jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Zhe Xing | Mattia Fanetti | Sandra Gardonio | Elsebeth Schröder | Dmytro Orlov
Source: Applied Surface Science (article, 2024-07-06)
Field: Materials Science — Materials Chemistry

Initial oxidation of low index Mg surfaces investigated by SCLS and DFT Magnesium (Mg) is a metal having a high structural efficiency and a very high chemical reactivity at the same time. Its potential areas of applications include the automotive industry, biomedicine, and energy storage and generation. Further developments in these very diverse application areas require a more detailed investigation of the behavior of Mg surfaces under oxidative conditions. The basic mechanisms of magnesium reactivity are not yet fully understood and therefore need to be further investigated by a combination of theoretical and experimental studies on representative surfaces with different crystallographic orientations. For this, we measured in situ high-resolution Mg 2p core level spectra at critical low-index Mg(0001), Mg(101¯0), and Mg(112¯0) surfaces to obtain surface core level shifts (SCLSs) at the early stages of Mg oxidation. We also used density functional theory (DFT) to obtain theoretical estimates of the SCLSs for respective surfaces and associated possible reconstructions to guide the analysis of the experimental spectra and to rule out un-reconstructed Mg(112¯0). DFT simulations were also used to reveal the energies of O atom adsorption, and the formation of evolving oxide structures in the Mg surfaces. Density functional theory ; Magnesium ; Reactivity (psychology) ; Oxide ; Metal ; Adsorption ; Atom (system on chip) ; Materials science ; Physical chemistry ; Computational chemistry ; Chemistry ; Metallurgy Catalytic Processes in Materials Science ; Semiconductor materials and devices ; Electronic and Structural Properties of Oxides
Authors: Mahmood T. Alkhayyat | Faisal Falah Aiwa | Ali Salah Alhfidh | Mohammed Y. Suliman
Source: International Journal of Electrical and Electronics Research (article, 2024-03-20)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Power Transformer Inrush Current Minimization During Energization using ANFIS based Peak Voltage Tracking Approach Energizing the power transformer at no load causes inrush current flow. The value of this current depends on main three factors, the residual and saturation flux of the transformer core, the rating of the transformer, and the switching instant. Inrush current may decrease the life of the transformer and causes mall function of the protective relays. Many efforts were done for limiting the inrush current using a current limiter or improve the core material to reduce residual flux. Other treating is to control energizing instance. This paper focused on controlling the instant of the transformer energization switch using fuzzy logic inference system. A new technique depends on adaptive seeking the crest of the voltage waveform. By this method there is no need to zero-crossing technique or phase looked loop. At this point, the flux of the core reaches the minimum value. Simulation and laboratory results show the success of this technique in reducing the inrush current. This technique gives the freedom to the operational engineering for energizing the power transformer at any time. Inrush current ; Transformer ; Minification ; Electrical engineering ; Voltage ; Tracking (education) ; Adaptive neuro fuzzy inference system ; Control theory (sociology) ; Computer science ; Engineering ; Artificial intelligence ; Psychology Magnetic Properties and Applications ; Power Quality and Harmonics ; Non-Destructive Testing Techniques
Authors: Jia Yi | Jiang Huilin | Yong Tan
Source: Agronomy (article, 2024-12-28)
Field: Chemistry — Analytical Chemistry

