jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Priyanka Sawant | Gauri Gharat | Vedanti Harad
Source: International Journal of Novel Research and Development (article, 2025-12-01)
Field: Materials Science — Biomaterials

Nanoparticles In Cancer Therapy: Advances, Challenges and Future Directions Cancer remains one of the leading causes of mortality worldwide, and conventional treatments such as Chemotherapy, radiation, and surgery often face limitations including toxicity, drug resistance, and poor Selectivity. Nanotechnology has emerged as a transformative approach in cancer therapy by enabling Precise drug delivery, enhanced targeting, and reduced systemic side effects. Nanoparticles (NPs) such As liposomes, dendrimers, polymeric nanoparticles, metallic nanoparticles, and quantum dots offer Unique physicochemical properties that improve drug solubility, bioavailability, and controlled release. Their ability to exploit mechanisms like passive targeting through the enhanced permeability and Retention (EPR) effect and active targeting via ligand–receptor interactions significantly enhance Therapeutic efficacy. Despite promising preclinical outcomes, clinical translation remains limited due To challenges in biodistribution, biocompatibility, large-scale synthesis, and long-term safety. Continued research focusing on the optimization of nanoparticle design, toxicity evaluation, and Personalized nanomedicine may pave the way for safer and more effective cancer treatments. Nanomedicine ; Cancer ; Drug ; Drug delivery ; Cancer therapy ; Cancer treatment ; Targeted drug delivery ; Nanoparticle Nanoparticle-Based Drug Delivery ; Dendrimers and Hyperbranched Polymers ; Nanoplatforms for cancer theranostics
Authors: Naufaldin Adam Naim | Aditya Rianjanu
Source: Greensusmater (article, 2025-07-02)
Field: Materials Science — Biomaterials

Tuning Nanofiber Morphology and Hydrophobicity via PVDF-co-HFP Polymer Concentration This study investigates the effect of poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-co-HFP) concentration on the morphological and surface wettability properties of electrospun nanofibers. Nanofiber mats were fabricated using electrospinning with PVDF-co-HFP concentrations ranging from 12 wt% to 18 wt%. Scanning electron microscopy (SEM) analysis revealed that increasing polymer concentration resulted in larger and more uniform fiber diameters, ranging from approximately 235 nm to 560 nm. Fourier-transform infrared (FTIR) spectroscopy confirmed the preservation of the chemical structure, with characteristic peaks associated with CF₂ and C–F groups, and the presence of both α- and β-phases of PVDF. Water contact angle (WCA) measurements indicated a marked increase in hydrophobicity, with WCA values rising from ~108° for PVDF-co-HFP12 to ~128° for PVDF-co-HFP18. This enhancement is attributed to increased surface roughness and fiber diameter, in line with the Cassie–Baxter wetting model. The results demonstrate that polymer concentration is a critical parameter in tailoring nanofiber morphology and wettability, providing a straightforward strategy for designing functional materials in applications such as water-repellent coatings, filtration membranes, and sensing platforms. Nanofiber ; Morphology (biology) ; Materials science ; Chemical engineering ; Polymer ; Polymer chemistry ; Polymer science ; Composite material Electrospun Nanofibers in Biomedical Applications ; Advanced Sensor and Energy Harvesting Materials
Authors: Assefa Getachew | Ebise Getacho Bacha | Wondwosen Sime Geleta
Source: Scientific Reports (article, 2025-11-22)
Field: Materials Science — Materials Chemistry

