jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Shuyu Yu | Yibo Lu | Dandan Du | Rankun Wu | Xiang Ji | Hao Li
Source: Processes (article, 2023-10-10)
Field: Materials Science — Materials Chemistry

Improved Laccase Encapsulation in Copper-Doped Zeolitic Imidazolate Framework-8 for Reactive Black 5 Decolorization As the largest group of synthetic dyes, azo dyes can pose various health and environmental risks due to their widespread use and challenging degradation. Laccases are efficient green biocatalysts for the degradation of organic pollutants. Herein, we report the in situ packaging of laccase in copper-doped zeolitic imidazolate framework-8 (ZIF-8) for the decolorization of reactive black 5, which is a model azo dye. The immobilization support (Cu5/mZIF-8) was obtained via lowering the precursor ratio of ZIF-8 and incorporating copper ions during the synthesis process. Cu5/mZIF-8 were found to be nanospheres with an average diameter of around 150 nm. Laccase encapsulated in Cu5/mZIF-8 showed an activity recovery of 75.6%, which was 2.2 times higher than that of the laccase embedded in ZIF-8. Meanwhile, the immobilized laccase (Lac@Cu5/mZIF-8) showed a higher catalytic activity in organic solvents than that of the free enzyme. In the presence of a mediator, Lac@Cu5/mZIF-8 could remove 95.7% of reactive black 5 in 40 min. After four consecutive cycles, the dye decolorization efficiency declined to 28%. About four transformation products of reactive black 5 were identified via LC-MS analysis, and the potential decolorization mechanism was proposed. The results indicated that the immobilized laccase could be used as an efficient biocatalyst in dye decolorization. Laccase ; Imidazolate ; Chemistry ; Copper ; Catalysis ; Nuclear chemistry ; Zeolitic imidazolate framework ; Inorganic chemistry ; Organic chemistry ; Adsorption ; Metal-organic framework ; Enzyme Advanced Nanomaterials in Catalysis ; Enzyme-mediated dye degradation ; Nanomaterials for catalytic reactions
Authors: Maksims Fiļipovičs
Source: Research for Rural Development/Research for Rural Development (Online) (article, 2023-12-17)
Field: Chemistry — Analytical Chemistry

Hyperspectral imaging for early detection of foliar fungal diseases on small grain cereals: a minireview Foliar fungal diseases of small grain cereals are economically among the most important diseases worldwide and in the Baltics. Finding an effective, reliable, and easily accessible method for plant disease diagnosis still presents a challenge. Currently used methods include visual examination of the affected plant, morphological characterization of isolated pathogens and different molecular, and serological methods. All of these methods have important limitations, especially for large-area applications. Hyperspectral imaging is a promising technique to assess fungal diseases of plants, as it is a non-invasive, indirect detection method, where the plant’s responses to the biotic stress are identified as an indicator of the disease. Hyperspectral measurements can reveal a relationship between the spectral reflectance properties of plants and their structural characteristics, pigment concentrations, water level, etc., which are considerably influenced by biotic plant stress. Despite the high accuracy of the information obtained from hyperspectral detectors, the interpretation is still problematic, as it is influenced by various circumstances: noise level, lighting conditions, abiotic stress level, a complex interaction of the genotype and the environment, etc. The application of hyperspectral imaging in everyday farming practice will potentially allow farmers to obtain timely and precise information about the development of diseases and affected areas. This review provides an introduction into issues of hyperspectral imaging and data analysis and explores the published reports of worldwide research on the use of hyperspectral analysis in the detection of foliar fungal diseases of small-grain cereals. Hyperspectral imaging ; Remote sensing ; Plant disease ; Abiotic component ; Biotechnology ; Biology ; Computer science ; Environmental science ; Ecology ; Geography Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Essential Oils and Antimicrobial Activity
Authors: Candelaria Tejada-Tovar | Ángel Villabona-Ortíz | Fabián Aguilar-Bermúdez | Yerardin Pájaro-Moreno | Ángel Darío González-Delgado
Source: Processes (article, 2023-10-31)
Field: Chemistry — Analytical Chemistry

