jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Marta A. Teixeira | Inês Leite | Raquel Gonçalves | Helena Vilaça | Catarina Guise | Carla Silva
Source: Fibers (article, 2025-08-21)
Field: Materials Science — Biomaterials

Comprehensive Evaluation of Wet-Spun Polyhydroxyalkanoate Fibres: Morphology, Crystallinity, and Thermal Properties In response to increasing environmental concerns, significant efforts have been made to reduce our reliance on fossil fuel-based plastics, driving the development of sustainable alternatives such as polyhydroxyalkanoates (PHAs). This study investigates the processing of various PHAs into fibres, focusing on their morphological, thermal, and mechanical properties. Different PHAs were spun into fibres at a 15% (w/v) concentration using wet-spinning techniques. Among the PHAs studied, commercially available PHBHHx, used as a reference, exhibited spongy morphology in the fibres and demonstrated thermal vulnerability due to its rapid degradation. Blended fibres showed enhanced morphological and mechanical properties compared with neat fibres. In Fourier-transform infrared spectroscopy (FTIR), no differences were observed between the unprocessed polymers and the wet-spun polymeric fibres, indicating that the wet-spinning process did not affect the molecular structure of the polymers. Thermal and mechanical evaluations confirmed the miscibility between the polymers in the blends. Overall, these results highlight, for the first time, the successful production of wet-spun fibres from two modified P(3HB) variants, individually, in combination with each other, and in blends with the well-established commercial PHA, PHBHHx. However, this study also underscores the need to optimise feed rates to enhance fibre production efficiency and mechanical strength, thereby broadening their potential for various applications. Polyhydroxyalkanoates ; Crystallinity ; Materials science ; Morphology (biology) ; Thermal ; Chemical engineering ; Composite material ; Polymer science ; Geology ; Engineering ; Thermodynamics ; Bacteria biodegradable polymer synthesis and properties ; Additive Manufacturing and 3D Printing Technologies ; Electrospun Nanofibers in Biomedical Applications
Authors: Bárbara de Salles Macena da Cruz | Lucas Galhardo Pimenta Tienne | Vinícius de Oliveira Aguiar | Fábio Elias Jorge | Maria de Fátima Vieira Marques | Érica Gervasoni Chaves
Source: Journal of Applied Polymer Science (article, 2025-11-19)
Field: Materials Science — Polymers and Plastics

PE‐RT Grades for High‐Temperature Flexible Risers: Comparative Evaluation of Thermal, Mechanical, and Aging Performance ABSTRACT This study compares three polyethylene grades—a benchmark PE100 and two high‐temperature resistant polyethylene (PE‐RT) types (Type I and Type II)—to assess their suitability for flexible riser applications. The materials were evaluated for their thermal stability, crystallinity, mechanical performance, and resistance to thermal aging at 110°C for up to 180 days. Differential scanning calorimetry (DSC) and x‐ray diffraction (XRD) indicated that PE‐RT Type II had a higher degree of crystallinity. Thermogravimetric analysis (TGA) showed that PE100 had the highest T onset (457°C), confirming its superior thermal stability. However, PE‐RT Type II was the most promising material, showing a balanced response to thermal and chemical stress with excellent thermo‐oxidative durability, flexibility, and aging resistance. The tensile test results demonstrated that PE‐RT Type II consistently outperformed PE‐RT Type I in mechanical strength and durability. After aging tests performed in synthetic oil at 80°C for 180 days, PE‐RT Type II retained approximately 85% of its original elongation at break and 90% of its initial tensile strength. In contrast, PE‐RT Type I exhibited a significant reduction in performance, retaining only about 42% of its original elongation and 70% of its tensile strength. These results indicate that PE‐RT Type II is more resistant to thermal and oxidative degradation, reinforcing its suitability for long‐term use in high‐temperature flexible riser systems. Fourier‐transform infrared (FTIR) spectroscopy revealed more significant oxidation in Type I, suggesting lower resistance to thermo‐oxidative degradation. Overall, PE‐RT Type II displayed an enhanced balance of properties, making it the most promising candidate among the evaluated materials for application in high‐temperature flexible riser barrier layers. Ultimate tensile strength ; Differential scanning calorimetry ; Thermogravimetric analysis ; Polyethylene ; Elongation ; Tensile testing ; Accelerated aging Polymer crystallization and properties ; Mechanical stress and fatigue analysis ; Tribology and Wear Analysis
Authors: Arun K. Upadhyaya | Dibyendu K. Sasmal
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-06-27)
Field: Materials Science — Materials Chemistry

