jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Naiyf S. Alharbi | Jamal M. Khaled | Khaled Alanazi | Shine Kadaikunnan | Ahmed S. Alobaidi
Source: Saudi Pharmaceutical Journal (article, 2023-04-20)
Field: Materials Science — Materials Chemistry

Biosynthesis of silver nanoparticles (Ag-NPs) using Senna alexandrina grown in Saudi Arabia and their bioactivity against multidrug-resistant pathogens and cancer cells There is no doubt that the risk of drug-resistant pathogens and cancer diseases is on the rise. So, the goal of this study was to find out how effective silver nanoparticles (Ag-NPs) made by <i>Senna alexandrina</i> are at fighting these threats. In this work, <i>S. alexandrina</i> collected from Medina, Saudi Arabia was used and the biosynthesis method was applied to produce the Ag-NPs. The characterization of Ag-NPs was done using different analytical techniques, including UV spectroscopy, FT-IR, TEM, and XRD analysis. The MIC, MBC, and MTT protocols were applied to confirm the bioactivity of the Ag-NPs as antibacterial and anticancer bioagents. The findings reported indicating that the aqueous extract of <i>S. alexandrina</i> leaves, grown naturally in Saudi Arabia, is ideal for the production of bioactive Ag-NPs. The hydroxyl, aliphatic, alkene, N-H bend of primary amines, C-H bonds, and C-O bonds of alcohol were detected in this product. The small, sphere-shaped particles (4-7 nm) were the most prevalent among the bioactive Ag-NPs produced in this work. These nanoparticles inhibited some important multidrug-resistant pathogens (MDRPs) (<i>Escherichia coli</i>, <i>Acinetobacter baumanii/haemolyticus</i>, <i>Staphylococcus epidermidis</i>, and Methicillin-resistant <i>Staphylococcus aureus</i> (MRSA)), as well as their ability to inhibit breast cancer cells (MCF-7 cells). The MIC of Ag-NPs ranged from 0.03 to 0.6 mg/mL, while their MBC ranged from 0.06 to 2.5 mg/mL. Anticancer activity test showed that IC<sub>50</sub> of the Ag-NPs against tested breast cancer cells was 61.9 ± 3.8 µg/mL. According to the current results, biosynthesis using <i>S. alexandrina</i> leaves grown naturally in Saudi Arabia was an ideal technique for producing bioactive Ag-NPs that could be used to combat a variety of MDRPs and cancer diseases. Staphylococcus epidermidis ; Antibacterial activity ; Multiple drug resistance ; Microbiology ; MTT assay ; Silver nanoparticle ; Chemistry ; Antimicrobial ; Traditional medicine ; In vitro ; Staphylococcus aureus ; Nanoparticle ; Biology ; Drug resistance ; Medicine ; Bacteria ; Materials science ; Biochemistry ; Nanotechnology Nanoparticles: synthesis and applications
Authors: Karel Asselman | Mohamed Haouas | Maarten Houlleberghs | Sambhu Radhakrishnan | Wauter Wangermez | Christine E. A. Kirschhock | Eric Breynaert
Source: Crystal Growth & Design (article, 2023-03-24)
Field: Chemistry — Inorganic Chemistry

Does Water Enable Porosity in Aluminosilicate Zeolites? Porous Frameworks versus Dense Minerals Recently identified zeolite precursors consisting of concentrated, hyposolvated homogeneous alkalisilicate liquids, hydrated silicate ionic liquids (HSIL), minimize correlation of synthesis variables and enable one to isolate and examine the impact of complex parameters such as water content on zeolite crystallization. HSIL are highly concentrated, homogeneous liquids containing water as a reactant rather than bulk solvent. This simplifies elucidation of the role of water during zeolite synthesis. Hydrothermal treatment at 170 °C of Al-doped potassium HSIL with chemical composition 0.5SiO<sub>2</sub>:1KOH:<i>x</i>H<sub>2</sub>O:0.013Al<sub>2</sub>O<sub>3</sub> yields porous merlinoite (MER) zeolite when H<sub>2</sub>O/KOH exceeds 4 and dense, anhydrous megakalsilite when H<sub>2</sub>O/KOH is lower. Solid phase products and precursor liquids were fully characterized using XRD, SEM, NMR, TGA, and ICP analysis. Phase selectivity is discussed in terms of cation hydration as the mechanism, allowing a spatial cation arrangement enabling the formation of pores. Under water deficient conditions, the entropic penalty of cation hydration in the solid is large and cations need to be entirely coordinated by framework oxygens, leading to dense, anhydrous networks. Hence, the water activity in the synthesis medium and the affinity of a cation to either coordinate to water or to aluminosilicate decides whether a porous, hydrated, or a dense, anhydrous framework is formed. Zeolite ; Anhydrous ; Aluminosilicate ; Crystallization ; Chemistry ; Chemical engineering ; Silicate ; Porosity ; Hydrothermal synthesis ; Hydrothermal circulation ; Phase (matter) ; Solvent ; Inorganic chemistry ; Water of crystallization ; Organic chemistry ; Catalysis Zeolite Catalysis and Synthesis ; Mesoporous Materials and Catalysis ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Soochan Lee | Dongsik Nam | D. ChangMo Yang | Wonyoung Choe
Source: Small (article, 2023-02-09)
Field: Chemistry — Inorganic Chemistry

