jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yaping Wu | Xiaolong Wu | Yuanwu Xu | Yongjun Cheng | Xi Li
Source: Sustainability (article, 2023-09-30)
Field: Materials Science — Materials Chemistry

A Novel Adaptive Neural Network-Based Thermoelectric Parameter Prediction Method for Enhancing Solid Oxide Fuel Cell System Efficiency Efficiency prediction plays a crucial role in the ongoing development of electrochemical energy technology. Our industries heavily depend on a reliable energy supply for power and electricity, and solid oxide fuel cell (SOFC) systems stand out as renewable devices with immense potential. SOFCs, as one of the various types of fuel cells, are renowned for their capability of combined heat and power generation. They can achieve an efficiency of up to 90% in operation. Furthermore, due to the fact that water is the byproduct of their electricity generation process, they are extremely environmentally friendly, contributing significantly to humanity’s sustainable development. With the advancement of renewable energy technologies and the increasing emphasis on sustainable development requirements, predicting and optimizing the efficiency of SOFC systems is gaining importance. This study leverages data collected from an SOFC system and applies an improved neural network structure, specifically the dendritic network (DN) architecture, to forecast thermoelectric efficiency. The key advantage of this method lies in the adaptive neural network algorithm based on the dendritic network structure without manually setting hidden nodes. Moreover, the predicted model of thermoelectric efficiency is validated using 682 and 1099 h of operational data from the SOFC system, and the results are compared against a conventional machine learning method. After comparison, it is found that when the novel method with adaptive characteristics proposed was used for SOFC system efficiency prediction, the MAE and RMSE values were both lower than 0.014; the result is significantly better than from other traditional methods. Additionally, this study demonstrated its effectiveness in predicting the thermoelectric efficiency of SOFC systems through secondary experiments. This study offers guidance on enhancing SOFC systems thermoelectric efficiency. Therefore, this study provides a foundation for the future industrialization of fuel cell systems. Renewable energy ; Process engineering ; Solid oxide fuel cell ; Artificial neural network ; Electricity generation ; Efficient energy use ; Computer science ; Electricity ; Automotive engineering ; Engineering ; Power (physics) ; Artificial intelligence ; Electrical engineering Advancements in Solid Oxide Fuel Cells ; Fuel Cells and Related Materials ; Electrocatalysts for Energy Conversion
Authors: Ali Abou Taka | Joseph E. Reynolds | Neil C. Cole-Filipiak | Mohana Shivanna | Christine Yu | Patrick Feng | Mark D. Allendorf | Krupa Ramasesha | Vitalie Stavila | Laura M. McCaslin
Source: Physical Chemistry Chemical Physics (article, 2023-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Comparing the structures and photophysical properties of two charge transfer co-crystals Organic co-crystals have emerged as a promising class of semiconductors for next-generation optoelectronic devices due to their unique photophysical properties. This paper presents a joint experimental-theoretical study comparing the crystal structure, spectroscopy, and electronic structure of two charge transfer co-crystals. Reported herein is a novel co-crystal Npe:TCNQ, formed from 4-(1-naphthylvinyl)pyridine (Npe) and 7,7,8,8-tetracyanoquinodimethane (TCNQ) <i>via</i> molecular self-assembly. This work also presents a revised study of the co-crystal composed of Npe and 1,2,4,5-tetracyanobenzene (TCNB) molecules, Npe:TCNB, herein reported with a higher-symmetry (monoclinic) crystal structure than previously published. Npe:TCNB and Npe:TCNQ dimer clusters are used as theoretical model systems for the co-crystals; the geometries of the dimers are compared to geometries of the extended solids, which are computed with periodic boundary conditions density functional theory. UV-Vis absorption spectra of the dimers are computed with time-dependent density functional theory and compared to experimental UV-Vis diffuse reflectance spectra. Both Npe:TCNB and Npe:TCNQ are found to exhibit neutral character in the S<sub>0</sub> state and ionic character in the S<sub>1</sub> state. The high degree of charge transfer in the S<sub>1</sub> state of both Npe:TCNB and Npe:TCNQ is rationalized by analyzing the changes in orbital localization associated with the S<sub>1</sub> transitions. Density functional theory ; Monoclinic crystal system ; Crystallography ; Crystal (programming language) ; Chemistry ; Dimer ; Absorption spectroscopy ; Molecule ; Crystal structure ; Ionic bonding ; Molecular orbital ; Single crystal ; Materials science ; Chemical physics ; Computational chemistry ; Optics Organic and Molecular Conductors Research ; Luminescence and Fluorescent Materials ; Perovskite Materials and Applications
Authors: Louise Marie Buur | Arthur Declercq | Marina Strobl | Robbin Bouwmeester | Sven Degroeve | Lennart Martens | Viktoria Dorfer | Ralf Gabriels
Source: ChemRxiv (preprint, 2023-11-16)
Field: Chemistry — Spectroscopy