Curcumin Conjugated Carbon Quantum Dots: A Theranostic Probe to Study BSA Interaction, Cellular Imaging, and RICS-Based Intracellular Transport Abstract Plant-based products such as jamun leaves and herbaceous perennials like turmeric are replete with carbon-rich elements, and our recent focus has been directed to synthesizing Carbon Quantum Dots (CQDs) in a low-cost, straightforward, and sustainable method, with their biological and therapeutic applications. A valuable insight we have gained from our results is the environmentally friendly production of CQDs with their distinct physicochemical characteristics, in addition to excellent water solubility and remarkable stability. The as-synthesized CQDs manifest good quantum yields with many potential applications. Moreover, for the stability and enhancement of the solubilization of the hydrophobic drug curcumin, to improve its uptake and bio accessibility, CQDs are a unique choice. After the conjugation of CQDs with curcumin (C-CQDs), the findings we have obtained with partially unfolded BSA demonstrate a modest interaction involving dynamic quenching, as exemplified by steady-state and time-resolved fluorescence quenching driven by Forster Resonance Energy Transfer (FRET). In addition to that, our research also delved into the application of in vivo bioimaging, and by using that fluorescence imaging technique, we introduced Raster Image Correlation Spectroscopy (RICS) techniques to find the diffusion of both CQDs and C-CQDs in the live cell. The study also reaffirms the inherent biocompatibility and antibacterial ability confirmed by the MTT-based cytotoxicity assay and MIC study. Curcumin ; Conjugated system ; Quantum dot ; Intracellular ; Nanotechnology ; Carbon quantum dots ; Chemistry ; Biophysics ; Materials science ; Biochemistry ; Organic chemistry ; Polymer Carbon and Quantum Dots Applications ; Electrochemical sensors and biosensors ; Nicotinic Acetylcholine Receptors Study
Authors: Lidong Wan | Haitao Fan | Xiuhua Chen | Fan Guo
Source: Journal of Composites Science (article, 2025-12-30)
Field: Materials Science — Materials Chemistry

FiberGAN: A Conditional GAN-Based Model for Small-Sample Prediction of Stress–Strain Fields in Composites Accurate prediction of the stress–strain fields in fiber-reinforced composites is crucial for performance analysis and structural design. However, due to their complex microstructures, traditional finite element analysis (FEA) entails a very high computational cost. Therefore, this study proposes a conditional generative adversarial network (cGAN) framework, named FiberGAN, to enable rapid prediction of the microscopic stress–strain fields in fiber-reinforced composites. The method employs an adaptive representative volume element (RVE) generation algorithm to construct random fiber arrangements with fiber volume fractions ranging from 30% to 50% and uses FEA to obtain the corresponding stress and strain fields as training data. A U-Net generator, combined with a PatchGAN discriminator, captures both global distribution patterns and fine local details. Under tensile and shear loading conditions, the R2 values of FiberGAN predictions range from 0.96 to 0.99, while the structural similarity index (SSIM) values range from 0.95 to 0.99. The error maps show that prediction residuals are mainly concentrated in high-gradient regions with small magnitudes. These results demonstrate that the proposed deep learning model can successfully predict stress–strain field distributions for different fiber volume fractions under various loading conditions. Finite element method ; Range (aeronautics) ; Fiber ; Random field ; Representative elementary volume ; Field (mathematics) ; Conditional random field ; Similarity (geometry) ; Volume (thermodynamics) Machine Learning in Materials Science ; Composite Material Mechanics ; Mechanical Behavior of Composites
Authors: Ikuto Nakatsukasa | Victor Parque | Yasuaki Ito | Koji Nakano
Source: Applied Sciences (article, 2025-10-31)
Field: Materials Science — Materials Chemistry

