jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Harsh Bhutra | M. Angele Thomas | K. S. Keerthana Shri | T Smitha | N. Neelima
Source:  (article, 2025-01-09)
Field: Materials Science — Materials Chemistry

FEniCSx-Based Effective Scheme for the Cahn-Hilliard Equation The Cahn-Hilliard equation is a fourth-order parabolic partial differential equation that is challenging and time-intensive to solve using conventional methods. Although the equation is difficult to solve, it finds its use cases in many aspects of science including but not limited to the study of phase separation in the binary, isotropic and isothermal mixtures of materials such as molten alloys. Some of the other applications are Bioinformatics, Computational Biology, Biomedical informatics, human activity recognition, Healthcare, computer vision, Climate Science and Natural Language Processing. Many researchers have come up with a way to deal with partial differential equations, but very few works and methods deal with different orders of partial differential equations. In this article, a novel and effective scheme for solving the Cahn-Hilliard equation is proposed using FEniCS. The time of execution and relative tolerance of the solutions of this equation are computed from methods of direct computation and parallel processing which is carried out for the equation with higher-order finite element method for various boundary conditions to demonstrate the efficiency of the proposed approach. The solution thus obtained helps in understanding the non-linear behaviour of the equation with the help of a three-dimensional heatmap plot. This work solves the Cahn Hilliard equation by using the in-built libraries, Dolphin an open-source software called FEniCS and Message Passing Interface (MPI). The MPI is responsible for achieving parallelism in high-performance computing environments and breaks down the problem into four smaller parts making it faster to get to the solution. The obtained results demonstrate that this approach outperforms the existing literature by achieving a forty percent faster computational speed. The approach will be very useful in solving many similar problems arising in the field of science and engineering. Cahn–Hilliard equation ; Scheme (mathematics) ; Computer science ; Applied mathematics ; Mathematics ; Mathematical analysis ; Partial differential equation Solidification and crystal growth phenomena
Authors: Julien Steffen (14790860)
Source: Figshare (article, 2025-07-18)
Field: Materials Science — Materials Chemistry

Simulation of HydrogenStorage in MOF‑5 andLi-MOF‑5 by Ring Polymer Molecular Dynamics on Self-ConsistentlyFine-Tuned Machine-Learned Interatomic Potentials The hydrogen storage in MOF-5 and lithiated MOF-5 (Li-MOF-5) is simulated with ring polymer molecular dynamics (RPMD) on machine-learned interatomic potentials (MLIPs). The MLIPs were parametrized based on the message-passing atomic cluster expansion (MACE) foundation model. It was fine-tuned for H<sub>2</sub> storage in MOF-5 and Li-MOF-5, using density-functional theory (DFT) single point calculations of each 100th frame from MD trajectories calculated with it. In order to focus the samplings on the most relevant parts of configuration space and reduce the overhead due to erroneous samplings with the foundation model, the fine-tuning was done self-consistently: MD samplings were performed with the fine-tuned MLIP, DFT single points calculated and the data used for another fine-tuning, until the property of interest (the spatial H<sub>2</sub> distribution in this case) has converged. With this, highly accurate MLIPs were obtained that allowed for the simulation of H<sub>2</sub> storage, depending on the temperature and the H<sub>2</sub> loading. Nuclear quantum effects, important for the description of H<sub>2</sub> at the low temperatures relevant for storage, were accounted for with RPMD. In MOF-5, the H<sub>2</sub> molecules are loosely associated with the edges of the framework, whereas in Li-MOF-5, each Li atom coordinates 2–3 H<sub>2</sub> molecules up to room temperature. Its H<sub>2</sub> capacity is therefore increased significantly. Nuclear quantum effects lead to a slight decrease in storage capacity for both MOF-5 and Li-MOF-5, in agreement with previous studies. The outlined fine-tuning strategy facilitates the fast and systematic generation of high-quality MLIPs for hydrogen storage in arbitrary MOFs. Ring (chemistry) ; Molecular dynamics ; Storage ring ; Quantum ; Hydrogen storage ; Molecule ; Hydrogen ; Interatomic potential ; Quantum simulator Machine Learning in Materials Science ; Thermal Expansion and Ionic Conductivity ; Advanced Battery Materials and Technologies
Authors: James Bowden | Sergey Levine | Jennifer Listgarten
Source: ArXiv.org (preprint, 2025-11-04)
Field: Materials Science — Materials Chemistry

