jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Sandeep Eswaran Panchu | Saranya Sekar | Elayaraja Kolanthai | S. Moorthy Babu | Narayana Kalkura Subbaraya
Source: Crystals (article, 2023-01-24)
Field: Chemistry — Analytical Chemistry

Extremely Fast and Efficient Removal of Congo Red Using Cationic-Incorporated Hydroxyapatite Nanoparticles (HAp: X (X = Fe, Ni, Zn, Co, and Ag)) Congo red (CR) is a stable anionic diazo dye that causes allergic reactions with carcinogenic properties. The rapid removal of CR using cation-incorporated nanohydroxyapatite (pristine HAp: X (X = Fe, Ni, Zn, Co, and Ag)) was investigated. The pristine and cation ion-doped HAp adsorbents were coprecipitated and subjected to hydrothermal and ultrasound treatments and subsequent microwave drying. The dopant ions significantly engineered the crystallite size, crystallinity, particle size (decreased 38–77%), shape (a rod to sphere modification by the incorporation of Ag+, Ni2+, and Co2+ ions), and colloidal stability (CS) of the adsorbent. These modifications aided in the rapid removal of the CR dye (98%) within one minute, and the CR adsorption rate was found to be significantly higher (93–99%) compared to previously reported rates. Furthermore, the kinetic, Langmuir, Freundlich, and DKR isotherms and thermodynamic results confirmed that the CR adsorption on the HAp was due to the strong chemical adsorption process. The order of the maximum CR adsorption capacity was Fe-HAp &gt; HAp &gt; Ag-HAp &gt; Co-HAp &gt; Zn-HAp. Whereas the CR regeneration efficiency was Fe-HAp (92%) &gt; Ag-HAp (42%) &gt; Ni-HAp (30%), with the other adsorbents exhibiting a poor recycling efficiency (1–16%). These results reveal Fe-HAp as a potential adsorbent for removing CR without the formation of byproducts. Adsorption ; Congo red ; Crystallinity ; Nuclear chemistry ; Crystallite ; Freundlich equation ; Hydrothermal circulation ; Chemistry ; Langmuir ; Langmuir adsorption model ; Nanoparticle ; Materials science ; Inorganic chemistry ; Chemical engineering ; Nanotechnology ; Metallurgy ; Organic chemistry Dye analysis and toxicity ; Adsorption and biosorption for pollutant removal ; Dyeing and Modifying Textile Fibers
Authors: A. Navarro-Badilla | G. Calderón‐Ayala | Y. Delgado‐Beleño | M. C. Heras-Sánchez | R. Britto Hurtado | J.E. Leal-Pérez | A. Macias | M. Cortez-Valadez
Source: ACS Omega (article, 2023-09-07)
Field: Materials Science — Materials Chemistry

Green Synthesis for Carbon Quantum Dots via <i>Opuntia ficus-indica</i> and <i>Agave maximiliana</i>: Surface-Enhanced Raman Scattering Sensing Applications In this study, we present an alternative method for synthesizing carbon quantum dots (CQDs) using a green synthesis approach via extracts from <i>Agave maximiliana</i> and <i>Opuntia ficus-indica</i><i>(Ofi)</i>. The extracts from both plants were used as the carbon source for the CQDs. The synthesis method employs mesoporous zeolite 4A as a refractory for the thermal treatment of the samples. Transmission electron microscopy analysis established that the size of the CQDs shows a narrow distribution centered around 2 nm with a maximum size of less than 3 nm for both cases. The CQDs exhibit absorption bands associated with π-π* transitions located around 220 nm. In both cases, photoluminescence (PL) phenomenon was detected by irradiating the samples with a UV wavelength and detecting emissions close to the blue wavelength. Additionally, both kinds of CQDs were tested as surface-enhanced Raman scattering (SERS) substrates against methylene blue (MB), indicating an enhancement associated with ring deformation and stretching modes of the v(C-C) and v(C-N) bonds located around 1400 and 1620 cm<sup>-1</sup>, respectively. Complementarily, in the framework of density functional theory, H<sub>2<i>n</i></sub>C<sub>2(2<i>m</i>+1)</sub> structures (with <i>n</i> = 3-5 and <i>m</i> = 1-3) were used as a theoretical representation of CQDs in interaction with the MB molecule. It is used for developing the analysis of charge transfer effects between both systems and for specifying elements that generate the SERS effect associated with the chemical enhancement mechanism. Agave ; Ficus ; Raman scattering ; Carbon fibers ; Raman spectroscopy ; Optoelectronics ; Nanotechnology ; Materials science ; Botany ; Physics ; Optics ; Biology ; Composite material Carbon and Quantum Dots Applications ; Selenium in Biological Systems ; Quantum Dots Synthesis And Properties
Authors: Cristina Cejudo‐Bastante | Marta Ferreiro‐González | Irene Romera | Lourdes Casas | Casimiro Mantell
Source: Foods (article, 2023-08-07)
Field: Materials Science — Biomaterials