Unveiling Hidden Zeolitic Imidazolate Frameworks Guided by Intuition‐Based Geometrical Factors Herein, synthesizable candidate topologies to form zeolitic imidazolate frameworks (ZIFs) are efficiently identified from over 2 000 000 hypothetical structures in zeolite databases, using structural descriptors extracted from known ZIFs. A combination of intuition-based structural descriptors, such as ring patterns, node numbers, and TOT bridging angles (T = tetrahedral metal nodes in zeolites and ZIFs), is used as data filters to eliminate topologies infeasible for ZIF formation. Carefully chosen structural descriptors facilitate the prediction of plausible ZIF topologies. To investigate potential applications as porous ZIFs, this work performs hydrogen adsorption screening and suggested notable target ZIFs. The collection of new plausible ZIFs, derived from the combined descriptors, will be a structural blueprint for synthetic chemists. Zeolitic imidazolate framework ; Network topology ; Tetrahedron ; Computer science ; Pyranose ; Intuition ; Materials science ; Imidazolate ; Topology (electrical circuits) ; Adsorption ; Nanotechnology ; Metal-organic framework ; Chemistry ; Mathematics ; Crystallography ; Stereochemistry ; Physical chemistry ; Combinatorics Metal-Organic Frameworks: Synthesis and Applications ; Polyoxometalates: Synthesis and Applications ; Machine Learning in Materials Science
Authors: Jingfa Li | Dukui Zheng | Wei Zhang
Source: Atmosphere (review, 2023-08-19)
Field: Materials Science — Materials Chemistry

Advances of Phase-Field Model in the Numerical Simulation of Multiphase Flows: A Review The phase-field model (PFM) is gaining increasing attention in the application of multiphase flows due to its advantages, in which the phase interface is treated as a narrow layer and phase parameters change smoothly and continually at this thin layer. Thus, the construction or tracking of the phase interface can be avoided, and the bulk phase and phase interface can be simulated integrally. PFM provides a useful alternative that does not suffer from problems with either the mass conservation or the accurate computation of surface tension. In this paper, the state of the art of PFM in the numerical modeling and simulation of multiphase flows is comprehensively reviewed. Starting with a brief description of historical developments in the PFM, we continue to take a tour into the basic concepts, fundamental theory, and mathematical models. Then, the commonly used numerical schemes and algorithms for solving the governing systems of PFM in the application of multiphase flows are presented. The various applications and representative results, especially in non-match density scenarios of multiphase flows, are reviewed. The primary challenges and research focus of PFM are analyzed and summarized as well. This review is expected to provide a valuable reference for PFM in the application of multiphase flows. Multiphase flow ; Computer science ; Interface (matter) ; Field (mathematics) ; Computation ; Focus (optics) ; Phase (matter) ; Conservation of mass ; Computer simulation ; Mechanics ; Simulation ; Algorithm ; Mathematics ; Physics Solidification and crystal growth phenomena ; Aluminum Alloy Microstructure Properties ; Metallurgical Processes and Thermodynamics
Authors: Shahin Sultana | Dildar Hossain | Md Mazherul Islam | Sarkar M. A. Kawsar
Source: Current Chemistry Letters (article, 2023-10-06)
Field: Chemistry — Organic Chemistry