Leveraging Discrete Function Decomposability for Scientific Design In the era of AI-driven science and engineering, we often want to design discrete objects in silico according to user-specified properties. For example, we may wish to design a protein to bind its target, arrange components within a circuit to minimize latency, or find materials with certain properties. Given a property predictive model, in silico design typically involves training a generative model over the design space (e.g., protein sequence space) to concentrate on designs with the desired properties. Distributional optimization$\unicode{x2013}$which can be formalized as an estimation of distribution algorithm or as reinforcement learning policy optimization$\unicode{x2013}$finds the generative model that maximizes an objective function in expectation. Optimizing a distribution over discrete-valued designs is in general challenging because of the combinatorial nature of the design space. However, many property predictors in scientific applications are decomposable in the sense that they can be factorized over design variables in a way that could in principle enable more effective optimization. For example, amino acids at a catalytic site of a protein may only loosely interact with amino acids of the rest of the protein to achieve maximal catalytic activity. Current distributional optimization algorithms are unable to make use of such decomposability structure. Herein, we propose and demonstrate use of a new distributional optimization algorithm, Decomposition-Aware Distributional Optimization (DADO), that can leverage any decomposability defined by a junction tree on the design variables, to make optimization more efficient. At its core, DADO employs a soft-factorized "search distribution"$\unicode{x2013}$a learned generative model$\unicode{x2013}$for efficient navigation of the search space, invoking graph message-passing to coordinate optimization across linked factors. Leverage (statistics) ; Protein design ; Property (philosophy) ; Graph ; Generative model ; Function (biology) ; Generative Design Machine Learning in Materials Science ; Advanced Multi-Objective Optimization Algorithms ; Protein Structure and Dynamics
Authors: Kornelia Hyjek | Klaudia Dymek | Grzegorz Kurowski | Anna Boguszewska‐Czubara | Barbara Budzyńska | Jorge A. R. Navarro | Emilio Borrego-Marin | Weronika Mrozek | Justyna Grymuza | Anna Pajdak | Witold Piskorz | Paweł Śliwa | Alicja Trzpil | Anna Stachniuk | Emilia Fornal | Przemysław J. Jodłowski
Source: ACS Applied Materials & Interfaces (article, 2025-11-30)
Field: Chemistry — Inorganic Chemistry

Reviving the Fight against Opioid Overdoses: Unleashing the Power of Metal–Organic Frameworks for Morphine Removal The lack of suitable medical adsorbents that exhibit a quick response at the time of an overdose is challenging. In this work, we focused on morphine (MORPH) adsorbents that efficiently abate MORPH during the acute overdose and provide, in a controlled, gradual manner, MORPH antagonist─naloxone (NAL) to effectively and safely reverse overdose and its side effects by using, as sorbent, zirconium metal-organic frameworks (MOFs). Three model MOFs, including UiO-66, UiO-67, and NU-1000, were characterized in terms of their ability to adsorb MORPH as well as NAL release in water and a simulated body fluid (SBF). Single MORPH adsorption on NU-1000 was 100% in water and 90 wt % in SBF solution. At the same time, in a single NAL release in SBF from the prepared NAL@UiO-67 composite was equal to 76%. Additionally, in the simultaneous experiment of MORPH adsorption and NAL release, a designed mixture of NU-1000/NAL@UiO-67 has shown maximum adsorption/release values in SBF solution of 89 and 8%, respectively. The in vivo and in vitro experiments confirmed the exceptional effect of prepared materials on the locomotor activity of mice and the low cytotoxicity of MOFs. In vivo fluorescent imaging has confirmed that the nano-MOFs obtained are mostly accumulated in the liver when administered intravenously. Adsorption ; In vivo ; Simulated body fluid ; Cytotoxicity ; Morphine ; Opioid ; Opioid overdose Metal-Organic Frameworks: Synthesis and Applications ; Drug-Induced Hepatotoxicity and Protection ; Covalent Organic Framework Applications
Authors: Liyanage Chamila Roshani Perera | Nick Huettner | Sönke Menke | Richard Hoogenboom | Nathan R. B. Boase | Neha S. Gandhi | Tim R. Dargaville
Source: European Polymer Journal (article, 2025-07-26)
Field: Materials Science — Biomaterials