Functional, Physical, and Volatile Characterization of Chitosan/Starch Food Films Functionalized with Mango Leaf Extract Active packaging is one of the currently thriving methods to preserve highly perishable foods. Nonetheless, the integration of active substances into the formulation of the packaging may alter their properties-particularly mass transfer properties-and therefore, the active compounds acting. Different formulations of chitosan (CH), starch (ST), and their blends (CH-ST), with the addition of mango leaf extract (MLE) have been polymerized by casting to evaluate their food preservation efficiency. A CH-ST blend with 3% MLE using 7.5 mL of the filmogenic solution proved to be the most effective formulation because of its high bioactivity (ca. 80% and 74% of inhibition growth of <i>S. aureus</i> and <i>E. coli</i>, respectively, and 40% antioxidant capacity). The formulation reduced the water solubility and water vapor permeability while increasing UV protection, properties that provide a better preservation of raspberry fruit after 13 days than the control. Moreover, a novel method of Headspace-Gas Chromatography-Ion Mobility Spectrometry to analyze the volatile profiles of the films is employed, to study the potential modification of the food in contact with the active film. These migrated compounds were shown to be closely related to both the mango extract additions and the film's formulation themselves, showing different fingerprints depending on the film. Active packaging ; Chitosan ; Chemistry ; Solubility ; Food packaging ; Starch ; Active ingredient ; Antioxidant ; Food science ; Chemical engineering ; Organic chemistry Nanocomposite Films for Food Packaging ; Postharvest Quality and Shelf Life Management
Authors: Kousuke Nakano | Oto Kohulák | Abhishek Raghav | Michele Casula | Sandro Sorella
Source: The Journal of Chemical Physics (article, 2023-12-11)
Field: Materials Science — Materials Chemistry

<scp>TurboGenius</scp>: Python suite for high-throughput calculations of <i>ab initio</i> quantum Monte Carlo methods TurboGenius is an open-source Python package designed to fully control ab initio quantum Monte Carlo (QMC) jobs using a Python script, which allows one to perform high-throughput calculations combined with TurboRVB [Nakano et al. J. Phys. Chem. 152, 204121 (2020)]. This paper provides an overview of the TurboGenius package and showcases several results obtained in a high-throughput mode. For the purpose of performing high-throughput calculations with TurboGenius, we implemented another open-source Python package, TurboWorkflows, that enables one to construct simple workflows using TurboGenius. We demonstrate its effectiveness by performing (1) validations of density functional theory (DFT) and QMC drivers as implemented in the TurboRVB package and (2) benchmarks of Diffusion Monte Carlo (DMC) calculations for several datasets. For (1), we checked inter-package consistencies between TurboRVB and other established quantum chemistry packages. By doing so, we confirmed that DFT energies obtained by PySCF are consistent with those obtained by TurboRVB within the local density approximation (LDA) and that Hartree-Fock (HF) energies obtained by PySCF and Quantum Package are consistent with variational Monte Carlo energies obtained by TurboRVB with the HF wavefunctions. These validation tests constitute a further reliability check of the TurboRVB package. For (2), we benchmarked the atomization energies of the Gaussian-2 set, the binding energies of the S22, A24, and SCAI sets, and the equilibrium lattice parameters of 12 cubic crystals using DMC calculations. We found that, for all compounds analyzed here, the DMC calculations with the LDA nodal surface give satisfactory results, i.e., consistent either with high-level computational or with experimental reference values. Python (programming language) ; Quantum Monte Carlo ; Monte Carlo method ; Ab initio ; Computational science ; Statistical physics ; Density functional theory ; Diffusion Monte Carlo ; Wave function ; Quantum ; Computer science ; Physics ; Monte Carlo molecular modeling ; Quantum mechanics ; Mathematics ; Markov chain Monte Carlo Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Inorganic Fluorides and Related Compounds
Authors: Xiaoxian Zhang | Tingran Liu | Jichen Zhang | Ling Zhu
Source: International Journal of Environmental Research and Public Health (article, 2023-01-03)
Field: Materials Science — Materials Chemistry