Statistical optimization of eco-friendly synthesized silver nanoparticles using Discopodium penninervium Hochst leaf extract for enhanced antimicrobial efficacy Infectious diseases caused by pathogenic microorganisms are a significant global threat, affecting millions of people. The aim of this study was optimizing the eco-friendly synthesis of silver nanoparticles (AgNPs) using Discopodium Penninervium Hochst leaf extract via a response surface methodology approach. The ANOVA results revealed that the quadratic model (p < 0.0001) was sufficient to achieve the most precise prediction of particle size (R<sup>2</sup> = 0.995). A minimum AgNPs size of 21.65 nm, was achieved under optimal conditions. The ultraviolet-visible (UV-vis) UV-vs spectroscopy of the synthesized AgNPs revealed a strong absorption peak at 402 nm. The X-ray diffraction (XRD) analysis confirmed a face-centered cubic crystal structure with average crystallite size of 17.60 nm. Dynamic light scattering (DLS) value (38.62 nm) displays AgNPs was in the nanoscale whereas the zeta potential value (-14.20 mV) indicates its stability. The scanning electron microscopy (SEM) image showed spherical in shape and exhibited an average particle size of 2 μm with some agglomeration. Fourier transform infrared spectroscopy (FTIR) spectra depicted the presence of functional groups from plant extract, which used as a capping agent and bioreduction process. thermogravimetric analysis (TGA) measurement suggested that AgNPs exhibit good thermal stability. The AgNPs exhibited good antimicrobial activities against Gram-negative (Escherichia coli) and Gram-positive (Staphylococcus aureus) bacteria, as well as fungus (Candida albicans) with corresponding inhibition zones of 25 mm (mm), 21 mm, and 20 mm, respectively. The phytochemical screening revealed the presence of bioactive components such as phenols, alkaloids, flavonoids, tannins, steroids, and terpenoids. This study presented rapid, simple, and eco-friendly methods for synthesizing AgNPs with potential antimicrobial applications. Silver nanoparticle ; Thermogravimetric analysis ; Zeta potential ; Dynamic light scattering ; Fourier transform infrared spectroscopy ; Particle size ; Phytochemical ; Nanoparticle ; Scanning electron microscope Nanoparticles: synthesis and applications ; Gold and Silver Nanoparticles Synthesis and Applications ; Graphene and Nanomaterials Applications
Authors: Alaeddine Kaouka | Khedidja Benarous | Mourad Keddam
Source: Zastita materijala (article, 2025-07-11)
Field: Materials Science — Materials Chemistry

Electrochemical evaluation of natural extracts as effective corrosion inhibitors and surface treatments on metal substrates Corrosion is a serious problem encountered in the industry, protection from it is more than necessary using inhibitors and treatments. These treatments can effectively ease the problem on the surface of the material substrate, particularly the metal substrate for being easily etched during usage and being unable to withstand abrasion. Experimental results showed that the extracts are effective inhibitors of corrosion. Polarization tests indicate that the inhibitors are of mixed nature and the corrosion mechanism does not change after their addition to the solution. The electrochemical impedance spectroscopy confirmed that inhibitory quality and surface treatments improved corrosion resistance. Surface analysis revealed that the surface of the sample for the control solution was covered and protected. However, for the inhibited solutions the presence of oxides was not observed. Corrosion ; Dielectric spectroscopy ; Materials science ; Metal ; Polarization (electrochemistry) ; Electrochemistry ; Corrosion inhibitor ; Metallurgy ; Substrate (aquarium) ; Chemical engineering ; Chemistry ; Electrode Corrosion Behavior and Inhibition ; Surface Modification and Superhydrophobicity ; Anodic Oxide Films and Nanostructures
Authors: Thomas A. Seymour-Cozzini | Rae Ernest | Julia V. Zaikina
Source: Journal of Materials Chemistry A (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Hydride synthesis of thermoelectric skutterudites (Ba,Sr)Fe<sub>3±<i>x</i></sub>Ni<sub>1±<i>x</i></sub>Sb<sub>12</sub> optimized <i>via</i> design of experiments Diffusion-enhanced hydride synthesis enables the modern solidstate chemist to achieve their Hephaestian aspirations through design of experiments methods and the mechanistic knowledge gleaned from in situ powder X-ray diffraction data. Thermoelectric effect ; Hydride ; Materials science ; Thermoelectric materials ; Crystallography ; Metallurgy ; Condensed matter physics ; Physics ; Chemistry ; Thermodynamics ; Metal Advanced Thermoelectric Materials and Devices ; Rare-earth and actinide compounds ; Thermodynamic and Structural Properties of Metals and Alloys
Authors: Farid Samsudin | Melbi Mahardika | Nasrullah Razali | Mohamad Haafiz Mohamad Kassim
Source: PaperAsia (review, 2025-08-18)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Activated Carbon: Past, Present and Future Trends in Sustainable Applications and the Role of Artificial Intelligence – A Comprehensive Review Activated carbon (AC), characterized by its high porosity, surface area, and functional versatility, is essential in environmental remediation, energy storage, and various industrial applications. Producing activated carbon from lignocellulosic agricultural biomass provides notable environmental and economic advantages. This review examines the historical evolution of AC, contemporary methods for its sustainable production, and innovative applications that correspond with the Sustainable Development Goals (SDGs). It points out key challenges on the feedstock, variability, energy-intensive processes, and environmental impacts, introducing innovative solutions such as microwave and ultrasonic activation and using artificial intelligence to optimize processes. Future trends are underlined by using circular economy principles and renewable energy integration to improve AC production efficiency and carbon footprint. Management science ; Engineering Supercapacitor Materials and Fabrication ; Adsorption and biosorption for pollutant removal ; Catalytic Processes in Materials Science
Authors: Funmilayo Ayedun | G.T. Solola
Source: World Journal of Applied Science & Technology (article, 2025-06-17)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Band structure, thermoelectric features and electronic fitness function of p-type semiconductor half-Heusler RhCrGe compound This work conducted an investigation of structural, electronic and thermoelectric reactions of the ternary half-Heusler RhCrGe compound utilising Perdew-Burke-Ernzerhof for solids within Generalised Gradient Approximation (PBEsol-GGA) rooted in Density Functional Theory (DFT) as implemented in Quantum Espresso software bundle. The material demonstrated a semiconductor type only with an indirect energy gap of 0.7eV. Electronic transport features were calculated using BoltzTrap code and TransM code. This study revealed p-type material with the thermoelectric properties suggesting better values of figure of merit, power factor, Seebeck coefficient and electronic fitness function as temperature increased from 300K to 800 K. Heusler compound ; Semiconductor ; Materials science ; Compound semiconductor ; Thermoelectric effect ; Electronic band structure ; Condensed matter physics ; Electronic structure ; Optoelectronics ; Nanotechnology ; Physics ; Quantum mechanics ; Layer (electronics) Heusler alloys: electronic and magnetic properties ; Advanced Thermoelectric Materials and Devices
Authors: Shigeru Yamaguchi
Source: ChemRxiv (article, 2025-08-21)
Field: Materials Science — Materials Chemistry