Deciphering cloud point temperature suppression of poly(2-ethyl-2-oxazoline) by an angiotensin-converting enzyme inhibitor Cloud point ; Oxazoline ; Enzyme ; Angiotensin-converting enzyme ; Chemistry ; Enzyme inhibitor ; Melting point ; Materials science ; Biochemistry ; Organic chemistry ; Internal medicine ; Medicine ; Blood pressure ; Aqueous solution biodegradable polymer synthesis and properties ; Polymer crystallization and properties ; Advanced Polymer Synthesis and Characterization
Authors: Sahar Koritisani | Gunjana Yadav | Abhishek Khetan
Source: ChemRxiv (preprint, 2025-07-10)
Field: Materials Science — Materials Chemistry

Heating of CeO₂ surfaces under microwave irradiation using non-equilibrium molecular dynamics This study explores the thermal behavior of cerium oxide (CeO₂) surfaces subjected to microwave electric fields using non-equilibrium molecular dynamics (NEMD) simulations. A key contribution of this work is the optimization of reactive interatomic potentials for ceria, using both evolutionary and gradient-based methods, to enable accurate simulation within the LAMMPS framework. Simulations reveal the role of oxygen vacancies and surface layer thickness in governing microwave-induced heating, offering insights that are valuable for applications in catalysis and energy storage. Microwave irradiation ; Irradiation ; Dynamics (music) ; Molecular dynamics ; Microwave ; Materials science ; Chemistry ; Physics ; Computer science ; Nuclear physics ; Computational chemistry ; Acoustics ; Telecommunications Catalytic Processes in Materials Science ; Microwave-Assisted Synthesis and Applications ; Catalysts for Methane Reforming
Authors: Andrey O. Kurbatov | Kirill A. Litvin | Iurii Iu. Grishin | Н. К. Балабаев | Elena Yu. Kramarenko
Source: Polymers (article, 2025-12-28)
Field: Materials Science — Polymers and Plastics

Atomistic Simulations of Individual Amphiphilic Carbosilane Dendrimers with –(OCH2CH2)n–OCH3 Terminal Groups in Hydrophilic and Hydrophobic Environments and at Interfaces Amphiphilic dendrimers represent a promising class of nanoscale building blocks for functional materials, yet their conformational behavior, solvation, and interfacial activity remain incompletely understood. In this work, we employ atomistic molecular dynamics simulations to investigate G2-G4 carbosilane dendrimers functionalized with ethylene glycol terminal groups of two lengths-R1 (one ethylene glycol unit) and R3 (three units)-in water, toluene, and at fluid interfaces (water-toluene and water-air). Both types of dendrimers adopt compact, nearly spherical conformations in water but swell significantly (~83% in volume for G4) in toluene, a good solvent for the hydrophobic core. At the water-toluene interface, the dendrimers remain fully solvated in the toluene phase and show no surface activity. In contrast, at the water-air interface, they adsorb and adopt a mildly anisotropic, biconvex conformation, with a modest deformation. The total number of hydrogen bonds is reduced by ~50% compared to bulk water. Notably, the R3 dendrimers form more hydrogen bonds overall due to their higher oxygen content, which may contribute to the enhanced stability of their monolayers observed experimentally. These results demonstrate how dendrimer generation as well as terminal group length and hydrophilicity finely tune dendrimer conformation, hydration, and interfacial behavior, which are key factors for applications in nanocarriers, interfacial engineering, and self-assembled materials. The validated simulation protocol provides a robust foundation for future studies of multi-dendrimer systems and monolayer formation. Dendrimer ; Amphiphile ; Ethylene glycol ; Monolayer ; Hydrogen bond ; Molecular dynamics ; Hydrophobic effect ; Solvent Dendrimers and Hyperbranched Polymers ; Polymer Surface Interaction Studies ; Molecular Junctions and Nanostructures
Authors: R.J. Caraballo-Vivas | Marcelo Albuquerque | Vanessa Torres | Luciano T. Costa | Pedro Venezuela | M.S. Reis
Source: ACS Omega (article, 2025-08-23)
Field: Materials Science — Biomaterials