Potential Mechanism of Long-Term Immobilization of Pb/Cd by Layered Double Hydroxide Doped Chicken-Manure Biochar Layered double hydroxide (LDH)-doped chicken-manure biochar (CMB) with long-term stability was synthesized to immobilize Pb/Cd. MgAl-Cl-LDH-doped CMB (MHs) showed prominent long-term oxidation resistance and the least biodegradation sensitivity. Efficient Pb/Cd adsorption was observed on MHs, and the maximum adsorption capacities of Pb(II)/Cd(II) reached 1.95 mmol/g and 0.65 mmol/g, respectively. Precipitation and isomorphous substitution were identified as the key adsorption mechanisms, which formed highly stable Pb/Cd species (PbAl-CO<sub>3</sub>-LDH, Pb<sub>3</sub>(OH)<sub>2</sub>CO<sub>3</sub>, CdAl-Cl-LDH and CdCO<sub>3</sub>). Pb(II) and Cd(II) precipitated with CO<sub>3</sub><sup>2-</sup> in MHs; meanwhile, Mg(II) and Ca(II) in LDH layers were substituted by Pb(II) and Cd(II) respectively. Therefore, MHs had the potential for long-term stability of Pb/Cd. Moreover, complexation and electrostatic adsorption also contributed to the Pb/Cd immobilization to a certain extent. When 5% MHs (<i>w</i>/<i>w</i>) was applied to Pb/Cd contaminated smelting site soils, the soil pH increased from 5.9 to 7.3. After applying MHs for 25 d, the content of bioavailable Pb(II) and Cd(II) decreased by 98.8% and 85.2%, respectively, and the content of soluble Pb and Cd dropped by 99.5% and 96.7%. This study paves the way for designing a novel LDH doped CMB as efficient Pb/Cd immobilizers for smelting site soils. Biochar ; Manure ; Chicken manure ; Hydroxide ; Mechanism (biology) ; Chemistry ; Environmental chemistry ; Term (time) ; Doping ; Environmental science ; Agronomy ; Materials science ; Inorganic chemistry ; Biology ; Pyrolysis ; Physics ; Optoelectronics ; Organic chemistry Layered Double Hydroxides Synthesis and Applications ; Covalent Organic Framework Applications ; Advanced Photocatalysis Techniques
Authors: Iversen Luk Jun Lam | Mariah Aqilah Mohd Affandy | Nasir Md Nur ‘Aqilah | Joseph Merillyn Vonnie | Wen Xia Ling Felicia | Kobun Rovina
Source: Polymers (article, 2023-05-16)
Field: Materials Science — Biomaterials