Antifungal potential of mannopyranoside derivatives through computational and molecular docking studies against Candida albicans 1IYL and 1AI9 proteins Methyl α-D-mannopyranoside (MAM) is a naturally occurring carbohydrate derivative that has gained attention in drug discovery due to its potential therapeutic applications, particularly as an antifungal agent. In this study, we employed a computational approach to investigate the interactions between MAM and two Candida albicans antifungal proteins, 1IYL and 1AI9, through molecular docking simulations. Furthermore, we performed a PASS (Prediction of Activity Spectra for Substances) analysis to predict MAM potential biological activities, explored the pharmacokinetic properties and ADMET (absorption, distribution, metabolism, excretion, and toxicity) profiles, and optimized the MAM using the density functional theory (DFT) method. The molecular docking results revealed favorable binding interactions between MAM and the active sites of the 1IYL and 1AI9 proteins, suggesting potential antifungal activity. Additionally, the ADMET profiles indicated low toxicity and suitable drug-like properties, such as moderate metabolic stability and minimal risk of adverse effects. Furthermore, DFT optimization was performed to investigate the molecular geometry and electronic properties of MAM. The optimization results provided valuable information on the stability and reactivity of MAM, enabling a better understanding of its chemical behavior and potential modifications for enhanced activity. Finally, PASS prediction was employed to evaluate MAM's potential biological activities beyond its antifungal properties. The analysis revealed several potential activities, including antibacterial, antiviral, and immunomodulatory effects, expanding the scope for future research and therapeutic applications. In conclusion, this computational study sheds light on the molecular interactions, pharmacokinetic properties, ADMET profiles, DFT optimization, and PASSES predictions of MAM. These findings highlight the potential of MAM as a promising antifungal agent with favorable pharmacological properties. Chemistry ; Docking (animal) ; Candida albicans ; Antifungal drug ; Antifungal ; Computational biology ; Molecular dynamics ; Quantitative structure–activity relationship ; Drug ; Pharmacokinetics ; Combinatorial chemistry ; Computational chemistry ; Stereochemistry ; Biochemistry ; Pharmacology ; Biology ; Microbiology Synthesis and biological activity ; Carbohydrate Chemistry and Synthesis ; Bioactive Compounds and Antitumor Agents
Authors: Mikkel A. Christensen | Iulia Chiciudean | Piotr Jablonski | Ana‐Maria Tănase | Volha Shapaval | Hilde Hansen
Source: PLoS ONE (article, 2023-03-08)
Field: Materials Science — Biomaterials

Towards high-throughput screening (HTS) of polyhydroxyalkanoate (PHA) production via Fourier transform infrared (FTIR) spectroscopy of Halomonas sp. R5-57 and Pseudomonas sp. MR4-99 High-throughput screening (HTS) methods for characterization of microbial production of polyhydroxyalkanoates (PHA) are currently under investigated, despite the advent of such systems in related fields. In this study, phenotypic microarray by Biolog PM1 screening of Halomonas sp. R5-57 and Pseudomonas sp. MR4-99 identified 49 and 54 carbon substrates to be metabolized by these bacteria, respectively. Growth on 15 (Halomonas sp. R5-57) and 14 (Pseudomonas sp. MR4-99) carbon substrates was subsequently characterized in 96-well plates using medium with low nitrogen concentration. Bacterial cells were then harvested and analyzed for putative PHA production using two different Fourier transform infrared spectroscopy (FTIR) systems. The FTIR spectra obtained from both strains contained carbonyl-ester peaks indicative of PHA production. Strain specific differences in the carbonyl-ester peak wavenumber indicated that the PHA side chain configuration differed between the two strains. Confirmation of short chain length PHA (scl-PHA) accumulation in Halomonas sp. R5-57 and medium chain length PHA (mcl-PHA) in Pseudomonas sp. MR4-99 was done using Gas Chromatography-Flame Ionization Detector (GC-FID) analysis after upscaling to 50 mL cultures supplemented with glycerol and gluconate. The strain specific PHA side chain configurations were also found in FTIR spectra of the 50 mL cultures. This supports the hypothesis that PHA was also produced in the cells cultivated in 96-well plates, and that the HTS approach is suitable for analysis of PHA production in bacteria. However, the carbonyl-ester peaks detected by FTIR are only indicative of PHA production in the small-scale cultures, and appropriate calibration and prediction models based on combining FTIR and GC-FID data needs to be developed and optimized by performing more extensive screenings and multivariate analyses. Polyhydroxyalkanoates ; Fourier transform infrared spectroscopy ; Halomonas ; Bacteria ; Chemistry ; Pseudomonas ; Strain (injury) ; Nuclear chemistry ; Microbiology ; Food science ; Biology ; Halophile ; Chemical engineering biodegradable polymer synthesis and properties ; Microplastics and Plastic Pollution ; Biopolymer Synthesis and Applications
Authors: Austin O. Atsango | Tobias Morawietz | Ondřej Maršálek | Thomas E. Markland
Source: The Journal of Chemical Physics (article, 2023-08-15)
Field: Chemistry — Spectroscopy