Evidence of the Giant Barocaloric Effect in the PVA-Slime System by Molecular Dynamics Simulations Advancements in the study of the barocaloric effect in polymers have opened promising applications in both the scientific and industrial fields. Among these, elastic polymers based on poly-(vinyl alcohol) (PVA), such as slimes, have shown significant potential for solid-state refrigeration and thermal battery applications due to their notable pressure-induced thermal response, which occurs without an associated structural phase transition. Thus, current research focuses on understanding the mechanism behind this response to applied pressure with the aim of optimizing its thermal performance. Therefore, we employed a molecular dynamics simulation in order to explore the barocaloric effect in the Slime system. We used pure PVA chains cross-linked by tetrahydroxyborate ions to provide further details about our Slime system, promoting a greater proximity between polymeric chains. Our results reveal that these connections reduce the free volume in the Slime system compared to pure PVA. This, combined with the applied simulated pressure, decreases the mobility of the polymer chains, lowering their kinetic energy while favoring potential energy. As a result, this contributes significantly to the change in internal energy and, consequently, to the barocaloric effect. Thus, our investigation shows a significant increase in entropy from 56 JK<sup>-1</sup> kg<sup>-1</sup> for pure PVA to 295 JK<sup>-1</sup> kg<sup>-1</sup> Slime system and temperature change from 3 to 26 K at 300 MPa. These findings highlight the importance of cross-linking between polymer chains, which enhances the barocaloric effect in this system type, offering promising prospects for practical applications. Dynamics (music) ; Molecular dynamics ; Statistical physics ; Chemistry ; Physics ; Computational chemistry Calcium Carbonate Crystallization and Inhibition ; Corrosion Behavior and Inhibition ; Shape Memory Alloy Transformations
Authors: Tom Stavert | Carlos Brambila | Siddharth V. Patwardhan | Miguel Jorge
Source: Journal of Materials Chemistry A (article, 2025-01-01)
Field: Materials Science — Biomaterials

Computer-aided development of bio-inspired routes to highly ordered green mesoporous silica By combining multi-scale modelling and design of experiments, we have elucidated the mechanism of order promotion in mesoporous silica, and have proposed strategies for environmentally friendly, cheap and scalable production of those materials. Mesoporous material ; Mesoporous silica ; Nanotechnology ; Computer science ; Materials science ; Development (topology) ; Chemistry ; Mathematics ; Organic chemistry Diatoms and Algae Research
Authors: Haifeng Wu | Wei Zhang | Shichao Xu | Baoli Zhang | Yuanyuan Xie | Zhen‐Gang Wang
Source: Nano Research (article, 2025-09-16)
Field: Materials Science — Biomaterials

Bioinspired self-assembled bilayers of alkylated aza-crown ethers as a synthetic oxyanion hole mimic for enhanced hydrolytic catalysis Enzymes fold into three-dimensional structures for spatial arrangement of amino acid residues and formation of specific motifs within their active sites, enabling their remarkable catalytic properties. Replicating such intricate folding and functional group distribution in synthetic systems could allow for efficient and mild catalysis with significant potential in green chemistry, but achieving this remains a major challenge. Inspired by structure and function of oxyanion hole-a fundamental structural feature in hydrolases, we design a surfactant system comprising an aza-crown ether core and an alkyl tail, which self-assembles into tail-to-tail bilayer nanostructures capable of catalyzing hydrolytic reactions. The theoretical and experimental results reveal that the alkyl chain enhances the protonation and organization of the aza-crown ether, promoting ester substrate access and stabilizing the transition state, reminiscent of natural oxyanion hole mechanisms. It is observed that the alkylated aza-crown ether exhibits a 43.3-fold increase in catalytic efficiency (<em>k</em><sub>cat</sub>/<em>K</em><sub>m</sub>) compared to its non-alkylated counterpart. Additionally, the self-assembled alkylated aza-crown ether demonstrates efficient CO<sub>2</sub> hydration activity, resembling the function of carbonic anhydrase. This work offers a model for how simple molecules can evolve sophisticated catalysts through structural and functional optimization, offering new insights for the design of bioinspired catalyst in green chemistry. Oxyanion ; Alkylation ; Catalysis ; Oxyanion hole ; Ether ; Alkyl ; Protonation ; Hydrolysis Supramolecular Self-Assembly in Materials ; Porphyrin and Phthalocyanine Chemistry ; Molecular Sensors and Ion Detection
Authors: Kiran Kumar Bokara | Sreenivasan Kuravi | Vikas Sahu | Chandra Sri Durga | Neema Kumari
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-08-03)
Field: Materials Science — Biomaterials