MS²Rescore 3.0 is a modular, flexible, anduser-friendly platform to boost peptideidentifications, as showcased with MS Amanda 3.0 Rescoring of peptide-spectrum matches (PSMs) has emerged as a standard procedure for the analysis of tandem mass spectrometry data. This emphasizes the need for software maintenance and continuous improvement for such algorithms. We here introduce MS²Rescore 3.0, a versatile, modular, and user-friendly platform designed to increase peptide identifications. Researchers can install MS²Rescore across various platforms with minimal effort and benefit from a graphical user interface, a modular Python API, and extensive documentation. To showcase benefits of this new version, we connected MS²Rescore 3.0 with MS Amanda 3.0, a new release of the well-established search engine, addressing previous limitations on automatic rescoring. Among new features, MS Amanda now contains additional output columns that can be used for rescoring. The full potential of rescoring is best revealed when applied on challenging data sets. We therefore evaluated the performance of these two tools on publicly available single-cell data sets, where the number of PSMs was substantially increased, thereby demonstrating that MS²Rescore offers a powerful solution to boost peptide identifications. The modular design and user-friendly interface make MS²Rescore a valuable tool for the proteomics community, offering additional insights into the often nontransparent topic of machine learning, making it more accessible even for inexperienced users. Modular design ; Python (programming language) ; Computer science ; User Friendly ; Documentation ; Graphical user interface ; Interface (matter) ; Software ; User interface ; Human–computer interaction ; Operating system ; Software engineering Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Advanced biosensing and bioanalysis techniques
Authors: Markus Hermann | Christofer S. Tautermann | Peter Sieger | Marc A. Grundl | Alexander Weber
Source: Pharmaceuticals (article, 2023-01-12)
Field: Chemistry — Organic Chemistry

BIreactive: Expanding the Scope of Reactivity Predictions to Propynamides We present the first comprehensive study on the prediction of reactivity for propynamides. Covalent inhibitors like propynamides often show improved potency, selectivity, and unique pharmacologic properties compared to their non-covalent counterparts. In order to achieve this, it is essential to tune the reactivity of the warhead. This study shows how three different in silico methods can predict the in vitro properties of propynamides, a covalent warhead class integrated into approved drugs on the market. Whereas the electrophilicity index is only applicable to individual subclasses of substitutions, adduct formation and transition state energies have a good predictability for the in vitro reactivity with glutathione (GSH). In summary, the reported methods are well suited to estimate the reactivity of propynamides. With this knowledge, the fine tuning of the reactivity is possible which leads to a speed up of the design process of covalent drugs. Reactivity (psychology) ; Covalent bond ; In silico ; Electrophile ; Combinatorial chemistry ; Glutathione ; Chemistry ; Computational biology ; Computer science ; Biochemistry ; Biology ; Organic chemistry ; Medicine ; Enzyme ; Gene Chemical Reaction Mechanisms ; Synthesis and Biological Evaluation ; Computational Drug Discovery Methods
Authors: Qian Ma | Anze Shui | Chao He | Yuqian Zhou | Q. Shan
Source: International Journal of Applied Ceramic Technology (article, 2023-07-18)
Field: Materials Science — Ceramics and Composites

