jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Borun Das | Andrew J. Peters | Guoqiang Li | Xiali Hei
Source: Journal of Polymer Science (article, 2025-01-17)
Field: Materials Science — Polymers and Plastics

Generative Design of Thermoset Shape Memory Polymers Driven by Chemical Group: A Conditional Variational Autoencoder Approach ABSTRACT The discovery of novel thermoset shape memory polymers (TSMPs) for additive manufacturing can be accelerated through the use of a deep‐generative algorithm, minimizing the need for laborious traditional laboratory experiments. This study is the first to introduce an innovative approach that uses a deep generative learning model, namely the conditional variational autoencoder (CVAE), to discover novel TSMPs with lower glass transition temperature () and high recovery stress values (). In this study, specific chemical groups, such as epoxy, amine, thiol, and vinyl, are integrated as constraints to generate novel TSMPs while preserving the essential reaction properties. To address the challenges posed by a small dataset, the CVAE model is used with graph‐extracted features. Unlike previous studies focused on single‐polymer systems, this research extends to two‐monomer samples, discovering 22 novel TSMPs. This approach has practical implications in additive manufacturing, biomedical devices, aerospace, and robotics for the discovery of novel samples from limited data. Autoencoder ; Thermosetting polymer ; Group (periodic table) ; Generative grammar ; Shape-memory polymer ; Artificial intelligence ; Polymer ; Computer science ; Materials science ; Biological system ; Mathematics ; Natural language processing ; Chemistry ; Organic chemistry ; Composite material ; Artificial neural network ; Shape-memory alloy ; Biology Polymer composites and self-healing ; Photopolymerization techniques and applications ; Epoxy Resin Curing Processes
Authors: Yahya Saleh | Álvaro Fernández Corral | Emil Vogt | Armin Iske | Jochen Küpper | Andrey Yachmenev
Source: Journal of Chemical Theory and Computation (article, 2025-05-15)
Field: Chemistry — Spectroscopy

Computing Excited States of Molecules Using Normalizing Flows Calculations of highly excited and delocalized molecular vibrational states are computationally challenging tasks, which strongly depend on the choice of coordinates for describing vibrational motions. We introduce a new method that leverages normalizing flows, i.e, parametrized invertible functions, to learn optimal vibrational coordinates that satisfy the variational principle. This approach produces coordinates tailored to the vibrational problem at hand, significantly increasing the accuracy and enhancing the basis set convergence of the calculated energy spectrum. The efficiency of the method is demonstrated in calculations of the 100 lowest excited vibrational states of H<sub>2</sub>S, H<sub>2</sub>CO, and HCN/HNC. The method effectively captures the essential vibrational behavior of molecules by enhancing the separability of the Hamiltonian and hence allows for an effective assignment of approximate quantum numbers. We demonstrate that the optimized coordinates are transferable across different levels of basis set truncation, enabling a cost-efficient protocol for computing vibrational spectra of high-dimensional systems. Excited state ; Computer science ; Molecule ; Data science ; Physics ; Atomic physics ; Quantum mechanics Spectroscopy and Laser Applications ; Laser-Matter Interactions and Applications ; Spectroscopy and Quantum Chemical Studies
Authors: Kamyar Barakati | Yu Liu | Christopher T. Nelson | Maxim Ziatdinov | Xiaohang Zhang | Ichiro Takeuchi | Sergei V. Kalinin
Source: Advanced Materials (article, 2025-06-18)
Field: Materials Science — Materials Chemistry

