jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Alexander Chidara | Kai Cheng | David Gallear
Source: Polymers (article, 2025-09-26)
Field: Materials Science — Biomaterials

Ontology-Based Modelling and Analysis of Sustainable Polymer Systems: PVC Comparative Polymer and Implementation Perspectives This study develops an ontology-based decision support framework to enhance sustainable polymer recycling within the circular economy. The framework, constructed in Protégé (OWL 2), systematically captures polymer categories with emphasis on polyethylene terephthalate (PET), polylactic acid (PLA), and rigid polyvinyl chloride (PVC) as well as recycling processes, waste classifications, and sustainability indicators such as carbon footprint. Semantic reasoning was implemented using the Semantic Web Rule Language (SWRL) and SPARQL Protocol and RDF Query Language (SPARQL) to infer optimal material flows and sustainable pathways. Validation through a UK industrial case study confirmed both the framework's applicability and highlighted barriers to large-scale recycling, including performance gaps between virgin and recycled polymers. The comparative analysis showed carbon footprints of 2.8 kg CO<sub>2</sub>/kg for virgin PET, 1.5 kg CO<sub>2</sub>/kg for PLA, and 2.1 kg CO<sub>2</sub>/kg for PVC, underscoring material-specific sustainability challenges. Validation through a UK industrial case study further highlighted additive complexity in PVC as a major barrier to large scale recycling. Bibliometric and thematic analyses conducted in this study revealed persistent gaps in sustainability metrics, lifecycle assessment, and semantic support for circular polymer systems. By integrating these insights, the proposed framework provides a scalable, data-driven tool for evaluating and optimising polymer lifecycles, supporting industry transitions toward resilient, circular, and net-zero material systems. Sustainability ; Life-cycle assessment ; Polyvinyl chloride ; SPARQL ; Polyethylene terephthalate ; Polymer ; Polylactic acid biodegradable polymer synthesis and properties ; Microplastics and Plastic Pollution ; Sustainable Supply Chain Management
Authors: Zhongru Ren | Hongcheng Yin | Changliang Zhang | Ming Fang | Yan Lü | Xin Sun | Junzhe He | Xiaofang Liu
Source: Nano Research (article, 2025-07-25)
Field: Chemistry — Organic Chemistry