In-Silico Evaluation of Silk Fibroin-Conjugated Doxycycline for Sustained Drug Delivery Abstract Tetracyclines such as Doxycycline and Minocycline are broad-spectrum antibiotics. Their high oral bioavailability aids systemic absorption but limits achieving sustained local drug levels at the infection site. Sustained drug release to enhance the therapeutic efficacy and minimise side effects remains a significant challenge. This study investigated the conjugation of Doxycycline with silk fibroin (SF), which would provide sustained drug release at the target site. We employed an in-silico approach using molecular docking and molecular dynamics (MD) simulations to investigate the interaction and stability of antibiotics with SF. We also assessed the structural stability of SF when conjugated with these antibiotics. Molecular level characterization using a blind docking approach and MD simulation revealed that Doxycycline exhibited the strongest binding affinity of -6.0 kcal/mol, compared with both Tetracycline (−5.9 kcal/mol) and Minocycline (−5.7 kcal/mol). The MMPBSA analysis also showed that Doxycycline exhibited the highest binding energy of -25.71 kcal/mol compared to Tetracycline (−18.27 kcal/mol) and Minocycline (−10.8 kcal/mol). The strong binding energy and stability of Doxycycline with SF was attributed mainly by van der Waals interactions and hydrogen bonds. To evaluate the stability of protein-antibiotic complexes, 100 ns MD simulations were performed. The RMSD, RMSF, radius of gyration, SASA, and DSSP analyses revealed that SF was stable without much deformation upon docking of all three antibiotics. In summary, our computational results suggest that Doxycycline and SF conjugates offer a promising strategy for sustained drug delivery, potentially improving therapeutic efficacy in the treatment of chronic inflammatory diseases. Highlights - The study finds silk fibroin as a potential carrier for sustained drug delivery of tetracycline family antibiotics. - Silk fibroin remained stable with minimal structural deviations in complex with Doxycycline, Minocycline, and Tetracycline over a 100 ns MD simulation. - Doxycycline showed the highest binding affinity and most favourable binding energy and remained stable throughout the simulation. - SF-Doxycycline conjugate shows promise for sustained, localized drug delivery. Fibroin ; Doxycycline ; In silico ; Conjugated system ; Drug delivery ; Drug ; Pharmacology ; SILK ; Chemistry ; Medicine ; Computer science ; Nanotechnology ; Materials science ; Antibiotics ; Biochemistry Silk-based biomaterials and applications ; Biochemical and Structural Characterization ; Phytochemical compounds biological activities
Authors: Anupom Roy | Connard Giresse Tetssassi Feugmo
Source: ChemRxiv (preprint, 2025-04-18)
Field: Materials Science — Materials Chemistry

Optimizing Bio-Imaging with Computationally Designed Polymer Nanoparticles Conjugated polymer nanoparticles (CPNs), especially poly(p-phenylene ethyny- lene) nanoparticles (PPE-NPs), are promising candidates for bio-imaging due to their high photostability, adjustable optical characteristics, and biocompatibility. Despite their potential, the fluorescence mechanisms of these nanoparticles are not yet fully understood. In this work, we modeled a spherical PPE-NP in a water environment us- ing 30 PPE dimer chains. Combining molecular dynamics (MD) simulations and time- dependent density functional theory (TD-DFT) calculations, we examined the struc- tural and optical properties of PPE-NPs in water. The MD simulations showed that PPE-NPs remain stable via hydrophobic interactions, with octyloxy side chains shield- ing the core from water. After evaluating six hybrid functionals, we found that the M05 functional provided the most accurate prediction of absorption wavelengths (450.94 nm vs. the experimental value of 450.00 nm). TD-DFT analysis of selected PPE dimer chains revealed strong fluorescence, characterized by high oscillator strengths (2.689– 4.004) and large Stokes shifts (134.51–156.31 nm), which minimize spectral overlap and improve imaging resolution. HOMO–LUMO orbital analysis confirmed that π →π∗ transitions dominate (> 90%), indicating efficient electronic behavior. These results reinforce the potential of PPE-NPs as effective fluorescent probes for bio-imaging, sup- ported by a reliable computational approach for designing future CPNs. By comparing computational predictions with experimental data, this study contributes to the devel- opment of customized nanomaterials for biomedical applications. Nanoparticle ; Polymer ; Nanotechnology ; Materials science ; Computer science ; Composite material Machine Learning in Materials Science ; Innovative Microfluidic and Catalytic Techniques Innovation ; Photoacoustic and Ultrasonic Imaging