Reward Driven Workflows for Unsupervised Explainable Analysis of Phases and Ferroic Variants From Atomically Resolved Imaging Data Rapid progress in aberration corrected electron microscopy necessitates development of robust methods for the identification of phases, ferroic variants, and other pertinent aspects of materials structure from imaging data. While unsupervised methods for clustering and classification are widely used for these tasks, their performance can be sensitive to hyperparameter selection in the analysis workflow. In this study, the effects of descriptors and hyperparameters are explored on the capability of unsupervised ML methods to distill local structural information, exemplified by the discovery of polarization and lattice distortion in Sm - dopped BiFeO<sub>3</sub> (BFO) thin films. It is demonstrated that a reward-driven approach can be used to optimize these key hyperparameters across the full workflow, where rewards are designed to reflect domain wall continuity and straightness, ensuring that the analysis aligns with the material's physical behavior. This approach allows the discovery of local descriptors that are best aligned with the specific physical behavior, providing insight into the fundamental physics of materials. The reward driven workflow is further extended to disentangle structural factors of variation via an optimized variational autoencoder (VAE). Finally, the importance of well-defined rewards is explored as a quantifiable measure of the success of the workflow. Hyperparameter ; Workflow ; Autoencoder ; Cluster analysis ; Computer science ; Unsupervised learning ; Artificial intelligence ; Materials science ; Pattern recognition (psychology) ; Data mining ; Machine learning ; Deep learning ; Database Machine Learning in Materials Science ; Geophysical and Geoelectrical Methods ; Hydrocarbon exploration and reservoir analysis
Authors: Etinosa Osaro | Matthew LaCapra | Yamil J. Colón
Source: The Journal of Physical Chemistry C (article, 2025-05-16)
Field: Chemistry — Inorganic Chemistry

Harmonizing Adsorption and Diffusion in Active Learning Campaigns of Gas Separations in a MOF This study establishes an active learning (AL) framework designed to enhance the prediction of selectivity in the metal–organic framework (MOF) CuBTC by addressing the adsorption and diffusion mechanisms essential for gas separation applications. Traditional methods of predicting gas selectivity across broad pressure, temperature, and composition (PTX) conditions face considerable computational demands, particularly when simulating both adsorption and diffusion in porous materials. We tackled this challenge by integrating Gaussian Process (GP) models with grand canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulations, applying AL to iteratively select data points exclusively based on the highest model uncertainty (emphasizing exploration), and others schemes, to systematically improve prediction accuracy across diverse conditions. We evaluated several AL strategies tailored to two distinct molecular-level phenomena involved in gas separations: adsorption and diffusion. Specifically, adsorption-based selectivity prediction methods employed AL to preferentially select data points characterized by high uncertainty in adsorption predictions. In contrast, diffusion-based selectivity prediction methods directed AL toward regions exhibiting high uncertainty in diffusion predictions. These approaches included direct prediction of selectivity as well as propagation-based methods, where selectivity uncertainty was calculated from individual component uncertainties in adsorption or diffusion predictions. The culmination of this exploration is an end-to-end (E2E) framework that integrates adsorption and diffusion modeling within a single AL-driven data-labeling process. In this framework, uncertainty in either adsorption or diffusion predictions guides data selection, enabling more precise model training across adsorption and diffusion. Results indicate that the diffusion-focused E2E scheme yields the highest predictive accuracy and a more efficient process. This approach minimizes redundant sampling and improves the efficiency of data acquisition across adsorption and diffusion models. Adsorption ; Diffusion ; Gaseous diffusion ; Chemical engineering ; Chemistry ; Materials science ; Physical chemistry ; Thermodynamics ; Physics ; Engineering Metal-Organic Frameworks: Synthesis and Applications ; Gas Sensing Nanomaterials and Sensors ; Catalytic Processes in Materials Science
Authors: Ruisi Qiu | Xuan Gao | Yun Xiao | Daquan Yu | Bing Wang
Source: Separation and Purification Technology (article, 2025-05-06)
Field: Materials Science — Materials Chemistry

Efficient adsorption of sodium p-perfluorous nonenoxybenzenesulfonate by environmentally friendly self-floating amino ordered mesoporous silica: Energy-efficient solid–liquid separation and enhanced adsorption performance Adsorption ; Environmentally friendly ; Chemical engineering ; Mesoporous material ; Mesoporous silica ; Chemistry ; Sodium alginate ; Chromatography ; Materials science ; Organic chemistry ; Sodium ; Catalysis ; Engineering Mesoporous Materials and Catalysis ; Adsorption and biosorption for pollutant removal ; Covalent Organic Framework Applications
Authors: Srilakshmi Jeyaraman | Dmitri L. Danilov | Peter H. L. Notten | Udaya Bhaskar Reddy Ragula | R. Vaira Vignesh | Thirugnasambandam G. Manivasagam
Source: Energies (article, 2025-07-23)
Field: Materials Science — Materials Chemistry

