function of the central nervous system. Moreover, the impairment of lipid mechanisms/pathways is associated with neurodegenerative disorders and onset of Alzheimer's disease (AD). AD is a chronic neurodegenerative disease representing the major cause of dementia worldwide. In this case, the overexpression of different pharmacological targets has been confirmed to address neuronal inflammation and AD, with acetylcholinesterase (AChE), monoamine oxidase-B (MAO-B), cyclooxygenase-2 (COX-2) and 5-lipoxygenase (LOX-5) being the most explored targets. Currently, the available treatments are only capable of alleviating the symptoms and not capable of delivering disease-modifying effects. Thus, the current research objective is to synthesize triazolo-thiadiazine derivatives of the deferasirox drug as multi-target compounds that could concurrently inhibit ChEs, MAOs, LOX-5 and COX-2. The synthesized derivatives were confirmed by FTIR, <sup>1</sup>H NMR, <sup>13</sup>C NMR and DEPT-135 spectroscopic techniques. During <i>in vitro</i> investigations, compound 11 was found to be the most potent inhibitor of all the targeted enzymes. Briefly, this compound exhibited inhibitory values (IC<sub>50</sub> ± SEM) of 0.31 ± 0.16, 0.13 ± 0.16 and 0.94 ± 0.16 μM against AChE, MAO-B and COX-2, respectively, suggesting that it is a lead molecule for the synthesis of more potential multi-targeted inhibitors. Several compounds, such as compound 9 and 13, showed dual inhibition potential in comparison to standard drugs. Furthermore, molecular docking analysis was performed to validate the <i>in vitro</i> results, where the potent compounds showed some significant interactions with the key amino acids present in the active site of the targeted enzymes. Furthermore, molecular dynamics (MD) simulation data and physicochemical properties supported deferasirox-substituted triazolo-thiadiazine as a promising horizon for the discovery and development of new molecules to treat multifactorial diseases associated with neuro-inflammation, such as AD. Deferasirox ; Pharmacophore ; Medicine ; Virtual screening ; Disease ; Pharmacology ; Chemistry ; Internal medicine ; Stereochemistry Synthesis and biological activity ; Click Chemistry and Applications ; Computational Drug Discovery Methods
Authors: Chao Tan | Hao Liu | Zhen Zhang | Xinyu Liu | Yuhang Ai | Xiumin Wu | Enlin Jian | Yongyan Song | Jin Yang
Source: Frontiers in Medicine (review, 2025-08-15)
Field: Chemistry — Spectroscopy

Progress and trends on machine learning in proteomics during 1997-2024: a bibliometric analysis https://doi.org/10.17605/OSF.IO/F4WUG. Bibliometrics ; Transformative learning ; Data science ; Citation ; Construct (python library) ; Citation analysis ; Computer science ; Library science ; Sociology Advanced Proteomics Techniques and Applications ; Bioinformatics and Genomic Networks ; Machine Learning in Bioinformatics