The Detection of Soybean Bacterial Blight Based on Polarization Spectral Imaging Techniques Soybean bacterial blight, caused by Pseudomonas savastanoi pv. glycine, which is one of the common diseases of soybeans, has a strong harm and a great impact on the yield of soybeans. If the disease is not diagnosed in time and no solution comes up, it will lead to the serious loss of yield after the disease becomes serious. Therefore, this paper proposes the detection of the soybean bacterial blight with the polarization spectroscopic imaging method, derived from the detection principle and mathematical model of polarization bidirectional reflection distribution function on the basis of the Stokes vector analysis method. By synthesizing the spectral lines of the four polarization states and the non-polarization states, it was found that the physical parameters of I (135°, 90°) polarization state were the most suitable for identifying soybean bacterial blight disease, and other polarization states could also supplement the characteristic information. The results show that the polarization spectral image can effectively identify the polarization characteristics of healthy soybean leaves and early bacterial blight in the field, and can distinguish the healthy leaves and the diseased leaves by obtaining the relative polarization reflectance of different areas in soybean leaves. Finally, the soybean disease species can be accurately diagnosed. This paper provides an optical method for the detection of crop diseases and insect pests, which makes up for the deficiency of the traditional detection technology and can provide a scientific basis for the safe non-destructive detection of crop diseases and pests. Blight ; Bacterial blight ; Remote sensing ; Environmental science ; Biology ; Agronomy ; Geography ; Gene ; Genetics Spectroscopy and Chemometric Analyses ; Remote Sensing and Land Use ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Te-Rina J King-Hudson | James S. Davies | Senwei Quan | Michael Currie | Zachary D. Tillett | Jack M. Copping | Santosh Panjikar | Rosmarie Friemann | Jane R. Allison | Rachel A. North | Renwick C. J. Dobson
Source: Journal of Biological Chemistry (article, 2024-09-30)
Field: Materials Science — Materials Chemistry

On the function of TRAP substrate-binding proteins: Conformational variation of the sialic acid binding protein SiaP Tripartite ATP-independent periplasmic (TRAP) transporters are analogous to ABC transporters in that they use a substrate-binding protein to scavenge metabolites (e.g., N-acetylneuraminate) and deliver them to the membrane components for import. TRAP substrate-binding proteins are thought to bind the substrate using a two-state (open and closed) induced-fit mechanism. We solved the structure of the TRAP N-acetylneuraminate substrate-binding protein from Aggregatibacter actinomycetemcomitans (AaSiaP) in both the open ligand-free and closed liganded conformations. Surprisingly, we also observed an intermediate conformation, where AaSiaP is mostly closed and is bound to a non-cognate ligand, acetate, which hints at how N-acetylneuraminate binding stabilizes a fully closed state. AaSiaP preferentially binds N-acetylneuraminate (K<sub>D</sub> = 0.4 μM) compared to N-glycolylneuraminate (K<sub>D</sub> = 4.4 μM), which is explained by the closed-N-acetylneuraminate bound structure. Small-angle X-ray scattering data alongside molecular dynamics simulations suggest the AaSiaP adopts a more open state in solution than in a crystal. However, the open unliganded conformation can also sample closed conformations. Molecular dynamics simulations also demonstrate the importance of water molecules for stabilizing the closed conformation. Although our data is consistent with an induced fit model of binding, we suggest that the open unliganded conformation may sample multiple states capable of binding substrate. The mechanism by which the ligand is released for import remains to be determined. Chemistry ; Sialic acid ; Plasma protein binding ; Biochemistry ; Binding site ; Substrate (aquarium) ; Function (biology) ; Binding protein ; Biophysics ; Biology ; Cell biology Enzyme Structure and Function ; Glycosylation and Glycoproteins Research ; Protein Structure and Dynamics
Authors: Hongmin Sun | Xifan Meng | Yingpeng Han | Xiao Li | Xiaoming Li | Yongguang Li
Source: Journal of Spectroscopy (article, 2024-05-10)
Field: Chemistry — Analytical Chemistry

Soybean Saponin Content Detection Based on Spectral and Image Information Combination Soybean saponin is a natural antioxidant and is anti-inflammatory. Hyperspectral analysis technology was applied to detect soybean saponin content rapidly and nondestructively in this paper. Firstly, spectral preprocessing methods were studied, and standard normal variable (SNV) was used to remove noise information. Secondly, a two-step hybrid variable selection approach based on synergy interval partial least squares (SiPLS) and iteratively retains informative variables (IRIV) was proposed to extract characteristic variables. Then, the ensemble learning model was constructed by back propagation neural network (BPNN), deep forest (DF), partial least squares regression (PLSR), and extreme gradient boosting (EXG). Finally, image information was combined into spectral data to improve model accuracy. The prediction coefficient of determination ( <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"><a:msup><a:mrow><a:mi>R</a:mi></a:mrow><a:mrow><a:mn>2</a:mn></a:mrow></a:msup></a:math> ) of the final model reached 0.9216. It can provide rapid, nondestructive, and accurate detection technology of soybean saponin content. A combination of spectral and image information will provide a new idea for application of hyperspectral. Saponin ; Content (measure theory) ; Artificial intelligence ; Computer science ; Information retrieval ; Computer vision ; Pattern recognition (psychology) ; Mathematics ; Medicine Spectroscopy and Chemometric Analyses ; Food Quality and Safety Studies ; Phytoestrogen effects and research
Authors: Károly Lázár | Zoltán Máthé | Tibor Németh | Viktória Kovács Kis | S. Stichleutner | Ivett Kovács
Source: Minerals (article, 2024-02-14)
Field: Chemistry — Inorganic Chemistry