Evaluation of Adsorbent Biomaterials Based on Coconut Mesocarp for Treatment of Wastewater Contaminated with Tartrazine Dye The presence of synthetic dyes in industrial wastewater poses significant environmental and health concerns due to their persistent nature and potential toxicity. Tartrazine is a synthetic yellow dye known for its stability and resistance to conventional treatment methods. As a result, its discharge into natural water bodies can lead to adverse ecological impacts and can jeopardize public health. The objective of this work was to functionalize coconut shells (CSs), coconut cellulose (CC), and modified coconut cellulose (MCC) bioadsorbents with cetyl trimethyl ammonium chloride (CTAC) for their use in the elimination by adsorption of the dye tartrazine in aqueous solutions. CC was synthesized through a double extraction with sodium hydroxide, and a chemical treatment was performed with CTAC at 100 mmol L−1. The final dye concentration was determined through UV-Vis at 500 nm. An FTIR analysis showed multiple active sites, represented in groups such as hydroxyl, COO-, NHx-, and hydrocarbon compounds. Increasing the initial concentration had a positive effect on the efficiency of the process, reaching 99% removal with an adsorption capacity of 11.89 mg/g at equilibrium using MCC. The test showed that equilibrium was reached after 30 min. Initially, the removal of the dyes was rapid, about 97% of the contaminant being removed in the first 5 min. The Langmuir and Freundlich models were satisfactorily fitted to the adsorption isotherm, showing physical and chemical adsorption. It can be concluded that MCC is a promising bioadsorbent for the removal of tartrazine dye in aqueous solutions. Tartrazine ; Adsorption ; Freundlich equation ; Chemistry ; Nuclear chemistry ; Aqueous solution ; Cellulose ; Wastewater ; Langmuir ; Contamination ; Langmuir adsorption model ; Sodium hydroxide ; Chromatography ; Organic chemistry ; Waste management Dye analysis and toxicity ; Adsorption and biosorption for pollutant removal ; Mercury impact and mitigation studies
Authors: Amna Ismail | Nuzhat Sial | Rakhshanda Rehman | Sobia Abid | Muhammad Shoaib Ismail
Source: Toxicology Reports (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Survival, growth, behavior, hematology and serum biochemistry of mice under different concentrations of orally administered amorphous silica nanoparticle Silica nanoparticles (SiNPs) are used extensively in consumer products and biomedical research basically due to ease of production and low cost. However, insufficient literature is reported regarding the toxicity and biocompatibility of SiNPs. The present study aimed to investigate the potential role of amorphous SiNPs on survival, growth, behavioral alterations, hematology and serum biochemistry of mice at four concentrations (control, 50, 100 and 150 mg/kg/day) of an oral supplementation for a period of 3 months. Signs of toxicity (lethargy, nausea, coma, tremors, vomiting and diarrhea, etc.) were noted at 9:00 am and 9:00 pm (twice a day) and the body weight of each of these mice was measured every week. The data were subjected to mean, standard deviation (S.D). Moreover, One-Way Analysis of Variance (ANOVA) and Dunnett's test were applied for analysis of statistical significance between groups by using SPSS software, version 20. All the mice survived with minor alterations in behavior and no significant weight changes were observed during the stipulated time period. Complete blood count (CBC) analysis indicated non-significant (P ≥ 0.05) systemic dysfunctions of organ systems. However, there was elevation in the level of AST and ALT in the analysis of serum biochemistry, while the values of all other examined parameters were not-significant (P ≥ 0.05). The study concluded that orally administered large silica nanoparticles up to the dose level of 150 mg/kg/day are nontoxic for the in vivo use in mice. Lethargy ; Nausea ; Toxicity ; Hematology ; Vomiting ; Analysis of variance ; Medicine ; In vivo ; Internal medicine ; Pharmacology ; Animal science ; Chemistry ; Biology ; Biotechnology Nanoparticles: synthesis and applications ; Immunotoxicology and immune responses ; Advanced Drug Delivery Systems
Authors: Xu Yi | Lichirui Zhang | Richard A. Friesner | Ann E. McDermott
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2023-01-25)
Field: Chemistry — Spectroscopy