Developing machine-learned potentials to simultaneously capture the dynamics of excess protons and hydroxide ions in classical and path integral simulations The transport of excess protons and hydroxide ions in water underlies numerous important chemical and biological processes. Accurately simulating the associated transport mechanisms ideally requires utilizing ab initio molecular dynamics simulations to model the bond breaking and formation involved in proton transfer and path-integral simulations to model the nuclear quantum effects relevant to light hydrogen atoms. These requirements result in a prohibitive computational cost, especially at the time and length scales needed to converge proton transport properties. Here, we present machine-learned potentials (MLPs) that can model both excess protons and hydroxide ions at the generalized gradient approximation and hybrid density functional theory levels of accuracy and use them to perform multiple nanoseconds of both classical and path-integral proton defect simulations at a fraction of the cost of the corresponding ab initio simulations. We show that the MLPs are able to reproduce ab initio trends and converge properties such as the diffusion coefficients of both excess protons and hydroxide ions. We use our multi-nanosecond simulations, which allow us to monitor large numbers of proton transfer events, to analyze the role of hypercoordination in the transport mechanism of the hydroxide ion and provide further evidence for the asymmetry in diffusion between excess protons and hydroxide ions. Proton ; Ion ; Hydroxide ; Ab initio ; Molecular dynamics ; Chemistry ; Diffusion ; Ab initio quantum chemistry methods ; Chemical physics ; Path integral formulation ; Density functional theory ; Proton transport ; Computational chemistry ; Physics ; Thermodynamics ; Quantum ; Nuclear physics ; Molecule ; Quantum mechanics ; Inorganic chemistry Advanced NMR Techniques and Applications ; Spectroscopy and Quantum Chemical Studies ; Quantum, superfluid, helium dynamics
Authors: Chris Cadigan | Chris Chmura | Gus Floerchinger | Péter Frankl | Simon A. Hunt | Søren Højgaard Jensen | Cyrus Boushehri | Tyrone L. Vincent | Robert J. Braun | Neal P. Sullivan
Source: Journal of Power Sources (article, 2023-05-03)
Field: Materials Science — Materials Chemistry

Performance characterization of metal-supported solid-oxide fuel cell stacks at elevated pressure Stack (abstract data type) ; Anode ; Nuclear engineering ; Methane ; Natural gas ; Solid oxide fuel cell ; Oxide ; Materials science ; Cabin pressurization ; Waste management ; Chemical engineering ; Chemistry ; Electrode ; Composite material ; Engineering ; Metallurgy ; Computer science Advancements in Solid Oxide Fuel Cells ; Electrocatalysts for Energy Conversion ; Fuel Cells and Related Materials
Authors: Stefan Bruns | Diana Krüger | Silvia Galli | D. C. Florian Wieland | Jörg U. Hammel | Felix Beckmann | Ann Wennerberg | Regine Willumeit‐Römer | Berit Zeller‐Plumhoff | Julian Moosmann
Source: Bioactive Materials (article, 2023-05-19)
Field: Materials Science — Biomaterials