Iron-Bearing Minerals in the Boda Claystone Formation: Correspondences with Stages of Evolution Revealed by Mössbauer Spectroscopy The Boda Claystone Formation (BCF) is an extended sedimentary sequence formed in a shallow-water salt lake under semi-arid to arid climatic conditions during the middle Permian period. The rock was formed predominantly from denuded and altered products of three primary felsic sources, the Mórágy Metagranite Complex, the Baksa Metamorphic Complex and the rhyolitic Gyűrűfű Formation, resulting in the recent dominant sheet silicate components, illite and chlorite. BCF has been considered a potential host rock for high-level nuclear waste, too. Thus, it has been characterized by several powerful methods so far (X-ray diffraction (XRD), transmission electron microscopy (TEM), etc.). 57Fe Mössbauer spectroscopy may provide a unique additional tool to study iron-bearing minerals. Iron is dominantly present in a ferrous form in minerals of the fresh parent rocks (in the biotite group and amphibole), and in a ferric oxide, hematite, in altered Gyűrűfű Formation. During transformations of biotite group minerals and amphibole, the partial release of ferrous iron or its conversion to ferric form takes place with the stabilization of recent illite and chlorite, while the original layered structure is still preserved. Mössbauer spectroscopy revealed the dominant presence of ferrous iron located in cis-M2 octahedral sites both in parent biotite group minerals and in the final illite, as well as chlorite in both stages. The proportion of ferrous iron in biotite group minerals was halved during the stages of evolution by conversion to ferric iron still in sheet silicate illite or by segregation into separate hematite inclusions. The transformation process of biotite group minerals and amphibole of the source rocks is connected only to the iron-bearing smaller fraction of sheet silicates in the BCF clay mineral assemblage. Determination of Fe2+/Fe3+ ratios in sheet silicates was also pertinent in two sections of BCF. Namely, in samples from the Gorica region, Fe3+ was dominant, siting in illite, whereas Fe2+ was also present in significant portions in chlorite in samples from the Western Mecsek Anticline. The interpretation is deduced in correspondence with results of extended XRD, and high-resolution TEM studies. Illite ; Chlorite ; Biotite ; Geology ; Hematite ; Silicate ; Ferrous ; Mineral ; Geochemistry ; Mineralogy ; Silicate minerals ; Clay minerals ; Amphibole ; Chemistry ; Quartz Radioactive element chemistry and processing ; Geochemistry and Elemental Analysis ; Clay minerals and soil interactions
Authors: Jin Cui | Hengyang Yu | Yong Gong | Poorva Sharma | Ashwini Kumar | Guiwei Tu
Source: Advanced Engineering Materials (article, 2024-09-08)
Field: Materials Science — Materials Chemistry