Bio-inspired flexible composite multilayer material: Cross-scale topological assembly for infrared-radar compatible detection suppression The increasing demand for multi-spectral compatibility in complex electromagnetic environments has highlighted the critical challenge of reconciling infrared detection suppression with broadband microwave absorption. Inspired by the multilevel gradient structure of bamboo and the dynamic nanocrystal spacing modulation in chameleon skin, a flexible composite multilayer material is fabricated through a cross-scale topological assembly method. By constructing a functional coupling architecture comprising an infrared low-emissivity pattern layer, a broadband impedance matching layer, and a resistive frequency selective surface layer, effective energy suppression across both the infrared and radar spectra is achieved. The optimized structure demonstrates a reflection loss below −10 dB across a broad frequency range from 4.06 to 20.68 GHz, while maintaining an average infrared emissivity below 0.21 in the 8–14 μm wavelength range. Moreover, this structure exhibits high mechanical strength, a simple fabrication process, and stable performance, making it a promising candidate for next-generation multi-spectral detection applications. Composite number ; Infrared ; Materials science ; Radar ; Scale (ratio) ; Nanotechnology ; Optoelectronics ; Composite material ; Aerospace engineering ; Optics ; Engineering ; Physics Polydiacetylene-based materials and applications ; Advanced Materials and Mechanics ; Metamaterials and Metasurfaces Applications
Authors: Md. Rezwan Ahmed | Oishi Jyoti | Pritu Parna Sarkar | Mohammod Abdul Motin | Md. Selim Habib | Md. Samiul Habib
Source: Scientific Reports (article, 2025-12-22)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Accurate prediction of geometrical parameters of an ultra-broadband metamaterial absorber using machine learning In this paper, we systematically demonstrate the design and analysis of a new type of ultra-broadband tunable metamaterial perfect absorber (MPA) comprising a top vanadium dioxide (VO2) based patterned resonating patch, a continuous metallic film at the bottom, and an intermediate dielectric substrate having a thickness of only 0.18 $$\lambda$$ at the center working frequency. The simulation results reveal that the absorber achieves a bandwidth of 7.26 THz, ranging from 5.40 THz to 12.66 THz, with more than 90% absorptance and an average absorption of 98.21% under normal incidence of the incoming THz wave. Furthermore, absorptance exceeding 99% is achieved between 6.25 THz and 11.30 THz (5.05 THz bandwidth), demonstrating superior performance compared to existing broadband absorbers. The high absorption efficiency is attributed to the electric and magnetic dipole resonance, as illustrated through the electric field and vector surface current distribution at different frequencies. An equivalent RLC circuit model is developed using the least squares method, showing strong agreement with full-wave numerical simulations. However, designing metamaterial absorber requires extensive analysis of absorption spectra across a broad range of structural parameters – a computationally expensive process due to the complex interplay of impedance matching and electric field coupling. To overcome this challenge, we introduce a machine learning (ML)-based approach utilizing the Random Forest (RF) algorithm to predict absorption bandwidth and optimize structural parameters, significantly reducing computational time and spectral analyses. The RF model achieves considerably high accuracy, predicting an ultra-broadband absorption bandwidth of 7.26 THz with minimal error. We show that predicted and simulated results show excellent agreement, with negligible deviations. In addition, the terahertz absorber stably maintains more than 90% absorptance for both transverse electric (TE) and transverse magnetic (TM) waves up to 50° and due to its rotationally symmetric structure the proposed absorber is easy to fabricate and ensures complete polarization insensitivity. With its strong performance, the proposed MPA offers considerable potential for applications in terahertz modulation, switching, imaging, and biochemical sensing. Metamaterial ; Terahertz radiation ; Bandwidth (computing) ; Absorptance ; Metamaterial absorber ; Electric field ; Impedance matching ; Dielectric ; Absorption (acoustics) Metamaterials and Metasurfaces Applications ; Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies
Authors: Chris J. Benmore
Source: Glass Europe (article, 2025-01-22)
Field: Materials Science — Ceramics and Composites

The Structure of Glassy and Liquid Sulfur Revisited High energy x-ray experiments have been performed on liquid and glassy sulfur over a wide temperature range. Heating the elastic quenched glass above -9 ºC and supercooling liquid sulfur below 51 ºC both resulted in crystallization to monoclinic sulfur. The average coordination number of the first shell in glassy sulfur determined from the pair distribution function is found to be 1.90±0.05. This result is in good agreement with previous neutron and x-ray pair distribution function studies, and lends support to the recent proposal that there are a significant number of short chains in the low temperature liquid upon melting. Also, a non-negligible coordination number of 0.20±0.04 is found in the interstitial region between the first and second shells in glassy sulfur, similar to that found in the liquid. An increase in the third peak in the glassy pair distribution function at 4.47 Å associated with S8-rings indicates the percentage is higher in the quenched glass compared to the stable liquid. This casts doubt on previous estimations of the percentage of S8-rings present upon melting. Sulfur ; Materials science ; Chemistry ; Metallurgy Glass properties and applications ; High-pressure geophysics and materials ; Material Dynamics and Properties
Authors: Apurba Taye | Uddhab Kalita | Polash P. Dutta | Dhrubajyoti Haloi
Source: Packaging Technology and Science (article, 2025-06-17)
Field: Materials Science — Biomaterials