Physicochemical Characterization and Antimicrobial Analysis of Vegetal Chitosan Extracted from Distinct Forest Fungi Species The main goal of this investigation is to conduct a thorough analysis of the physical, chemical, and morphological characteristics of chitosan derived from various forest fungi. Additionally, the study aims to determine the effectiveness of this vegetal chitosan as an antimicrobial agent. In this study, <i>Auricularia auricula-judae</i>, <i>Hericium erinaceus</i>, <i>Pleurotus ostreatus</i>, <i>Tremella fuciformis</i>, and <i>Lentinula edodes</i> were examined. The fungi samples were subjected to a series of rigorous chemical extraction procedures, including demineralization, deproteinization, discoloration, and deacetylation. Subsequently, the chitosan samples were subjected to a comprehensive physicochemical characterization analysis, encompassing Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), degree of deacetylation determination, ash content determination, moisture content determination, and solubility determination. To evaluate the antimicrobial efficacy of the vegetal chitosan samples, two different sampling parameters were employed, namely human hand and banana, to assess their effectiveness in inhibiting microbial growth. Notably, the percentage of chitin and chitosan varied significantly among the distinct fungal species examined. Moreover, EDX spectroscopy confirmed the extraction of chitosan from <i>H. erinaceus</i>, <i>L. edodes</i>, <i>P. ostreatus</i>, and <i>T. fuciformis</i>. The FTIR spectra of all samples revealed a similar absorbance pattern, albeit with varying peak intensities. Furthermore, the XRD patterns for each sample were nearly identical, with the exception of the <i>A. auricula-judae</i> sample, which exhibited sharp peaks at ~37° and ~51°, while the crystallinity index of this same sample was approximately 17% lower than the others. The moisture content results indicated that the <i>L. edodes</i> sample was the least stable, while the <i>P. ostreatus</i> sample was the most stable, in terms of degradation rate. Similarly, the solubility of the samples showed substantial variation among each species, with the <i>H. erinaceus</i> sample displaying the highest solubility among the rest. Lastly, the antimicrobial activity of the chitosan solutions exhibited different efficacies in inhibiting microbial growth of skin microflora and microbes found on the peel of <i>Musa acuminata</i> × <i>balbisiana</i>. Hericium erinaceus ; Chitosan ; Chitin ; Extraction (chemistry) ; Fourier transform infrared spectroscopy ; Crystallinity ; Demineralization ; Chemistry ; Food science ; Nuclear chemistry ; Chromatography ; Materials science ; Raw material Nanocomposite Films for Food Packaging ; Fungal Biology and Applications ; Phytochemicals and Antioxidant Activities
Authors: Aji Setiawan | Kusworo Adi | Catur Edi Widodo
Source: Mathematical Modelling and Engineering Problems (article, 2023-04-28)
Field: Chemistry — Analytical Chemistry

Rice Foreign Object Classification Based on Integrated Color and Textural Feature Using Machine Learning A blend of natural and artificial foreign objects can be used to determine the rice quality.The agricultural industry, particularly rice plants, has demonstrated great success rates for object detection based on image processing.Most food quality studies can be seen from the image shape color and size, and the rice quality can be seen from the absence of the foreign object.HSV color and GLCM texture are used to classify natural and non-natural foreign object images using the support vector machine (SVM) algorithm and other comparison methods, namely decision tree and naive Bayes.The dataset for foreign objects consists of 80 images, 20 of which are each of the following classes: stone, grain, yellow-broken, and red-black.The dataset will be preprocessed to obtain the feature values for color and texture.SVM method with cross-validation, the highest accuracy value is 96.83%, a decision tree is 87.31%, and naive Bayes is 82.54% in detecting natural and non-natural foreign objects.The use of cross-validation techniques with a value of K=5 gives an average accuracy increase of 10% compared to those without cross-validation.These results show that natural foreign objects in different classes can be appropriately detected using a combination of color and texture features in the SVM classification method and cross-validation. Artificial intelligence ; Feature (linguistics) ; Computer science ; Pattern recognition (psychology) ; Object (grammar) ; Computer vision ; Linguistics Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; GABA and Rice Research
Authors: Ankita Punetha | Deepak Kotiya
Source: Proteomes (review, 2023-01-10)
Field: Chemistry — Spectroscopy

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside. Proteomics ; Cancer ; Drug discovery ; Biomarker discovery ; Medicine ; Bioinformatics ; Carcinogenesis ; Drug development ; Computational biology ; Drug ; Biology ; Pharmacology ; Internal medicine Advanced Proteomics Techniques and Applications ; Advanced Biosensing Techniques and Applications ; Cancer Genomics and Diagnostics
Authors: Robin Schiemer | Jan Tobias Weggen | Katrin Schmitt | Jürgen Hubbuch
Source: Biotechnology and Bioengineering (article, 2023-05-16)
Field: Chemistry — Spectroscopy