Texture Evolution of α‐Ti and β‐Ti Alloys During Rolling and Recrystallization Managing the metal's texture throughout the entire processing procedure is imperative for controlling the final properties of metal alloys. In the aerospace industry, α‐Ti alloys have been successfully utilized in applications such as aircraft skins, heat shields, and heat exchangers. However, inherent mechanical strength, fatigue sensitivity, and fracture toughness limitations have significantly restricted their wider adoption. On the other hand, β‐Ti alloys have received increasing attention in the biomedical field due to their lower elastic modulus. However, their actual application has been primarily restricted by the inability to match natural bone's Young's modulus sufficiently. Among these application limitations for both α‐Ti and β‐Ti alloys, texture is an essential factor affecting mechanical properties. Elucidating texture evolution on α‐Ti and β‐Ti alloys is crucial for enabling the expansion of their applications. This review summarizes detailed analyses of the intertwined evolution of texture and microstructure in α‐Ti and β‐Ti alloys during cold rolling, hot rolling, and annealing. Furthermore, based on these fundamental materials science insights, the resultant impact of texture and microstructure on achieving targeted mechanical properties is discussed. Finally, potential pathways are proposed to further guide texture and microstructure evolution in α‐Ti and β‐Ti alloys to meet application requirements. Materials science ; Recrystallization (geology) ; Metallurgy ; Dynamic recrystallization ; Titanium alloy ; Microstructure ; Alloy ; Hot working Titanium Alloys Microstructure and Properties ; Advanced materials and composites ; Intermetallics and Advanced Alloy Properties
Authors: Rongqi Hong | Tingting Zheng | Vincenzo Marra | Dongping Yang | Jian K. Liu
Source: Journal of Neural Engineering (review, 2024-04-01)
Field: Materials Science — Materials Chemistry

Multi-scale modelling of the epileptic brain: advantages of computational therapy exploration <i>Objective</i>: Epilepsy is a complex disease spanning across multiple scales, from ion channels in neurons to neuronal circuits across the entire brain. Over the past decades, computational models have been used to describe the pathophysiological activity of the epileptic brain from different aspects. Traditionally, each computational model can aid in optimizing therapeutic interventions, therefore, providing a particular view to design strategies for treating epilepsy. As a result, most studies are concerned with generating specific models of the epileptic brain that can help us understand the certain machinery of the pathological state. Those specific models vary in complexity and biological accuracy, with system-level models often lacking biological details.<i>Approach</i>: Here, we review various types of computational model of epilepsy and discuss their potential for different therapeutic approaches and scenarios, including drug discovery, surgical strategies, brain stimulation, and seizure prediction. We propose that we need to consider an integrated approach with a unified modelling framework across multiple scales to understand the epileptic brain. Our proposal is based on the recent increase in computational power, which has opened up the possibility of unifying those specific epileptic models into simulations with an unprecedented level of detail.<i>Main results</i>: A multi-scale epilepsy model can bridge the gap between biologically detailed models, used to address molecular and cellular questions, and brain-wide models based on abstract models which can account for complex neurological and behavioural observations.<i>Significance</i>: With these efforts, we move toward the next generation of epileptic brain models capable of connecting cellular features, such as ion channel properties, with standard clinical measures such as seizure severity. Computational model ; Computer science ; Epilepsy ; Computational neuroscience ; Neuroscience ; Artificial intelligence ; Psychology Machine Learning in Materials Science ; Epilepsy research and treatment ; Molecular Communication and Nanonetworks
Authors: Kunpeng Tang | Yinong Li | Yingzhi Chen | Weili Cui | Zhiwei Lin | Yifan Zhang | Lei Shi
Source: Nanomaterials (article, 2024-06-02)
Field: Materials Science — Materials Chemistry

Encapsulation and Evolution of Polyynes Inside Single-Walled Carbon Nanotubes Polyyne is an sp-hybridized linear carbon chain (LCC) with alternating single and triple carbon-carbon bonds. Polyyne is very reactive; thus, its structure can be easily damaged through a cross-linking reaction between the molecules. The longer the polyyne is, the more unstable it becomes. Therefore, it is difficult to directly synthesize long polyynes in a solvent. The encapsulation of polyynes inside carbon nanotubes not only stabilizes the molecules to avoid cross-linking reactions, but also allows a restriction reaction to occur solely at the ends of the polyynes, resulting in long LCCs. Here, by controlling the diameter of single-walled carbon nanotubes (SWCNTs), polyynes were filled with high yield below room temperature. Subsequent annealing of the filled samples promoted the reaction between the polyynes, leading to the formation of long LCCs. More importantly, single chiral (6,5) SWCNTs with high purity were used for the successful encapsulation of polyynes for the first time, and LCCs were synthesized by coalescing the polyynes in the (6,5) SWCNTs. This method holds promise for further exploration of the synthesis of property-tailored LCCs through encapsulation inside different chiral SWCNTs. Carbon nanotube ; Materials science ; Encapsulation (networking) ; Molecule ; Nanotechnology ; Annealing (glass) ; Chemical engineering ; Solvent ; Carbon chain ; Chemistry ; Organic chemistry ; Composite material Carbon Nanotubes in Composites ; Synthesis and Properties of Aromatic Compounds ; Fullerene Chemistry and Applications
Authors: Bing Liu | Junqi Wang | Chaoning Li
Source: RSC Advances (article, 2024-01-01)
Field: Chemistry — Analytical Chemistry