Fabrication and mechanical properties of low‐temperature sintered Al <sub>2</sub> TiO <sub>5</sub> flexible ceramics Abstract To lower the sintering temperature and improve the mechanical properties of aluminum titanate (AT, Al 2 TiO 5 ) flexible ceramics, γ‐Al 2 O 3 is employed to partially replace the α‐Al 2 O 3 as the starting powder. The results show that the addition of γ‐Al 2 O 3 is sufficient to promote the reaction, improve the flexibility, raise the strength, and accelerate the grain growth of AT flexible ceramics when sintered at 1300°C. With that, the combination of optimum fracture strength (∼33.52 MPa) and high flexibility (∼1.05%) is obtained when the addition of γ‐Al 2 O 3 is 20 wt.%. As compared to the virgin, the optimization of 21.67% in fracture strength and 176% in strain can be obtained. It is believed that the increase of crack deflection and branching should take the responsibility. However, the mechanical strength degrades with the increase of sintering temperature, which is caused by the grain defects that reduce the bearing capacity of AT grains and lead to the grain fracture model transition. In addition, the effect of γ‐Al 2 O 3 content on AT grain growth transfers from promotion to inhibition with the increase of sintering temperature. The main reason is that the growth of the nanocrystals at AT grain boundary causes the uneven distribution of the intermediate phase, leading to the roughening transition of the boundary and hence reducing the grain growth rate. On these bases, the grain growth mechanism that dominates by grain boundary is proposed. It is believed that the discovery of this study will provide a new grain growth model and the reference for solving the abnormal grain growth or grain growth stagnation. Materials science ; Grain growth ; Sintering ; Ceramic ; Grain boundary ; Fabrication ; Grain boundary strengthening ; Grain size ; Grain boundary diffusion coefficient ; Composite material ; Microstructure Advanced ceramic materials synthesis ; Aluminum Alloys Composites Properties ; Intermetallics and Advanced Alloy Properties
Authors: Triyana Muliawati | Danni Gathot Harbowo | Andre Markus Fernando Lubis | Juan Daniel Turnip | Erina Rosalia Irda | Adelia Azahra | Yanti Marito
Source: Indonesian Journal of Applied Mathematics (article, 2023-07-30)
Field: Chemistry — Organic Chemistry

k-Means Clustering to Enhance the Petrified Wood Composition Data Analyses and Its Interpretation Geologically, the fossilization of wood materials into fossils requires appropriate conditions, some of which have been preserved for millions of years. In nature, the organic mass of wood must be quickly replaced by inorganic elements before it decomposes under harsh geological conditions. Anorganic oxides such as silica-oxide, are known to be the main components of most wood specimens (up to 80%). The presence of alkaline oxides such as sodium and potassium oxide seems to play a major role in the presence of dissolved silica during petrification. However, their significance in the petrification phenomenon that occurs in fossilized plant wood is not yet known. Therefore, in this study, cluster analysis was conducted to determine the relationship between the presence of silica and alkaline compounds in petrified wood fossils. The approach used was -means clustering supported by the Elbow Method, which aims to review and order a complex set of data into subsets, thus allowing interpretation. The results showed that the clustering of the fossil wood composition data was optimal at = 3. There is a fair correlation between the presence of silica and alkali oxide compounds (-0.504 to -0.387), as well as with another inorganic compounds (+0.957). The presence of sodium and potassium is strongly correlated during silicification (+0.905). Additionally, the results of data clustering made the wood fossilization process susceptible to describe, especially through data regression. The data visualization provides more facts and proper explanations of the role of alkaline oxides in wood silicification. This study furthers our understanding of wood fossilization, especially the diagenesis of wood chemical composition in geological history. Fossilization ; Cluster analysis ; Oxide ; Interpretation (philosophy) ; Geology ; Mineralogy ; Potassium ; Sodium ; Chemistry ; Computer science ; Artificial intelligence ; Organic chemistry Wood and Agarwood Research ; Image Processing and 3D Reconstruction
Authors: Yinggeng Wu | Bing Wu | Yao Ma | Meizhu Wang | Qi Feng | Zhiping He
Source: Applied Sciences (article, 2023-10-29)
Field: Chemistry — Analytical Chemistry

Rapid Discrimination of Organic and Non-Organic Leafy Vegetables (Water Spinach, Amaranth, Lettuce, and Pakchoi) Using VIS-NIR Spectroscopy, Selective Wavelengths, and Linear Discriminant Analysis Organic leafy vegetables face challenges related to potential substitution with non-organic products and vulnerability to dehydration and deterioration. To address these concerns, visible and near-infrared spectroscopy (VIS-NIR) combined with linear discriminant analysis (LDA) was employed in this study to rapidly distinguish between organic and non-organic leafy vegetables. The organic category includes organic water spinach (Ipomoea aquatica Forsskal), amaranth (Amaranthus tricolor L.), lettuce (Lactuca sativa var. ramosa Hort.), and pakchoi (Brassica rapa var. chinensis (Linnaeus) Kitamura), while the non-organic category consists of their four non-organic counterparts. Binary classification was performed on the reflectance spectra of these vegetables’ leaves and stems, respectively. Given the broad range of the VIS-NIR spectrum, stability selection (SS), random forest (RF), and analysis of variance (ANOVA) were used to evaluate the importance of the wavelengths selected by genetic algorithm (GA). According to the GA-selected wavelengths and their SS-evaluated values and locations, the significant bands for leaf spectra classification were identified as 550–910 nm and 1380–1500 nm, while 750–900 nm and 1700–1820 nm were important for stem spectra classification. Using these selected bands in the LDA classification, classification accuracies of over 95% were achieved, showcasing the effectiveness of utilizing the proposed method to rapidly identify organic leafy vegetables and the feasibility and potential of using a cost-effective spectrometer that only contains necessary bands for authenticating. Amaranth ; Leafy vegetables ; Spinach ; Linear discriminant analysis ; Lactuca ; Leafy ; Horticulture ; Mathematics ; Chemistry ; Food science ; Biology ; Statistics Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Advanced Chemical Sensor Technologies
Authors: Nabin Kumar Naik | Prabira Kumar Sethy | A. Geetha Devi | Santi Kumari Behera
Source: Ingénierie des systèmes d information (article, 2023-06-30)
Field: Chemistry — Analytical Chemistry