Predicting the Cooling Rate in Steel-Part Heat Treatment via Random Forests Heat treatment is a thermal-processing method involving controlled heating and cooling cycles designed to achieve the desired properties of materials. Among these steps, the cooling rate in heat treatment plays a crucial role, as it significantly influences the resulting material properties. In this paper, we investigated the feasibility of random forests in estimating the cooling-rate parameters for the steel-part heat treatment process. Random forests are particularly appealing in modeling an ensemble of expressive decision trees from which cooling can be modeled and estimated from the interaction of metal features. Our computational experiments using real-world data from industrial-scale operations demonstrated the advantageous properties of random forest regression models, particularly when combined with a random oversampling scheme. We also found that the chemical composition—specifically carbon and chromium content—as well as the weight of the steel parts, are key features that predict the cooling rate of steel parts. Furthermore, our validation using real-world cooling scenarios aligned closely with the practical insights of seasoned operators who routinely recommend cooling parameters for the metal-normalizing process. Our results highlight the effectiveness of the ensemble approach of random forest for practical applicability in industrial-scale heat treatment. Random forest ; Oversampling ; Cooling load ; Ensemble learning ; Key (lock) ; Decision tree Machine Learning in Materials Science ; Machine Learning and ELM ; Stock Market Forecasting Methods
Authors: Fiona Mukherjee | Anye Shi | Lourdes Aoi Latasa | Fengqi You | Nicholas L. Abbott
Source: Science Advances (article, 2025-12-12)
Field: Materials Science — Materials Chemistry

Liquid crystal–driven interfacial ordering of colloidal microplastics: Advancing microplastic characterization below the macroscale Detecting micrometer-scale and smaller plastic particles (microplastics or MPs) in the environment remains an unresolved challenge because they are small, have chemically heterogeneous surfaces as a result of environmental weathering, and are often accompanied by natural organic matter. Here, we advance the characterization of mixtures of MPs by leveraging their spontaneous adsorption and self-organization at liquid crystal (LC)-aqueous interfaces. We show that surface-sensitive interparticle interactions mediated by the LC can drive mixtures of colloidal MPs into assembly patterns that are accurately recognized using computer vision approaches. In particular, we show that we can identify MP composition (polystyrene and polymethyl methacrylate) in complex samples that contain natural organic matter and have been weathered using ultraviolet light. In addition, we explore how computer vision methods classify MP samples, generating fresh insights into the physical processes that control colloidal dynamics and assembly at fluid interfaces. Overall, our results advance efforts to develop characterization methods for colloidal-scale MPs that are broadly accessible (e.g., to citizen scientists). Characterization (materials science) ; Colloid ; Colloidal crystal ; Colloidal particle ; Adsorption ; Ultraviolet ; Soft matter ; Natural (archaeology) Pickering emulsions and particle stabilization ; Material Dynamics and Properties ; Microplastics and Plastic Pollution
Authors: Ehsan Ezzatpour Ghadim | Stephanie Bachmann | Rodrigo S. Corrêa | Dinu Iuga | Joanna F. Collingwood | Peter J. Sadler
Source: ChemistryOpen (article, 2025-10-14)
Field: Chemistry — Spectroscopy