Influence of Ni and Nb Addition in TiVCr-Based High Entropy Alloys for Room-Temperature Hydrogen Storage TiVCr-based alloys are well-explored body-centered cubic (BCC) materials for hydrogen storage applications that can potentially store higher amounts of hydrogen at moderate temperatures. The challenge remains in optimizing the alloy-hydrogen stability, and several transition elements have been found to support the reduction in the hydride stability. In this study, Ni and Nb transition elements were incorporated into the TiVCr alloy system to thoroughly understand their influence on the (de)hydrogenation kinetics and thermodynamic properties. Three different compositions, (TiVCr)95Ni5, (TiVCr)90 Ni10, and (TiVCr)95Ni5Nb5, were prepared via arc melting. The as-prepared samples showed the formation of a dual-phase BCC solid solution and secondary phase precipitates. The samples were characterized using hydrogen sorption studies. Among the studied compositions, (TiVCr)90Ni10 exhibited the highest hydrogen absorption capacity of 3 wt%, whereas both (TiVCr)95Ni5 and (TiVCr)90Ni5Nb5 absorbed up to 2.5 wt% hydrogen. The kinetics of (de)hydrogenation were modeled using the JMAK and 3D Jander diffusion models. The kinetics results showed that the presence of Ni improved hydrogen adsorption at the interface level, whereas Nb substitution enhanced diffusion and hydrogen release at room temperature. Thus, the addition of Ni and Nb to Ti-V-Cr-based high-entropy alloys significantly improved the hydrogen absorption and desorption properties at room temperature for gas-phase hydrogen storage. Hydrogen storage ; Materials science ; Hydrogen ; Metallurgy ; High entropy alloys ; Thermodynamics ; Chemical engineering ; Chemistry ; Alloy ; Physics ; Engineering Hydrogen Storage and Materials ; High Entropy Alloys Studies ; Advanced materials and composites
Authors: Chandandeep Kaur Behl | Archana Thakur
Source: Journal of Inorganic and Organometallic Polymers and Materials (article, 2025-05-03)
Field: Chemistry — Inorganic Chemistry

Investigating the Functionality of a Cobalt Metal‒Organic Framework for Dye Adsorption, Antimicrobial and Cytotoxicity Activity Cobalt ; Adsorption ; Cytotoxicity ; Antimicrobial ; Metal ; Chemistry ; Metal-organic framework ; Nuclear chemistry ; Combinatorial chemistry ; Organic chemistry ; Inorganic chemistry ; Biochemistry Metal-Organic Frameworks: Synthesis and Applications ; Adsorption and biosorption for pollutant removal ; X-ray Diffraction in Crystallography
Authors: Mateusz Pęśko | Anna Masek
Source: Polymers (review, 2025-08-23)
Field: Materials Science — Polymers and Plastics

Plant-Based Biofillers for Polymer Composites: Characterization, Surface Modification, and Application Potential The mounting global concern regarding the accumulation of plastic waste underscores the necessity for the development of innovative solutions, with particular emphasis on the incorporation of plant-based biofillers into polymer composites as a sustainable alternative to conventional materials. This review provides a comprehensive and structured overview of the recent progress (2020-2025) in the integration of plant-based biofillers into both thermoplastic and thermosetting polymer matrices, with a focus on surface modification techniques, physicochemical characterization, and emerging industrial applications. Unlike the prior literature, this work highlights the dual environmental and material benefits of using plant-derived fillers, particularly in the context of waste valorization and circular material design. By clearly identifying a current research gap-the limited scalability and processing efficiency of biofillers-this review proposes a strategy in which plant-derived materials function as key enablers for sustainable composite development. Special attention is given to extraction methods of lignocellulosic fillers from renewable agricultural waste streams and their subsequent functionalization to improve matrix compatibility. Additionally, it delineates the principal approaches for biofiller modification, demonstrating how their properties can be tailored to meet specific needs in biocomposite production. This critical synthesis of the state-of-the-art literature not only reinforces the role of biofillers in reducing dependence on non-renewable fillers but also outlines future directions in scaling up their use, improving durability, and expanding performance capabilities of sustainable composites. Overall, the presented analysis contributes novel insights into the material design, processing strategies, and potential of plant biofillers as central elements in next-generation green composites. Characterization (materials science) ; Composite material ; Materials science ; Polymer ; Surface modification ; Nanotechnology ; Chemical engineering ; Engineering Natural Fiber Reinforced Composites ; biodegradable polymer synthesis and properties ; Advanced Cellulose Research Studies
Authors: Palkaran Sethi | Sanghamitra Barman | Soumen Basu
Source: Materials Advances (article, 2025-01-01)
Field: Chemistry — Organic Chemistry