Hybrid Enhanced Featured AlexNet for Milled Rice Grain Identification Rice is a widely cultivated grain with numerous genetic variants that can be distinguished by their unique texture, shape, and color characteristics.Accurate classification and evaluation of seed quality depend on the ability to identify these traits.In this study, we propose a novel Hybrid Enhanced Featured AlexNet model for identifying eight varieties of milled rice, including arborio, basmati, ipsala, jasmine, jhili, masoori, HMT, and karacadag.Our approach combines the use of a pre-trained AlexNet model with multilayer feature fusion to extract deep features, which are then supplied to a Support Vector Machine (SVM) for classification.Our proposed model achieves an impressive accuracy of 99.63%, sensitivity of 99.63%, specificity of 99.95%, precision of 99.64%, and an F1 score of 99.63%.Our methodology has significant potential for application in the food processing sector to determine the price of various milled rice varieties. Identification (biology) ; Computer science ; Materials science ; Botany ; Biology Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Advanced Chemical Sensor Technologies
Authors: Song Zhang | Miao Yu | Guoqiang Zhang | Guanmei He | Yunxu Ji | Juan Dong | Huayan Zheng | Qian Lu
Source: Molecules (article, 2023-09-22)
Field: Materials Science — Surfaces, Coatings and Films

Revealing the Control Mechanisms of pH on the Solution Properties of Chitin via Single-Molecule Studies Chitin is one of the most common polysaccharides and is abundant in the cell walls of fungi and the shells of insects and aquatic organisms as a skeleton. The mechanism of how chitin responds to pH is essential to the precise control of brewing and the design of smart chitin materials. However, this molecular mechanism remains a mystery. Results from single-molecule studies, including single-molecule force spectroscopy (SMFS), AFM imaging, and molecular dynamic (MD) simulations, have shown that the mechanical and conformational behaviors of chitin molecules show surprising pH responsiveness. This can be compared with how, in natural aqueous solutions, chitin tends to form a more relaxed spreading conformation and show considerable elasticity under low stretching forces in acidic conditions. However, its molecular chain collapses into a rigid globule in alkaline solutions. The results show that the chain state of chitin can be regulated by the proportions of inter- and intramolecular H-bonds, which are determined via the number of water bridges on the chain under different pH values. This basic study may be helpful for understanding the cellular activities of fungi under pH stress and the design of chitin-based drug carriers. Chitin ; Molecule ; Chemistry ; Polysaccharide ; Force spectroscopy ; Intramolecular force ; Aqueous solution ; Cell wall ; Biophysics ; Nanotechnology ; Chemical engineering ; Stereochemistry ; Materials science ; Organic chemistry ; Chitosan ; Biochemistry ; Biology Polymer Surface Interaction Studies ; Force Microscopy Techniques and Applications ; Silk-based biomaterials and applications
Authors: Fausto Díaz-Sánchez | Miguel A. García‐Castro | Patricia Amador | Diego Espinosa-Morales | Jenaro Leocadio Varela‐Caselis
Source: ACS Omega (article, 2023-12-14)
Field: Chemistry — Organic Chemistry