Application of PLS–NN model based on mid-infrared spectroscopy in the origin identification of <i>Cornus officinalis</i> Mid-infrared spectroscopy has been increasingly used as a nondestructive analytical technique in Chinese herbal medicine identification in recent years. In this study, a new chemometric model named as PLS-NN model was proposed based on the mid-infrared spectral data of <i>Cornus officinalis</i> samples from 11 origins. It was realized by combining the partial least squares and neural networks for the identification of the origin of Chinese herbal medicines. First, we extracted features from the spectral data in 3448 bands using the partial least squares method, and extracted 122 components that contained more than 95% of the information. Then, we trained the PLS-NN model by neural network using the extracted components as inputs and the corresponding origin classes as outputs. Finally, based on an external test set, we evaluated the generalization ability of the PLS-NN model using metrics such as accuracy, <i>F</i><sub>1</sub>-Score and Kappa coefficient. The results show that the PLS-NN model performs well in all three metrics when compared to models such as Decision trees, Support vector machine, Partial least squares Discriminant analysis, and Naive bayes. The model not only realizes the dimensionality reduction of full-spectrum data and improves the training efficiency of the model, but also has higher accuracy compared with the full-spectrum data model. The PLS-NN model was applied to identify the origin of <i>Cornus officinalis</i> with an accuracy of 91.9%. Identification (biology) ; Test set ; Spectroscopy ; Set (abstract data type) ; Biological system ; Chemistry ; Analytical Chemistry (journal) ; Computer science ; Artificial intelligence ; Chromatography ; Physics ; Botany ; Biology Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Navnath Indore | Mudassir Chaudhry | Digvir S. Jayas | Jitendra Paliwal | Chithra Karunakaran
Source: Foods (article, 2024-01-29)
Field: Chemistry — Analytical Chemistry

Non-Destructive Assessment of Microstructural Changes in Kabuli Chickpeas during Storage The potential of hyperspectral imaging (HSI) and synchrotron phase-contrast micro computed tomography (SR-µCT) was evaluated to determine changes in chickpea quality during storage. Chickpea samples were stored for 16 wk at different combinations of moisture contents (MC of 9%, 11%, 13%, and 15% wet basis) and temperatures (10 °C, 20 °C, and 30 °C). Hyperspectral imaging was utilized to investigate the overall quality deterioration, and SR-µCT was used to study the microstructural changes during storage. Principal component analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) were used as multivariate data analysis approaches for HSI data. Principal component analysis successfully grouped the samples based on relative humidity (RH) and storage temperatures, and the PLS-DA classification also resulted in reliable accuracy (between 80 and 99%) for RH-based and temperature-based classification. The SR-µCT results revealed that microstructural changes in kernels (9% and 15% MC) were dominant at higher temperatures (above 20 °C) as compared to lower temperatures (10 °C) during storage due to accelerated spoilage at higher temperatures (above 20 °C). Chickpeas which had internal irregularities like cracked endosperm and air spaces before storage were spoiled at lower moisture from 8 wk of storage. Principal component analysis ; Relative humidity ; Hyperspectral imaging ; Partial least squares regression ; Materials science ; Endosperm ; Moisture ; Humidity ; Mathematics ; Biology ; Botany ; Remote sensing ; Composite material ; Meteorology ; Statistics Spectroscopy and Chemometric Analyses ; Food composition and properties ; Meat and Animal Product Quality