Computational Study on Data Integration in Chiral Catalyst Design: Case Study Using Michael Addition Reactions Data science in molecular catalysis often relies on the idea that molecules with similar structures show similar properties. This concept underlies many successful examples of regression analysis based on free energy relationships, typically using datasets in which substituents are varied on a single catalyst or substrate scaffold. Here, we present data integration for chiral catalyst design via regression using three-dimensional image-like descriptors (voxel data) derived from 718 TS (transition-state) structures calculated through DFT methods, along with their corresponding computed ΔΔG‡ values (energy differences between TSs leading to each enantiomer). These datasets covered seven reaction types, including organocatalysis, transition-metal catalysis, and both Michael addition and Diels–Alder reactions. Regression using integrated datasets from seven pairs of distinct reaction systems enabled the design of chiral catalysts with improved computed enantioselectivity in all seven catalytic systems. To facilitate applications, we have released a web platform (https://mcds.riken.jp) that offers a data-driven design tool and a database of DFT-computed TS data. Michael reaction ; Catalysis ; Computer science ; Chemistry ; Organic chemistry Machine Learning in Materials Science ; Surface Chemistry and Catalysis ; Catalysis and Oxidation Reactions
Authors: Shuntaro Takahashi | Michiaki Hamada | Hisae Tateishi‐Karimata | Naoki Sugimoto
Source: RSC Chemical Biology (review, 2025-01-01)
Field: Materials Science — Materials Chemistry

Fitness landscapes and thermodynamic approaches to development of nucleic acids enzymes: from classical methods to AI integration Nucleic acids (NA), namely DNA and RNA, dynamically fold and unfold to perform their functions in cells. Functional NAs include NA enzymes, such as ribozymes and DNAzymes. Their folding and target binding are governed by interactions between nucleobases, including base pairings, which follow thermodynamic principles. To elucidate biological mechanisms and enable diverse technical applications, it is essential to clarify the relationship between the primary sequence and the catalytic activity of NA enzymes. Unlike methods for predicting the stability of NA duplexes, which have been widely used for over half a century, predictive approaches for the catalytic activity of NA enzymes remain limited due to the low throughput of activity assays. However, recent advances in genome analysis and computational data science have significantly improved our understanding of the sequence-function relationship in NA enzymes. This article reviews the contributions of data-driven chemistry to understanding the reaction mechanisms of NA enzymes at the nucleotide level and predicting novel NA enzymes with catalytic activity from sequence information. Furthermore, we discuss potential databases for predicting NA enzyme activity under various solution conditions and their integration with artificial intelligence for future applications. Nucleic acid ; Chemistry ; Enzyme ; Catalysis ; Biochemistry ; Computational biology ; Biology Machine Learning in Materials Science ; Advanced biosensing and bioanalysis techniques ; Chemical Synthesis and Analysis
Authors: Aurelian Dobrițescu | Adriana Samide | Nicoleta Cioateră | Oana Camelia Mic | Cătălina Ionescu | Irina Dăbuleanu | Cristian Tigae | Cezar Spînu | Bogdan Oprea
Source: Molecules (article, 2025-07-26)
Field: Materials Science — Materials Chemistry