Predicted and Experimental NMR Chemical Shifts at Variable Temperatures: The Effect of Protein Conformational Dynamics NMR chemical shifts provide a sensitive probe of protein structure and dynamics. Prediction of shifts, and therefore interpretation of shifts, particularly for the frequently measured amidic <sup>15</sup> N sites, remains a tall challenge. We demonstrate that protein <sup>15</sup> N chemical shift prediction from QM/MM predictions can be improved if conformational variation is included via MD sampling, focusing on the antibiotic target, <i>E. coli</i> Dihydrofolate reductase (DHFR). Variations of up to 25 ppm in predicted <sup>15</sup> N chemical shifts are observed over the trajectory. For solution shifts the average of fluctuations on the low picosecond timescale results in a superior prediction to a single optimal conformation. For low temperature solid state measurements, the histogram of predicted shifts for locally minimized snapshots with specific solvent arrangements sampled from the trajectory explains the heterogeneous linewidths; in other words, the conformations and associated solvent are 'frozen out' at low temperatures and result in inhomogeneously broadened NMR peaks. We identified conformational degrees of freedom that contribute to chemical shift variation. Backbone torsion angles show high amplitude fluctuations during the trajectory on the low picosecond timescale. For a number of residues, including I60, ψ varies by up to 60º within a conformational basin during the MD simulations, despite the fact that I60 (and other sites studied) are in a secondary structure element and remain well folded during the trajectory. Fluctuations in ψ appear to be compensated by other degrees of freedom in the protein, including φ of the succeeding residue, resulting in "rocking" of the amide plane with changes in hydrogen bonding interactions. Good agreement for both room temperature and low temperature NMR spectra provides strong support for the specific approach to conformational averaging of computed chemical shifts. Chemical shift ; Chemistry ; Dihedral angle ; Picosecond ; Molecular dynamics ; Crystallography ; Hydrogen bond ; Chemical physics ; Computational chemistry ; Molecule ; Physics ; Physical chemistry ; Optics Advanced NMR Techniques and Applications ; Molecular spectroscopy and chirality ; Protein Structure and Dynamics
Authors: Shuai Liu | Honggao Liu | Jieqing Li | Yuanzhong Wang
Source: Research Square (preprint, 2023-04-27)
Field: Chemistry — Analytical Chemistry

FT-MIR combined with 3DCOS-ResNet model for rapid identification of wild and cultivated Gastrodia elata <title>Abstract</title> Wild <italic>Gastrodia elata</italic> resources are in short supply and the market is dominated by cultivated <italic>Gastrodia elata</italic> resources and the medicinal value of both is very different. It is significant to find a highly accurate and stable technique to identify wild and cultivated <italic>Gastrodia elata</italic>. It could prevent market fraud and protect the rights of consumers. In this context, this study is the first to combine three-dimensional correlated spectral (3DCOS) images with deep learning to identify wild and cultivated <italic>Gastrodia elata</italic>. Also, partial least squares discrimination analysis (PLS-DA) and support vector machine (SVM) models are compared with this model. The PLS-DA and SVM models are built based on Fourier transform mid-infrared (FT-MIR) spectral data after nine different preprocessing. The PLS-DA model with second-order derivatives (2D) gives the best results when comparing the effects of the models with different preprocessing. the SVM model with parameters <italic>c</italic>, <italic>g</italic> in a reasonable range also gives satisfactory model results. The advantage of the deep learning model over them is that no processing of the original spectral data is required. With only 46 iterations, the accuracy of the model is stable at 100% for the training set, test set and external validation set. The excellent performance of the model allows it to be used as a technical reference to solve studies on the qualitative aspects of <italic>Gastrodia elata</italic>. Gastrodia elata ; Preprocessor ; Artificial intelligence ; Support vector machine ; Computer science ; Set (abstract data type) ; Identification (biology) ; Pattern recognition (psychology) ; Machine learning ; Mathematics ; Biology ; Botany Spectroscopy and Chemometric Analyses ; Biological and pharmacological studies of plants ; Traditional Chinese Medicine Analysis
Authors: Anant Babu Marahatta
Source: Asian Journal of Applied Chemistry Research (article, 2023-06-17)
Field: Chemistry — Organic Chemistry