Mineral Speciation for CO <sub>2</sub> Captured by Potassium Hydroxide Capture of greenhouse gases, especially CO<sub>2</sub>, can reduce the effects of global warming and generate valuable minerals as feedstock for industry. Herein, the mineral products formed by capture of atmospheric CO<sub>2</sub> by potassium hydroxide (KOH) in aqueous, aqueous-ethanol, and aqueous-acetone solutions, and aqueous-acetone enriched using solid CO<sub>2</sub> are studied. A multimodal analysis combining single-crystal X-ray diffraction (SCXRD), powder X-ray diffraction (PXRD), with Pawley and Rietveld refinements, and 850 MHz, 1 GHz, and 1.2 GHz <sup>1</sup>H, as well as <sup>13</sup>C, and <sup>39</sup>K nuclear magnetic resonance (NMR), is used to analyze the composition of the mineral products. SCXRD identifies KHCO<sub>3</sub> in space group P2<sub>1</sub>/n (transformable to P2<sub>1</sub>/a) as a product from all reactions. PXRD and NMR data show the presence of both crystalline and amorphous phases in products, predominantly as mixtures of KHCO<sub>3</sub> and K<sub>2</sub>CO<sub>3</sub> and its hydrates, with KOH as a minor component, except for aqueous-ethanol which gives KHCO<sub>3</sub> in high purity. Analysis of complex <sup>1</sup>H NMR data is aided by 2D nuclear Overhauser effect spectroscopy (1 GHz), which characterizes COH···OC interactions. Revealing K<sub>2</sub>CO<sub>3</sub> hydration is aided by deconvolution of ultrahigh-field 28.2 T (56 MHz) <sup>39</sup>K spectra. This multimodal approach provides new insights into the speciation of potassium minerals from CO<sub>2</sub> capture. Potassium hydroxide ; Mineral ; Potassium ; Rietveld refinement ; Powder diffraction ; Spectroscopy ; Amorphous solid ; Hydroxide Advanced NMR Techniques and Applications ; High-pressure geophysics and materials ; Advanced Condensed Matter Physics
Authors: Aleksandr Rodin | Ben A. Olsen | A. Ustyuzhanin | A. Maevskiy
Source: ArXiv.org (preprint, 2025-04-09)
Field: Chemistry — Physical and Theoretical Chemistry

Time-local stochastic equation of motion for solid ionic electrolytes Numerical studies of ionic motion through solid electrolytes commonly involve static nudged-elastic band (NEB) methods or costly \emph{ab initio} molecular dynamics (AIMD). Building on a time-local model of current carrier-electrolyte interaction and incorporating thermal motion, we introduce an approach that is intermediate between the two well-established methodologies by treating the electrolyte as an effective medium that interacts with the mobile particle. Through this coupling, the thermally vibrating electrolyte imparts energy to the charge carriers while also absorbing energy from them due to its own finite elasticity. Using a simple model system, we validate our approach through a series of numerical simulations. Our methodology reproduces both dissipative and diffusive behavior, and helps link microscopic system parameters to measurable macroscopic properties. Electrolyte ; Ionic bonding ; Dissipative system ; Equations of motion ; Series (stratigraphy) ; Work (physics) ; Thermal ; Motion (physics) ; Energy (signal processing) Electrostatics and Colloid Interactions ; Material Dynamics and Properties ; Advanced Battery Materials and Technologies
Authors: João Pereira | Thiago Ferreira de Oliveira | MATHEUS COSTA PEREIRA | ANDERSON PAULO DE PAIVA | Antônio Carlos Ancelotti
Source: Anais ... Encontro Nacional de Engenharia de Produção/Anais do Encontro Nacional de Engenharia de Produção (article, 2025-11-04)
Field: Materials Science — Materials Chemistry

Predição da rugosidade superficial no fresamento de materiais compósitos utilizando aprendizagem de máquina Surface roughness ; Compression (physics) ; Reflectivity Material Selection and Properties ; Erosion and Abrasive Machining ; Rock Mechanics and Modeling
Authors: Florian Bogdain | Sebastian Mai | Leticia González | Oliver Kuehn
Source: ChemRxiv (preprint, 2025-03-20)
Field: Materials Science — Electronic, Optical and Magnetic Materials

BSE@GW-Based Protocol for Spin-Vibronic Quantum Dynamics Using the Linear Vibronic Coupling Model. Formulation and Application to an Fe(II) Compound A protocol for generating potential energy surfaces and performing photoinduced nonadiabatic multidimensional wave packet propagation is presented. The workflow starts with the parameterization of a linear vibronic coupling (LVC) Hamiltonian using the BSE@GW approach. In a second step, the LVC model is used as input for multi-layer multi-configurational time-dependent Hartree (ML-MCTDH) wave packet propagation. To facilitate automated ML tree generation, a spectral clustering algorithm is applied based on a correlation matrix obtained from nuclear coordinate expectation values of a full-dimensional Time-dependent Hartree (TDH) simulation. The performance of the protocol is tested on the photoinduced spin-vibronic dynamics of a transition metal complex, [Fe(cpmp)]$^{+2}$. For this example, it is shown that BSE@GW provides a more robust description of the character of the transitions contributing to the absorption spectrum compared to TD-DFT. Furthermore, the LVC parameterization is tested against explicit calculations of potential energy curves to find the validity of the linear approximation over a wide range of normal mode elongation. Finally, the flexibility of spectral clustering is used to generate different ML trees, resulting in very different numerical efficiencies for ML-MCTDH propagation. In terms of electronic structure and dimensionality, [Fe(cpmp)]$^{+2}$ is a challenging example, suggesting that the new protocol should be applicable to a wide range of systems. Vibronic coupling ; Vibronic spectroscopy ; Coupling (piping) ; Dynamics (music) ; Spin (aerodynamics) ; Physics ; Molecular physics ; Quantum mechanics ; Materials science ; Excited state Magnetism in coordination complexes ; Advanced NMR Techniques and Applications ; Electron Spin Resonance Studies
Authors: Anil Kumar Jangid | Rahul Dev | Shikha Sharma | Payal Bhatnagar
Source: Current Research in Pharmaceutical Sciences (article, 2025-07-08)
Field: Materials Science — Biomaterials