CuBTC–clay composites with tunable ratios for antibiotic removal: unraveling isotherm, kinetic, and thermodynamic study CuBTC–clay composites with tunable ratios demonstrate high tetracycline removal efficiency through efficient adsorption, exhibiting excellent stability, reusability, and favorable isotherm–kinetic behavior. Reusability ; Adsorption ; Kinetic energy ; Materials science ; Composite material ; Chemical engineering ; Chemical stability ; Degradation (telecommunications) ; Chemistry ; Physical chemistry Nanomaterials for catalytic reactions ; Covalent Organic Framework Applications ; Adsorption and biosorption for pollutant removal
Authors: Yifeng Huang | Lanyu Ma | Zhimin Huang | Wenqin Lai | Yihua Zheng | Mengxue Xu | Aimei Yang | Lunsu Liang | Zijie Lu | Juying Zhou | Yong Zhu
Source: Scientific Reports (article, 2025-01-02)
Field: Chemistry — Organic Chemistry

Effect of stearic acid and sodium stearate on hydrophobicity of nano calcium carbonate and mechanism of water vapor adsorption It is essential to understand the modification mechanism of hydrophobicity nano-CaCO<sub>3</sub> to their potential application in different fields of chemistry. However, the water absorption of hydrophobicity nano-CaCO<sub>3</sub> is seldom studied. In this study, Raman, BET and TGA experiments were performed on nano-CaCO<sub>3</sub> samples to obtain surfactants contents and microstructure characteristics. SEM, TEM and DSL results showed that the nano-CaCO<sub>3</sub> modified by stearic acid and sodium stearate had larger particle size and smaller nanoclusters. In the water vapor adsorption test, the order of saturation adsorption capacity was nano-CaCO<sub>3</sub>(PCC) > nano-CaCO<sub>3</sub> modified by sodium stearate(PCC-Sa-Na) > nano-CaCO<sub>3</sub> modified by stearic acid(PCC-Sa), and XPS results showed that PCC-Sa had more hydrophobic groups than PCC-Sa-Na, which also explained that the hydrophobicity of PCC modified by stearic acid and sodium stearate was improved by increasing the hydrophobic bond on the surface of CaCO<sub>3</sub> and reducing the hydrophilic groups. Our analysis provides a path for the design and the prediction of hydrophobicity of nano-CaCO<sub>3</sub>, which is the main focus of our work. Stearic acid ; Adsorption ; Calcium stearate ; Chemistry ; Chemical engineering ; Stearate ; Sodium ; Nano- ; Calcium carbonate ; Inorganic chemistry ; Materials science ; Organic chemistry Surfactants and Colloidal Systems ; Enhanced Oil Recovery Techniques ; Pickering emulsions and particle stabilization
Authors: Daniel R. Darby | Andrew J. Greenlee | Ren H. Bean | David C. Fairchild | Victorino Rodríguez | Andreas Jansen | Shantae C. Gallegos | Santiago Fernando Ramírez Jiménez | Jeffrey S. Moore | Samuel Leguizamon | Leah Appelhans
Source: Nature Communications (article, 2025-07-08)
Field: Chemistry — Organic Chemistry

Active light-controlled frontal ring-opening metathesis polymerization Frontal ring-opening metathesis polymerization (FROMP) is a promising energy-efficient approach to fabricate polymeric materials. Recent advances have demonstrated FROMP for diverse applications, including additive manufacturing, composites, and foams. However, the characteristic properties of the front are currently controlled primarily by varying the resin composition or the environmental conditions. In this work we present an approach to control FROMP of dicyclopentadiene (DCPD) using photochemical methods. A photobase generator is used to inhibit FROMP of DCPD with UV light while a photosensitizer and co-initiator are used to accelerate FROMP with blue light, enabling orthogonal active photocontrol of front velocity. In addition, photoinhibition-enabled lithographic patterning of frontal polymerizations is demonstrated. Frontal polymerizations are spatially controlled, redirected, and even split into diverging fronts. This work establishes a foundation for advanced control of frontal polymerizations, enabling innovation in traditional and additive manufacturing, as well as emerging processes like morphogenic manufacturing. Polymerization ; Ring-opening metathesis polymerisation ; Ring (chemistry) ; Metathesis ; Chemistry ; Organic chemistry Photopolymerization techniques and applications ; Advanced Polymer Synthesis and Characterization
Authors: Min Wu | Yue Liu | Lili Wu | Tom Hasell | Fang Luan
Source: RSC Advances (article, 2025-01-01)
Field: Materials Science — Polymers and Plastics