Gaussian-External Methodology Predicted Crystal Structures, Molecular Energetics, and Potential Energy Surface of the Crystalline Molecular Compass Nanoscience, Nanotechnology, and Molecular machines have triggered the scientists of wide-ranging disciplines alike for decades now, offered the most innovative technologies to maneuver the nanoscale devices molecule by molecule. In this arena of the nano-metric world, the strategical laboratorial syntheses &amp; computational designations of the prototype molecules/nanomaterials and the most probable techniques for their effective functionalization always stand as mandatory credentials. Among various types of functionalizing nanomaterials, the topologically closed Si and -(Si-O)x- based dipolar crystalline macrocyclic molecular compounds exhibiting macroscopic compass/gyroscope like functions at ambient temperatures have attracted the greatest admirations. In this outlook, the research works presented herewith by employing a Gaussian-external methodology for the quantum mechanical characterizations of the crystal structures, computations of the molecular energetics, and derivations of the rotational potential energy surface (PES) of the experimentally synthesized difluoro- /dichloro- phenylene encapsulated amphidynamic/non-amphidynamic crystalline ROT-2F/ROT-2Cl siloxaalkane macrocages can be taken as a stepping stone. Under the standardized interface of Gaussian, we ran SCC-DFTB scheme via the user's script as an external program, and accessed the PES scanning techniques of the former plus the "Dispersion Energy correction" features of the latter computationally. The results reported herein are mainly found to (a) validate the X-ray produced degenerate and non-degenerate crystal structures, (b) justify the experimentally observed structural deformations of the static siloxaalkane spokes, (c) quantize the free-volume units available around the rotator, (d) disclose the energy barrier Ea to be overcome by the rotator while exhibiting 1p-flipping motion, (e) foresee the structural requisites to be adopted for designing functional crystalline free-rotors, etc. It is believed that present theoretical study enlightens us about the most essential structural and dynamical features of the gyroscopic nanostructures &amp; molecular compasses quantitatively. Nanomaterials ; Potential energy surface ; Crystal (programming language) ; Nanotechnology ; Molecule ; Degenerate energy levels ; Materials science ; Chemical physics ; Gaussian ; Compass ; Nanoscopic scale ; Potential energy ; Computational chemistry ; Physics ; Chemistry ; Computer science ; Classical mechanics ; Quantum mechanics Supramolecular Chemistry and Complexes ; Advanced Chemical Physics Studies ; Crystallography and molecular interactions
Authors: Samantha Tetef | Ajith Pattammattel | Yong S. Chu | Maria K. Y. Chan | Gerald T. Seidler
Source: ChemRxiv (preprint, 2023-08-17)
Field: Materials Science — Materials Chemistry

Accelerating Nano-XANES Imaging via Feature Selection We investigate feature selection algorithms to reduce experimental time of nanoscale imaging via X-ray Absorption Fine Structure spectroscopy (nano-XANES imaging). Our approach is to decrease the required number of measurements in energy while retaining enough information to, for example, identify spatial domains and the corresponding crystallographic or chemical phase of each domain. We find sufficient accuracy in inferences when comparing predictions using the full energy point spectra to the reduced energy point subspectra recommended by feature selection. As a representative test case in the hard X-ray regime, we find that the total experimental time of nano-XANES imaging can be reduced by ~80% for a study of Fe-bearing mineral phases. These improvements capitalize on using the most common analysis procedure – linear combination fitting onto a reference library – to train the feature selection algorithm and thus learn the optimal measurements within this analysis context. We compare various feature selection algorithms such as Recursive Feature Elimination (RFE), random forest, and decision tree, and find that RFE produces moderately better recommendations. We further explore practices to maintain reliable feature selection results, especially when there is large uncertainty in the system, thus requiring a more expansive reference library, resulting in high linear mutual dependence within the reference set. More generally, the class of spectroscopic imaging experiments that scan energy by energy (rather than collecting an entire spectrum at once) is well-addressed by feature selection, and our approach is equally applicable to the soft X-ray regime via Scanning Transmission X-ray Microscopy (STXM) experiments. Feature selection ; Feature (linguistics) ; XANES ; Computer science ; Context (archaeology) ; Energy (signal processing) ; Artificial intelligence ; Random forest ; Pattern recognition (psychology) ; Algorithm ; Spectroscopy ; Mathematics ; Physics ; Statistics ; Geology Machine Learning in Materials Science ; Advanced X-ray and CT Imaging ; Radiomics and Machine Learning in Medical Imaging
Authors: M. S. Horetski | N. S. Frolova | V. M. Shkumatov
Source: Proceedings of the National Academy of Sciences of Belarus Chemical Series (article, 2023-06-05)
Field: Materials Science — Materials Chemistry