The Inhibitory Effect and Adsorption Properties of Testagen Peptide on Copper Surfaces in Saline Environments: An Experimental and Computational Study Experimental and theoretical studies were applied to investigate the adsorption properties of testagen (KEDG) peptide on copper surfaces in sodium chloride solution and, implicitly, its inhibition efficiency (IE) on metal corrosion. The tetrapeptide synthesized from the amino acids lysine (Lys), glutamic acid (Glu), aspartic acid (Asp), and glycine (Gly), named as H-Lys-Glu-Asp-Gly-OH, achieved an inhibition efficiency of around 86% calculated from electrochemical measurements, making KEDG a promising new copper corrosion inhibitor. The experimental data were best fitted to the Freundlich adsorption isotherm. The standard free energy of adsorption (ΔGadso) reached the value of -30.86 kJ mol<sup>-1</sup>, which revealed a mixed action mechanism of tetrapeptide, namely, chemical and physical spontaneous adsorption. The copper surface characterization was performed using optical microscopy and SEM/EDS analysis. In the KEDG presence, post-corrosion, SEM images showed a network surface morphology including microdeposits with an acicular appearance, and EDS analysis highlighted an upper surface layer consisting of KEDG, sodium chloride, and copper corrosion compounds. The computational study based on DFT and Monte Carlo simulation confirmed the experimental results and concluded that the spontaneous adsorption equilibrium establishment was the consequence of the contribution of noncovalent (electrostatic, van der Waals) interactions and covalent bonds. Adsorption ; Copper ; Erosion corrosion of copper water tubes ; Chemistry ; Corrosion ; van der Waals force ; Inorganic chemistry ; Freundlich equation ; Tetrapeptide ; Molecule ; Physical chemistry ; Peptide ; Organic chemistry Corrosion Behavior and Inhibition ; Polymer Surface Interaction Studies ; Metal and Thin Film Mechanics
Authors: Diriba Gonfa Tolasa
Source: American Journal of Physics and Applications (article, 2025-05-29)
Field: Chemistry — Physical and Theoretical Chemistry

Molecular Dynamics Simulations: Unraveling the Complexities of Chemical Reactions at the Atomic Level Molecular dynamics (MD) simulations have emerged as a cornerstone computational technique within the realms of chemistry and materials science, offering profound insights into the intricate behaviors of molecular systems at the atomic scale. By leveraging the principles of classical mechanics and statistical physics, MD simulations afford researchers a detailed, time-resolved perspective on the dynamical behavior of molecules, thereby facilitating the exploration of reaction mechanisms that often elude conventional experimental methodologies. This paper provides a comprehensive overview of the methodologies and diverse applications of molecular dynamics simulations in elucidating the complex processes that underpin chemical reactions. We delve into the fundamental principles of MD, encompassing force field parameterization, integration algorithms, and boundary conditions, underscoring their critical roles in accurately modeling molecular interactions. The selection of potential energy functions, including empirical force fields and abilities methods, is scrutinized, as it significantly impacts the fidelity of the simulations and the reliability of the resultant data. A notable advantage of MD simulations lies in their capacity to capture the temporal evolution of molecular systems, enabling the observation of transient states and intermediates that are pivotal in reaction pathways. Through the analysis of trajectory data, researchers can extract invaluable information regarding reaction coordinates, energy barriers, and the influence of solvent dynamics on reaction kinetics. Furthermore, advanced techniques such as umbrella sampling and meta dynamics are employed to enhance the exploration of conformational space, allowing for the investigation of rare events and transition states that are crucial in determining reaction outcomes. The applicability of MD simulations transcends traditional chemical reactions; they are instrumental in the investigation of biomolecule processes, catalysis, and materials design. For instance, the dynamics of enzyme-substrate interactions can be elucidated through MD, yielding insights into catalytic mechanisms and informing the design of more efficient catalysts. Similarly, the behavior of polymers and nanomaterial’s under varying conditions can be meticulously examined, paving the way for the development of novel materials with tailored properties. Molecular dynamics ; Dynamics (music) ; Chemical physics ; Reaction dynamics ; Statistical physics ; Physics ; Computational chemistry ; Chemistry ; Molecule ; Quantum mechanics Various Chemistry Research Topics
Authors: Linwei Sai | Boxue Du | Li Fu | Sharmin Akter | Chunmei Tang | Jijun Zhao
Source: Nanomaterials (article, 2025-06-30)
Field: Chemistry — Organic Chemistry