Adsorption/photodegradation of methylene blue using a sulfur-1,3-diisopropenylbenzene copolymer This study aims to utilize sulfur-1,3-diisopropenylbenzene (S-DIB) to develop a more cost-effective treatment method for dye-contaminated wastewater. The behavior and mechanisms of adsorption and photodegradation on the removal of methylene blue (MB) by S-DIB in water were studied systematically, including three isotherm model fitting tests, kinetics and thermodynamic analysis. With the optimization of the adsorption experimental conditions, the results revealed that S-DIB achieved a 96.53% removal percentage of MB at pH 11, initial dye concentration of 8 mg L<sup>-1</sup>, adsorbent dose of 20 mg, temperature of 293 K and contact time of 180 min. The adsorption data fitted well with the Langmuir isotherm and pseudo-second order models, with regression coefficients (<i>R</i> <sup>2</sup>) of 0.9990 and 0.9993, respectively. Thermodynamic studies showed that the adsorption of MB by S-DIB was exothermic and spontaneous. Furthermore, S-DIB exhibited a unique photodegradation property in visible light regions with the removal of MB from water, offering a dual mechanism of adsorption and photodegradation, with a degradation efficiency is 94%. This work enhances the possibilities and potential for the application of sulfur-rich copolymers in wastewater treatments. Photodegradation ; Methylene blue ; Adsorption ; Copolymer ; Sulfur ; Wastewater ; Chemistry ; Polymer ; Nuclear chemistry ; Catalysis ; Organic chemistry ; Environmental science ; Environmental engineering ; Photocatalysis Synthesis and properties of polymers ; Conducting polymers and applications ; Covalent Organic Framework Applications
Authors: Aparna Swain | Nimmi Das Anthuparambil | Nafisa Begam | Sivasurender Chandran | J. K. Basu
Source: Soft Matter (review, 2025-01-01)
Field: Materials Science — Polymers and Plastics

Harnessing interfacial entropic effects in polymer grafted nanoparticle composites for tailoring their thermo-mechanical and separation properties Nanocomposites based on polymeric materials have been extensively studied to understand and control the thermodynamics, flow, and mechanical properties of the underlying matrix as well to create new materials with diverse optical, electrical, magnetic, separation, catalytic, and biomedical properties. In the form of thin films or membranes, such materials can impart remarkable improvements in various properties of the underlying substrates. Using nanoparticles with grafted polymer chains usually overcomes a major hurdle in achieving enhancements in various properties by enabling better dispersion in the matrix while at the same time introducing a new parameter - interfacial entropy - leading to the emergence of new parameter space for tuning dispersion, flow and thermal properties. In this article, we highlight how this interfacial entropic effect can be harnessed to control various properties in thin films and membranes of grafted nanoparticle composites, in particular their thermo-mechanical properties, viscosity, fragility, glass transition temperature (<i>T</i><sub>g</sub>), and dynamic heterogeneity as well as their ability to act as highly selective gas separation and water desalination membranes. We discuss the application of a range of experimental techniques as well as molecular dynamics simulation to extract these properties and obtain microscopic insight into how the interplay of various surface and interfacial effects lies at the centre of these significant property improvements and enhanced functionality. Finally, we provide an outlook on future opportunities for designing sustainable PNCs, emphasizing their potential in environmental, energy, and biomedical applications, with advanced experiments and modelling driving further innovations. Materials science ; Nanocomposite ; Composite material ; Nanoparticle ; Polymer ; Matrix (chemical analysis) ; Polymer nanocomposite ; Nanotechnology Polymer Nanocomposites and Properties ; Polymer crystallization and properties ; Nanotechnology research and applications