From Waste to Wrap: Pistachio Shell Powder–Reinforced Chitosan Biocomposite for Eco‐Friendly Packaging ABSTRACT Chitosan (Cs) is a biopolymer which has exceptional biocompatibility, biodegradability and antibacterial properties. On the other hand, pistachio shell (Ps) powder is environmentally friendly, sustainable, biodegradable and non‐toxic. Therefore, the combination of these two biomaterials may lead to a biocomposite with numerous attractive properties. In this work, we report the preparation and characterization of a series of Cs/Ps biocomposites. Films of these biocomposites were prepared by solvent casting and were examined by FT‐IR, XRD, DSC, TGA, SEM and UTM analyses. Analyses were conducted to evaluate their moisture content, water vapour permeability (WVP), swelling percentage and transparency for packaging applications. The composite's mechanical properties improve the most when it is loaded with 20% Ps. The high moisture content of 14.39% observed in the pure Cs film has gone down to 10.76% in its composite film Cs/Ps 40 . The biocomposite films' WVP properties are significantly influenced by the amount of pistachio filler used. At a specified time, the pure Cs film experiences the highest swelling percentage, while the Cs/Ps 40 film experiences the least swelling percentage. It has also been observed that the thermal stability of biocomposite films gradually improves with the filler amount. The thermal stability of the biocomposite film Cs/Ps 40 was higher than that of any prepared films. The evaluated properties of these films indicate that these biocomposites have the potential to be used in food packaging. Biocomposite ; Materials science ; Food packaging ; Thermal stability ; Chitosan ; Composite material ; Swelling ; Composite number ; Biodegradation ; Biopolymer ; Environmentally friendly ; Moisture ; Chemical engineering ; Polymer ; Food science ; Chemistry ; Organic chemistry Nanocomposite Films for Food Packaging ; Natural Fiber Reinforced Composites ; biodegradable polymer synthesis and properties
Authors: Tore Brinck
Source: Pure and Applied Chemistry (article, 2025-08-21)
Field: Chemistry — Physical and Theoretical Chemistry

Molecular electrostatic potential as a guide to intermolecular interactions: challenge of nucleophilic interaction sites Abstract The surface electrostatic potential ( V S ( r )) is an established tool for characterization and prediction of sites susceptible to participate in intermolecular interactions. In particular, maxima in V S ( r ) ( V S,max ) have been shown to reflect σ-holes and π-holes, including the electrophilic sites of hydrogen bond donors and halogen bond donors as well as traditional Lewis acids. The characterization of nucleophilic sites on Lewis bases has proven more difficult, and surface minima ( V S,min ) often fail to predict the angular direction of interactions with electrophiles. In this study, it is demonstrated that the predictive capacity of spatial minima in the electrostatic potential ( V min ) is much higher than V S,min for interactions with neutral electrophiles, such as HF, BF 3 , BrF and LiF. V S,min , on the other hand, is better for interactions with ionic electrophiles, such as Li + . This latter observation can be explained by that the position of the V S,min corresponds to the site on the surface that has strongest electrostatic interaction with a point charge. V min performs better for interactions with neutral electrophiles, as the nucleophile interacts electrostatically with the entire charge distribution of the electrophile and not only with that of its electrophilic site; the charge distribution of a neutral electrophile can be approximated by a dipole or a superposition of dipoles, and a dipole interacting with a Lewis base (nucleophile) has its lowest electrostatic energy when it is pointed along the direction of strongest electrostatic field, which generally coincides with the direction of the V min . Chemistry ; Intermolecular force ; Nucleophile ; Electrostatic interaction ; Computational chemistry ; Electrostatics ; Intermolecular interaction ; Chemical physics ; Nanotechnology ; Organic chemistry ; Molecule ; Physical chemistry ; Catalysis Crystallography and molecular interactions ; Chemical Thermodynamics and Molecular Structure ; Molecular Spectroscopy and Structure
Authors: Chunyu Li | Alejandro Strachan
Source: Journal of Applied Physics (article, 2025-07-15)
Field: Materials Science — Ceramics and Composites