An adaptive soft‐sensor for advanced real‐time monitoring of an antibody‐drug conjugation reaction In the production of antibody-drug conjugates (ADCs), the conjugation reaction is a central step defining the final product composition and, hence, directly affecting product safety and efficacy. To enable real-time monitoring, spectroscopic sensors in combination with multivariate regression models have gained popularity in recent years. The extended Kalman filter (EKF) can be used as so-called soft-sensor to fuse sensor predictions with long-horizon forecasts by process models. This enables the dynamic update of the current state and provides increased robustness against experimental noise or model errors. Due to the uncertainty associated with sensor and process models in biopharmaceutical applications, the deployment of such soft-sensors is challenging. In this study, we demonstrate the combination of an uncertainty-aware sensor model with a kinetic reaction model using an EKF to monitor a site-directed ADC conjugation reaction. As the sensor model, a Gaussian process regression model is presented to realize a time-variant determination of the sensor uncertainty. The EKF fuses the time-discrete predictions of the amount of conjugated drug from the sensor model with the time-continuous predictions from the kinetic model. While the ADC species are not distinguishable by on-line recorded UV/Vis spectra, the developed soft-sensor is able to dynamically update all relevant reaction species. It could be shown that the use of time-variant process and sensor noise computation approaches improved the performance of the EKF and achieved a reduction of the prediction error of up to 23% compared with the kinetic model. The developed framework proved to enhance robustness against noisy sensor measurements or wrong model initialization and was successfully transferred from batch to fed-batch mode. In future, this framework could be implemented for model-based process control and be adopted for other ADC conjugation reaction types. Soft sensor ; Extended Kalman filter ; Robustness (evolution) ; Computer science ; Kalman filter ; Control theory (sociology) ; Biological system ; Process (computing) ; Artificial intelligence ; Chemistry Analytical Chemistry and Chromatography ; Viral Infectious Diseases and Gene Expression in Insects ; Spectroscopy and Chemometric Analyses
Authors: Feiren Wang | Boming Xie | Enli Lü | Zhixiong Zeng | Shuang Mei | Chengying Ma | Jiaming Guo
Source: Applied Sciences (article, 2023-01-31)
Field: Chemistry — Analytical Chemistry

Design of a Moisture Content Detection System for Yinghong No. 9 Tea Leaves Based on Machine Vision The moisture content of Yinghong No. 9 tea leaves is an important indicator for their processing. The traditional method used to detect the moisture content of tea leaves is not suitable for large-scale production. To improve the efficiency of tea processing, a moisture content detection system for Yinghong No. 9 tea leaves based on machine vision was developed, and the relationship between the moisture content and the fresh tea leaves was researched. Firstly, nine color features and five texture features of the tea leaves images were extracted, and two different tea leaves databases were constructed based on linear discriminant analysis (LDA) and principal component analysis (PCA). Secondly, two models of moisture prediction for fresh tea leaves were built using a backpropagation (BP) neural network, which were then optimized by particle swarm optimization (PSO) and a genetic algorithm (GA), respectively. After, the two preprocessing methods and the two optimization algorithms were cross-combined to optimize the models for moisture content prediction. Finally, the models above were filtered using segmental analysis for the segmental moisture content prediction. It was verified by experiments that the coefficient of determination (R2) of the combined model of PCA-GA-BP and PCA-PSO-BP was 94.1073%, the RMSE was 1.1490%, and the MAE was 0.9982%. The results of this paper can help in the instantaneous detection of the moisture content of fresh tea leaves during processing, improving the production efficiency of Yinghong No. 9 tea. Principal component analysis ; Water content ; Artificial intelligence ; Moisture ; Linear discriminant analysis ; Machine vision ; Backpropagation ; Mathematics ; Artificial neural network ; Computer science ; Chemistry ; Engineering Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Smart Agriculture and AI
Authors: Ana Medina-Moreno | Mazen M. El‐Hammadi | José L. Arias
Source: Journal of Drug Delivery Science and Technology (article, 2023-05-27)
Field: Materials Science — Biomaterials

pH-dependent, extended release and enhanced in vitro efficiency against colon cancer of Tegafur formulated using chitosan-coated poly(ε-caprolactone) nanoparticles Chitosan ; Biocompatibility ; Caprolactone ; Coacervate ; Nanoparticle ; Chemistry ; Drug delivery ; Surface modification ; Drug carrier ; Bioavailability ; Tegafur ; Materials science ; Nuclear chemistry ; Nanotechnology ; Polymer ; Chromatography ; Pharmacology ; Copolymer ; Organic chemistry ; Cancer ; Medicine Nanoparticle-Based Drug Delivery ; Peptidase Inhibition and Analysis ; Drug Transport and Resistance Mechanisms