Graph Neural Network Determine the Ground State Structures of Boron or Nitride Substitute C60 Fullerenes Substitutional doping of fullerenes represents a significant category of heterofullerenes. Due to the vast number of isomers, confirming the ground state structure poses considerable challenges. In this study, we generated isomers of C<sub>60-<i>n</i></sub>B<sub><i>n</i></sub> and C<sub>60-<i>n</i></sub>N<sub><i>n</i></sub> with <i>n</i> ranging from 2 to 12. To avoid overlooking the ground state structures, we applied specific filtering rules: no adjacent nitrogen (N) or boron (B) atoms are allowed, and substitutions in meta-positions within pentagons are prohibited when the substitution number <i>n</i> exceeds nine. Approximately 15,000 isomers across various values of <i>n</i> within the range of 2 to 12 for B and N substituted fullerenes were selected and optimized using density functional theory (DFT) calculations, forming our dataset. We developed a Graph Neural Network (GNN) that aggregates both topological connections and its dual graph with ring types as input information to predict their binding energies. The GNN achieved high accuracy, reaching a root mean square error (RMSE) of 1.713 meV. Furthermore, it operates efficiently; indeed, it can predict over six thousand isomers per second on an eight-core PC. Several predicted stable structures were further optimized by DFT to confirm their ground state configurations. The energy cutoffs of each composition were determined through statistical simulations to ensure that the selected ground state structures possess high confidence levels. Notably, new lower-energy structures have been discovered for boron-substituted fullerenes with substitution number ranging from seven to twelve and nitride-substituted fullerenes with substitution number ranging from seven to eleven. Fullerene ; Ground state ; Density functional theory ; Boron nitride ; Materials science ; Computational chemistry ; Binding energy ; Topology (electrical circuits) ; Chemistry ; Mathematics ; Combinatorics ; Nanotechnology ; Physics ; Atomic physics ; Organic chemistry Fullerene Chemistry and Applications ; Graphene research and applications ; Machine Learning in Materials Science
Authors: Di Pan | Jiayu Yu | Ke Du | Kexin Yan | Ling Ding | Yahong Zhang | Yi Tang
Source: Chemical Science (article, 2025-01-01)
Field: Chemistry — Inorganic Chemistry

Evaluation of the collaboration between intrinsic activity and diffusion: a descriptor for alkene epoxidation catalyzed by TS-1 The systemic evaluation of the collaboration between intrinsic activity of active sites and the substrate/product diffusion rate is a key challenge for rational optimization of reaction performance in alkene epoxidation. Herein, we constructed a series of TS-1 catalysts with adjustable local microenvironments around active sites to explore their performance in alkene epoxidation. This was achieved by controlling the contributions of classical and non-classical routines during the crystallization process. Based on the characterization of active sites, product diffusion and their alkene epoxidation activity, we proposed a descriptor, <i>R</i> <sub>a/d</sub>, for quantitative evaluation of the collaboration between intrinsic activity and product diffusion in TS-1 catalysts. This descriptor successfully explains the catalytic performance of various TS-1 catalysts including commercial TS-1 and guides further improvement of TS-1 in different alkene epoxidations. The optimal <i>R</i> <sub>a/d</sub> is found in various epoxidations, corresponding to peak epoxidation performance across different substrates due to the well-balanced intrinsic activity and diffusion rate. Alkene ; Catalysis ; Diffusion ; Rational design ; Substrate (aquarium) ; Chemistry ; Product (mathematics) ; Combinatorial chemistry ; Materials science ; Photochemistry ; Computational chemistry ; Organic chemistry ; Nanotechnology ; Thermodynamics ; Mathematics ; Physics ; Biology Zeolite Catalysis and Synthesis ; Polyoxometalates: Synthesis and Applications ; Catalysis and Oxidation Reactions