7-Methoxy-4-methylcoumarin: Standard Molar Enthalpy of Formation Prediction in the Gas Phase Using Machine Learning and Its Comparison to the Experimental Data Experimentally, the standard molar enthalpy of formation in the crystalline phase at 298.15 K, Δ<sub>f</sub><i>H</i><sub>m</sub>°(cr) for 7-methoxy-4-methylcoumarin (7M4MC) was calculated by traditional linear regression, which was obtained by combustion calorimetry. Similarly, the standard molar enthalpy of sublimation was determined through the standard molar enthalpy of fusion and by the standard molar enthalpy of vaporization, from differential scanning calorimetry and thermogravimetry, respectively; lately using these results, the standard molar enthalpy of formation in the gas phase was calculated at 298.15 K, Δ<sub>f</sub><i>H</i><sub>m</sub>°(g). In addition ML was used to predict the standard molar enthalpy of formation in the gas phase for the 7M4MC, constructing an experimental data set containing three kinds of functional groups: esters, coumarins, and aromatic compounds. The procedure was performed by using multiple linear regression algorithms and stochastic gradient descent with a <i>R</i><sup>2</sup> of 0.99. The obtained models were used to compare those predicted values versus experimental for coumarins, resulting in an average error rate of 9.0%. Likewise, four homodesmic reactions were proposed and predicted with the multiple linear regression algorithm of ML obtaining good results. Enthalpy ; Chemistry ; Standard enthalpy of formation ; Enthalpy of vaporization ; Enthalpy of atomization ; Enthalpy of fusion ; Standard enthalpy of reaction ; Linear regression ; Thermodynamics ; Sublimation (psychology) ; Calorimetry ; Differential scanning calorimetry ; Combustion ; Physical chemistry ; Mathematics ; Statistics Chemical Thermodynamics and Molecular Structure ; Analytical Chemistry and Chromatography ; Computational Drug Discovery Methods
Authors: Wiska Mailisa | Windy Dwi Annisa | Fitri Aulia Permatasari | Riezki Amalia | Atthar Luqman Ivansyah | Ferry Iskandar | Heni Rachmawati
Source: ACS Omega (article, 2023-03-06)
Field: Materials Science — Materials Chemistry

In Vitro and Silico Studies on the N-Doped Carbon Dots Potential in ACE2 Expression Modulation The alteration of ACE2 expression level, which has been studied in many diseases, makes the topic of ACE2 inducer potential crucial to be explored. The ACE2 inducer could further be designed to control the ACE2 expression level, which is appropriate to a specific case. An in vitro study of well-characterized carbon dots (CDs), made from citric acid and urea, was performed to determine their ability to modulate the ACE2 receptor. Gene expression of ACE2 was quantified using concentrations adjusted for IC50 results from CDs viability assays in HEK 293 and A549 cell lines. RT-qPCR was used to assess the expression of the ACE2 gene and its induction effect in normal cell lines (HEK-293A). According to the results of the tests, ACE2 is expressed in HEK-293A cell lines, and diminazene aceturate can increase ACE2 expression. The effect of CDs on ACE2 gene expression was further examined on the cell lines that had previously been induced with diminazene aceturate, which resulted in upregulation of the ACE2 expression level. An in silico study has been done by using a molecular docking approach. The molecular docking results show that CDs can make strong interactions with ACE2 amino acid residues through hydrophobic interaction, π-π interaction, π-cation interaction, and ionic interaction. In silico ; In vitro ; Modulation (music) ; Cell biology ; Chemistry ; Computational biology ; Biology ; Physics ; Biochemistry ; Gene Carbon and Quantum Dots Applications ; Electrochemical sensors and biosensors ; Nanocluster Synthesis and Applications
Authors: Euan M. Duncan | Amandine Ridouard | Franck Fayon | Emmanuel Véron | Cécile Genevois | Mathieu Allix | Christopher M. Collins | Michael J. Pitcher
Source: Chemical Communications (article, 2023-01-01)
Field: Materials Science — Ceramics and Composites

A computationally-guided non-equilibrium synthesis approach to materials discovery in the SrO–Al<sub>2</sub>O<sub>3</sub>–SiO<sub>2</sub> phase field Glass-crystallisation synthesis is coupled to probe structure prediction for the guided discovery of new metastable oxides in the SrO-Al<sub>2</sub>O<sub>3</sub>-SiO<sub>2</sub> phase field, yielding a new ternary ribbon-silicate, Sr<sub>2</sub>Si<sub>3</sub>O<sub>8</sub>. In principle, this methodology can be applied to a wide range of oxide chemistries by selecting an appropriate non-equilibrium synthesis route. Silicate ; Crystallization ; Ribbon ; Materials science ; Phase (matter) ; Field (mathematics) ; Silicate glass ; Chemical physics ; Mineralogy ; Chemistry ; Thermodynamics ; Physics ; Mathematics ; Organic chemistry ; Composite material Glass properties and applications ; Crystal Structures and Properties ; Nuclear materials and radiation effects