Lipophilicity of BODIPY fluorophores and their distribution in 1-octanol–water system The work covers synthesis and lipophilicity estimation of several BODIPY dyes. For these compounds, the distribution between 1-octanol and water layers is experimentally described and the corresponding partition coefficients LogP are calculated. The experimental LogP values are compared with popular fragment-based methods XLopP3, ALogPS, WLogP, SILICOS-IT and MLogP. Additionally, the hydrophobic and polar surface areas are found with quantum-mechanical calculations. That allowed to find a correlation between the LogP coefficient and the molecular surface topology, as well as to determine the corresponding incremental values of the methyl, acetyl, and phenyl substituents. Lipophilicity ; Partition coefficient ; Octanol ; BODIPY ; Polar surface area ; Chemistry ; Polar ; Computational chemistry ; Molecular dynamics ; Organic chemistry ; Molecule ; Fluorescence ; Physics Luminescence and Fluorescent Materials ; Photochemistry and Electron Transfer Studies ; Molecular Sensors and Ion Detection
Authors: Mikayla Browning | Alexandra Jefferson | Jazz Geter | Kesete Ghebreyessus
Source: Photochem (article, 2023-10-24)
Field: Materials Science — Biomaterials

Metal Ion-Induced Formation of Metallogels by Visible-Light-Responsive Phenylalanine-Functionalized Arylazopyrazole Ligands A visible-light-responsive arylazopyrazole-functionalized phenylalanine (4-MeS-AAP-NF) derived ligand was designed and synthesized, and it was found to form metallogels with reversible photo-responsive properties in mixed methanol/water (MeOH/H2O) solvents. The gelation behavior of the 4-MeS-AAP-NF ligand in the presence of different divalent metal ions in mixed methanol/water (MeOH/H2O) solvents at pH~11.60 was studied. It was found that the 4-MeS-AAP-NF ligand alone could not self-assemble to form any gels. However, in the presence of divalent metal ions, it readily formed the assembled metallogels in an alkaline aqueous/methanol solution with various morphologies. The results suggest that the gelation process was triggered by divalent metal ions. The presence of the AAP moiety in the gel matrix rendered the metallogel assemblies photo-responsive, and the reversible gel-to-sol phase transition was studied by UV-vis spectroscopy. The gels showed a slow, reversible visible-light-induced gel-to-sol phase transition under blue (λ = 405 nm) and then sol-to-gel transition by green light (λ = 530 nm) irradiation, resulting in the re-formation of the original gel state. The morphology and viscoelastic properties of the yellow–orange opaque metallogels were characterized by scanning electron microscopy (SEM) and rheological measurement, respectively. Chemistry ; Aqueous solution ; Divalent ; Metal ions in aqueous solution ; Moiety ; Ligand (biochemistry) ; Methanol ; Photochemistry ; Inorganic chemistry ; Metal ; Nuclear chemistry ; Organic chemistry Supramolecular Self-Assembly in Materials ; Photochromic and Fluorescence Chemistry ; Nanoparticle-Based Drug Delivery
Authors: Xijun Wang | Kaihang Shi | Anyang Peng | Randall Q. Snurr
Source: EES Catalysis (article, 2023-11-16)
Field: Materials Science — Materials Chemistry

Probing the structure–property relationships of supported copper oxide nanoclusters for methane activation Amorphous metal-oxide nanoclusters are investigated using DFT and machine learning for selective oxidation of methane. Nanoclusters ; Property (philosophy) ; Methane ; Copper ; Copper oxide ; Materials science ; Oxide ; Business ; Chemical engineering ; Chemistry ; Nanotechnology ; Metallurgy ; Engineering ; Organic chemistry Catalytic Processes in Materials Science ; Advanced Condensed Matter Physics ; Nanocluster Synthesis and Applications
Authors: Mikhail Kurbakov | Valentina Sulimova
Source: The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences (article, 2023-05-12)
Field: Materials Science — Surfaces, Coatings and Films

HIGH-PERFORMANCE TWO-LEVEL PARALLEL COMPUTING SCHEME FOR NANOPARTICLES DETECTION IN SEM IMAGES Abstract. In our previous work, an exponential approximation (EA) method was proposed for the detection of nanoparticles in scanning electron microscope (SEM) images. It shows the best quality of nanoparticle detection compared to other methods. But its main drawback is that it takes a lot of time. In this paper, we propose a two-level parallel computing scheme and a corresponding high-performance python+MPI implementation of the EA method. Experiments have shown that the developed parallel implementation can significantly speed up the computational process. Python (programming language) ; Computer science ; Scanning electron microscope ; Scheme (mathematics) ; Exponential function ; Nanoparticle ; Speedup ; Process (computing) ; Computational science ; Parallel computing ; Materials science ; Nanotechnology ; Mathematics ; Optics ; Physics ; Operating system Electron and X-Ray Spectroscopy Techniques ; Advanced Neural Network Applications