On the material dependency of peri-implant morphology and stability in healing bone The microstructural architecture of remodeled bone in the peri-implant region of screw implants plays a vital role in the distribution of strain energy and implant stability. We present a study in which screw implants made from titanium, polyetheretherketone and biodegradable magnesium-gadolinium alloys were implanted into rat tibia and subjected to a push-out test four, eight and twelve weeks after implantation. Screws were 4 mm in length and with an M2 thread. The loading experiment was accompanied by simultaneous three-dimensional imaging using synchrotron-radiation microcomputed tomography at 5 μm resolution. Bone deformation and strains were tracked by applying optical flow-based digital volume correlation to the recorded image sequences. Implant stabilities measured for screws of biodegradable alloys were comparable to pins whereas non-degradable biomaterials experienced additional mechanical stabilization. Peri-implant bone morphology and strain transfer from the loaded implant site depended heavily on the biomaterial utilized. Titanium implants stimulated rapid callus formation displaying a consistent monomodal strain profile whereas the bone volume fraction in the vicinity of magnesium-gadolinium alloys exhibited a minimum close to the interface of the implant and less ordered strain transfer. Correlations in our data suggest that implant stability benefits from disparate bone morphological properties depending on the biomaterial utilized. This leaves the choice of biomaterial as situational depending on local tissue properties. Biomaterial ; Materials science ; Implant ; Biomedical engineering ; Titanium ; Osseointegration ; Bone healing ; Nanotechnology ; Surgery ; Metallurgy ; Medicine Magnesium Alloys: Properties and Applications ; Bone Tissue Engineering Materials ; Titanium Alloys Microstructure and Properties
Authors: Xu Du | Suxia Xie | Haoxuan Nan | Siyi Sun | Weiwei Shen | Jingcheng Yang | Xin Guan
Source: Photonics (article, 2023-08-28)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Chiral Quasi-Bound States in the Continuum of a Dielectric Metasurface for Optical Monitoring and Temperature Sensing Chiral BIC can reach ultrahigh quality factors (Q-factor) based on its asymmetry, with broken mirror symmetries and in-plane inversion. Only by in-plane structural perturbation can chiral quasi-BIC (q-BIC) appear, so it is much more realizable and reasonable for the manufacturers in practical productions and fabrications considering the technology and means that are available. In this paper, we design a new dielectric metasurface employing H-shaped silica meta-atoms in the lattice, which is symmetrical in structure, obtaining chiral BIC with ultrahigh Q-factor (exceeding 105). In this process, we change the length of the limbs of the structure to observe the specific BICs. Previous scholars have focused on near-infrared-wavelength bands, while we concentrate on the terahertz wavelength band (0.8–1 THz). We found that there is more than one BIC, thus realizing multiple BICs in the same structure; all of them exhibit excellent circular dichroism (CD) (the maximum value of CD is up to 0.8127) for reflectance and transmittance, which provides significant and unique guidance for the design of multi-sensors. Meanwhile, we performed temperature sensing with chiral BIC; the sensitivity for temperature sensing can reach 13.5 nm/°C, which exhibits high accuracy in measuring temperature. As a consequence, the result proposed in this study will make some contributions to advanced optical imaging, chiral sensors with high frequency and spectral resolution, optical monitoring of environmental water quality, multiple sensors, temperature sensing, biosensing, substance inspection and ambient monitoring and other relevant optical applications. Terahertz radiation ; Dielectric ; Materials science ; Wavelength ; Infrared ; Optics ; Optoelectronics ; Photonic crystal ; Lattice (music) ; Transmittance ; Physics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Electromagnetic Scattering and Analysis
Authors: Rui Ribeiro | André Pilastri | Carla Victoria Rodrigues de Moura | José Carlos Morgado | Paulo Cortez
Source: Neural Computing and Applications (article, 2023-05-03)
Field: Materials Science — Polymers and Plastics

A data-driven intelligent decision support system that combines predictive and prescriptive analytics for the design of new textile fabrics Abstract In this paper, we propose an Intelligent Decision Support System (IDSS) for the design of new textile fabrics. The IDSS uses predictive analytics to estimate fabric properties (e.g., elasticity) and composition values (% cotton) and then prescriptive techniques to optimize the fabric design inputs that feed the predictive models (e.g., types of yarns used). Using thousands of data records from a Portuguese textile company, we compared two distinct Machine Learning (ML) predictive approaches: Single-Target Regression (STR), via an Automated ML (AutoML) tool, and Multi-target Regression, via a deep learning Artificial Neural Network. For the prescriptive analytics, we compared two Evolutionary Multi-objective Optimization (EMO) methods (NSGA-II and R-NSGA-II) when optimizing 100 new fabrics, aiming to simultaneously minimize the physical property predictive error and the distance of the optimized values when compared with the learned input space. The two EMO methods were applied to design of 100 new fabrics. Overall, the STR approach provided the best results for both prediction tasks, with Normalized Mean Absolute Error values that range from 4% (weft elasticity) to 11% (pilling) in terms of the fabric properties and a textile composition classification accuracy of 87% when adopting a small tolerance of 0.01 for predicting the percentages of six types of fibers (e.g., cotton). As for the prescriptive results, they favored the R-NSGA-II EMO method, which tends to select Pareto curves that are associated with an average 11% predictive error and 16% distance. Predictive analytics ; Artificial neural network ; Computer science ; Artificial intelligence ; Analytics ; Machine learning ; Textile ; Elasticity (physics) ; Data mining ; Materials science Textile materials and evaluations ; Industrial Vision Systems and Defect Detection ; Advanced Multi-Objective Optimization Algorithms