Spall strength of symmetric tilt grain boundaries in 6H silicon carbide Characterizing microstructural effects on the dynamical response of materials is challenging due to the extreme conditions and the short timescales involved. For example, little is known about how grain boundary characteristics affect spall strength. This study explores 6H-SiC bicrystals under shock waves via large-scale molecular dynamics simulations. We focused on symmetric tilt grain boundaries with a wide range of misorientations and found that spall strength and dynamical fracture surface energy are strongly affected by the grain boundary microstructure, especially the excess free volume. Grain boundary energy also plays a considerable role. As expected, low-angle grain boundaries tend to have higher spallation strengths. We also extracted cohesive models for the dynamical strength of bulk systems and grain boundaries that can be used in continuum simulations. Silicon carbide ; Grain boundary ; Materials science ; Tilt (camera) ; Carbide ; Silicon ; Spall ; Metallurgy ; Composite material ; Microstructure ; Geometry ; Mathematics Advanced ceramic materials synthesis ; Advanced Surface Polishing Techniques ; Silicon Carbide Semiconductor Technologies
Authors: Lin Guo | Yinchu Wang | Zilong Liu | Xingchuang Xiong | Fengyi Zhang
Source: Preprints.org (preprint, 2025-01-15)
Field: Chemistry — Spectroscopy

EQLC-EC: An Efficient Voting Classifier for 1D Mass Spectrometry Data Classification Mass spectrometry (MS) data presents challenges for machine learning (ML) classification due to its high dimensionality, complex feature distributions, batch effects, and intensity discrepancies, often hindering model generalization and efficiency. To address these issues, this study introduces the Efficient Quick 1D Lite CNN Ensemble Classifier (EQLC-EC), integrating 1D convolutional networks with reshape layers and dual voting mechanisms for enhanced feature representation and classification performance. Validation was performed on five publicly available MS datasets, each featured in high-impact publications. EQLC-EC underwent comprehensive evaluation against classical machine learning (ML) models (e.g., support vector machine [SVM], random forest) and the leading deep learning methods reported in these studies. EQLC-EC demonstrated dataset-specific improvements, including enhanced classification accuracy (1%-5% increase) and reduced standard deviation (1%-10% reduction). Performance differences between soft and hard voting mechanisms were negligible (&amp;lt;1% variation in accuracy and standard deviation). EQLC-EC presents a powerful and efficient tool for MS data analysis with potential applications across metabolomics and proteomics. Voting ; Classifier (UML) ; Computer science ; Mass spectrometry ; Artificial intelligence ; Pattern recognition (psychology) ; Chromatography ; Chemistry ; Political science Analytical Chemistry and Chromatography ; Metabolomics and Mass Spectrometry Studies ; Advanced Chemical Sensor Technologies
Authors: Dimple M. D
Source: Nanoscale Reports (article, 2025-06-10)
Field: Materials Science — Biomaterials