REVOLUTIONIZING THERAPEUTICS: ADVANCES, CHALLE- NGES, AND FUTURE HORIZONS IN CONTROLLED RELEASE DRUG DELIVERY SYSTEMS Revolutionizing modern therapeutics, controlled-release drug delivery systems (CRDDS) provide sustained release of a drug over extended periods, improve patient compliance in drug treatment, and improve the therapeutic efficacy. In consequence, these systems are meant to overcome the limitations of traditional drug delivery, namely the high frequency of dosing and drug concentration fluctuations. This review will examine the main strategies for CRDDS, such as diffusion-controlled, dissolution-controlled, osmotic, and stimuli-responsive systems as well as the materials, including polymers, lipids and hydrogels used to increase stability, bioavailability and release profiles. However, CRDDS have the promise of great advantages, but come with challenges in formulation, scalability, stability, and regulatory compliance. The advances in personalized medicine and targeted therapies are discussed in terms of emerging trends such as 3D printing, nanotechnology and smart drug delivery systems. Moreover, biodegradable and ecofriendly materials are becoming the focus of attention for their role in drug delivery. It also reviews ongoing research, recent patents and artificial intelligence applications in optimizing CRDDS design and functionality. In general, this article covers the current use of CRDDS, their challenges and future perspectives in drug delivery. Keywords: Drug delivery, Nanotechnology, Polymers, Controlled release, Biodegradable, Smart drug delivery, Personalized medicine Drug delivery ; New horizons ; Medicine ; Nanotechnology ; Engineering ; Materials science Nanoparticle-Based Drug Delivery ; Drug Solubulity and Delivery Systems ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Nadir Driza | Asma Elgade
Source: Alqalam Journal of Science (article, 2025-09-09)
Field: Materials Science — Materials Chemistry

Raman Light Scattering Study of the Isotopic Construction Effects on the Lattice properties -TO and LO Phonon modes- of CuCl This work expands on our research on isotope effects on phonons to include compound semiconductors. In this article, we concentrate our study on variation of the lattice properties such as lattice dynamics and electronic structure due to the effects of isotope substitution on the CuCl Raman spectra. We fulfilled that by examined 35Cl, 37Cl, 63Cu and 65Cu. Unlike elemental semiconductors, compounds whose constituents are isotopically substituted have a substantial dependence on the phonon branch and wave vector q for changes in phonon frequencies and atomic displacements. In the case of CuCl, the substitution of heavy or light atoms has distinct effects on the acoustic and visual branches of the phonon dispersion relations. The significant mass difference between copper and chlorine causes the eigenvectors of the acoustic vibrations to be dominated by copper displacements, while the optic vibrations are dominated by chlorine displacements. Consequently, the phonon frequencies in the visual and acoustic branches can be altered nearly independently, especially at the X point, by employing isotope replacement. At low temperatures, this enables us to examine the effectiveness of the anharmonic decay channels of Γ point optical phonons into lower-lying acoustic bands. Phonon ; Raman scattering ; Raman spectroscopy ; Anharmonicity ; Lattice (music) ; Kinetic isotope effect ; Copper ; Isotope ; Atomic mass ZnO doping and properties ; Copper-based nanomaterials and applications