AI-guided design of nanocarriers for targeted drug delivery in tumors Targeted drug delivery represents a critical advancement in cancer treatment, offering improved efficacy and minimized systemic toxicity. Nanocarriers have emerged as promising vehicles for site-specific delivery of anticancer drugs due to their customizable physicochemical properties. However, designing nanocarriers capable of effective tumor targeting remains a complex challenge, given the diverse variables involved in tumor biology, drug kinetics, and nanoparticle interactions with biological environments. The integration of artificial intelligence (AI) into the nanocarrier design process is transforming the landscape of drug delivery research. This article explores the use of AI, particularly machine learning and deep learning models, in guiding the rational design of nanocarriers for tumor-targeted drug delivery. A framework is proposed for utilizing AI tools to optimize design parameters, predict biological interactions, and improve formulation outcomes, thus accelerating the development of effective cancer therapies. Nanocarriers ; Drug delivery ; Targeted drug delivery ; Drug ; Medicine ; Nanotechnology ; Pharmacology ; Materials science Nanoparticle-Based Drug Delivery ; Graphene and Nanomaterials Applications ; Supramolecular Self-Assembly in Materials
Authors: Khaled Younes | Semaan Amine | Christina El Sawda | Samer El-Zahab | Jack Arayro | Rabih Mezher | Jalal Halwani | Baghdad Ouddane | Eddie Gazo Hanna
Source: Sustainability (article, 2025-05-15)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Principal Component Analysis of Biomass-Derived Carbon Aerogels: Unveiling Key Performance Factors for Supercapacitor Applications The demand for sustainable energy storage solutions has led to increased interest in biomass-derived carbon aerogels as electrode materials for supercapacitors. These materials offer a high surface area, tunable porosity, and excellent electrochemical properties while utilizing renewable and waste biomass sources. This study evaluates the electrochemical performance of various biomass-based carbon aerogels, including those derived from cellulose, lignin, chitosan, and biomass waste, to identify key factors influencing supercapacitor efficiency. Principal Component Analysis (PCA) is employed to systematically analyze the relationships between structural and electrochemical properties, such as the specific surface area, specific capacitance, capacity retention, rate capability, energy density, and power density. The PCA results indicate that the first two principal components (PC1 and PC2) explain 58.20% of the total variance, with capacity retention (26.22%), energy density (19.55%), and specific capacitance (18.48%) identified as the most critical quantitative factors influencing supercapacitor performance. Chitosan-derived carbon aerogels exhibit superior capacitance and energy density, with a specific capacitance reaching up to 1074 F/g and energy density of 40.18 Wh/kg, whereas lignin-based aerogels demonstrate a high structural stability and capacity retention (up to 97.4%). Biomass waste-derived aerogels, despite their lower performance (176–298.6 F/g capacitance, 81.6–91.7% retention), provide cost-effective and environmentally sustainable alternatives. This quantitative analysis offers valuable insights into the rational design of high-performance, biomass-based aerogels, contributing significantly to the development of sustainable energy storage technologies. Supercapacitor ; Principal component analysis ; Key (lock) ; Biomass (ecology) ; Component (thermodynamics) ; Carbon fibers ; Materials science ; Environmental science ; Process engineering ; Chemical engineering ; Chemistry ; Computer science ; Engineering ; Electrode ; Composite material ; Composite number ; Capacitance ; Physics ; Geology Supercapacitor Materials and Fabrication ; Aerogels and thermal insulation
Authors: Seungjai Won | Jungyoon Kim | Young‐Taek Oh | Taewon Kim | Seungman Choi | Byunggi Kim | Hongki Yoo | Seungwoo Kim | Young‐Jin Kim
Source: PhotoniX (article, 2025-11-06)
Field: Materials Science — Surfaces, Coatings and Films

Programmable structured DUV illumination by coherent harmonic generation at crystalline solids for nanometer-resolution inspection of periodic samples Abstract The continued narrowing of transistor pitch in semiconductor chips has boosted the demand for deep-ultraviolet (DUV, λ &lt; 280 nm)-based high-resolution optical inspection and metrology. However, the lack of a beam control device for DUV wavelength due to the significant UV absorption in most optical materials has hindered the handy implementation of conventional high-resolution metrology techniques such as structured illumination microscopy (SIM) to the DUV regime. Here, we present a programmable DUV structured illumination for nanometer-resolution pitch and displacement inspection of periodic samples enabled by nonlinear third-harmonic generation. By manipulating a spatial phase of the near-infrared (NIR, λ = 800 nm) driving beam that is incident on crystalline solids, the emitted third harmonic beam at DUV (λ = 266 nm) can be spatially controlled so as to form a high-visibility sinusoidal distribution with a real-time adjustable pitch and orientation angle. The angle-tunable DUV structured beam allows observation of low-visibility periodic sample information in high-visibility frequency-down-converted Moiré patterns, with a magnification factor of up to 70 times. By analyzing the Moiré pattern pitch and orientation angle, the sample periods of 277.8 nm and 416.7 nm were reconstructed with an error of 1.9% (5.4 nm) and 0.5% (2.1 nm), respectively. Furthermore, a 20.0 nm lateral shift of the periodic sample – below Abbe’s diffraction limit – was measured with a repeatability of 5.3 nm via monitoring of the magnified Moiré pattern. Our DUV structured illumination will enable high-resolution monitoring of semiconductor processes such as transistor pitch variation and mask alignment. Metrology ; Beam (structure) ; Diffraction ; Wavelength ; Dot pitch ; Repeatability ; Harmonic ; Holography ; Phase (matter) Optical Coatings and Gratings ; Advanced X-ray Imaging Techniques ; Near-Field Optical Microscopy