jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Shuo Liu | Lingzhi Ba | Chengning Li | Xinjie Di
Source: Materials (article, 2022-11-02)
Field: Materials Science — Metals and Alloys

Comparison of Fracture Toughness in the Coarse-Grain Heat-Affected Zone of X80 Pipelines Girth-Welded under Conventional and Ultra-Low Heat Input The coarse-grain heat-affected zones (CGHAZs) of X80 girth-welded steel pipelines are prone to embrittlement, which has an extremely adverse effect on their structural integrity. In the present work, the fracture behavior of the CGHAZs of X80 girth welds under the conditions of conventional and ultra-low heat input was studied. The fracture toughness of CGHAZs was evaluated using the crack tip opening displacement (CTOD) test at −10 °C, and the fracture behavior mechanism of CGHAZs were clarified by analyzing microstructural characteristics at prefabricated fatigue cracks containing fracture cloud image, scanning electron microscopy (SEM), and electron back-scatter diffraction (EBSD) figures. The results illustrate that the average fracture toughness (CTOD) value of the ultra-low heat input CGHAZ is 0.6 mm, and the dispersion of CTOD values is small, while the CTOD value of conventional heat input is only 0.04 mm. The ultra-low heat input makes the high-temperature residence time of the coarse-grained region short, reduces the proportion of prior austenite grain boundaries, and inhibits the formation of strip-like bainite and island-like M-A components. The reduction of these deleterious ductile microstructures increases the plastic reserve and deformation capacity of the CGHAZ. Materials science ; Fracture toughness ; Electron backscatter diffraction ; Bainite ; Crack tip opening displacement ; Welding ; Composite material ; Fracture (geology) ; Metallurgy ; Embrittlement ; Toughness ; Heat-affected zone ; Fracture mechanics ; Austenite ; Microstructure ; Crack closure Hydrogen embrittlement and corrosion behaviors in metals ; Microstructure and Mechanical Properties of Steels ; Fatigue and fracture mechanics
Authors: Zhenhua Li | Shuiquan Deng | Myung‐Hwan Whangbo | Hong‐Gang Luo
Source: AIP Advances (article, 2022-05-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Orbital projection technique to explore the materials genomes of optical susceptibilities The development in materials science and pharmaceutics shows that there exist some key materials genomes, i.e., certain groups of atoms with specific constituents and structures, which govern the property of a series of materials based on them. To pinpoint such materials, genomes are helpful to assemble functional units and synthesize new materials and, thus, have a profound meaning. In this work, we develop an innovative method based on the idea of projecting atomic orbitals’ wavefunction, which enables us to project every physical quantity into their orbital contribution and, thus, can be widely used to identify the materials genomes of various properties. Within this framework, we derive the expressions of the projected optical susceptibilities and exhibit a paradigm of studying the corresponding materials genomes of optical properties, especially the desired nonlinear optical materials. Nonlinear optical ; Atomic orbital ; Genome ; Wave function ; Materials science ; Nanotechnology ; Physics ; Computer science ; Nonlinear system ; Chemistry ; Quantum mechanics Nonlinear Optical Materials Research ; X-ray Diffraction in Crystallography ; Chalcogenide Semiconductor Thin Films
Authors: Ibrahim Khalil Almadani | Ibrahim Sufian Osman | Nasir Ghazi Hariri
Source: Energies (article, 2022-05-22)
Field: Materials Science — Materials Chemistry

In-Depth Assessment and Optimized Actuation Method of a Novel Solar-Driven Thermomechanical Actuator via Shape Memory Alloy Currently, energy demand is more significant than ever due to population growth and advances in recent technologies. In order to supply more energy while maintaining a healthy environment, renewable energy resources are employed. This paper proposes a novel solar-driven shape memory alloy thermomechanical actuator as an eco-friendly solution for solar thermal applications. The proposed actuator was assessed numerically and experimentally. The numerical tests showed that the designed actuation mechanism’s inner temperature has a minimum variation per day of about 14 °C and a temperature variation of 19 °C for most days of the year, which allows for proper activation and deactivation of the actuator. As for the experimental tests, the presented actuation mechanism achieved a bi-directional force of over 150 N, where the inner temperatures of the actuator were recorded at about 70.5 °C while pushing forces and 28.9 °C while pulling forces. Additionally, a displacement of about 127 mm was achieved as the internal temperature of the actuator reached 70.4 °C. The work presented adds to the body of knowledge of a novel solar-based self-driven actuation mechanism that facilitates various applications for solar thermal systems. Actuator ; Shape-memory alloy ; Mechanism (biology) ; Materials science ; Renewable energy ; Mechanical engineering ; Thermal ; Photovoltaic system ; Work (physics) ; Displacement (psychology) ; Electric potential energy ; Computer science ; Energy (signal processing) ; Composite material ; Electrical engineering ; Engineering ; Physics ; Artificial intelligence Shape Memory Alloy Transformations ; Solar Energy Systems and Technologies ; Building Energy and Comfort Optimization
Authors: Jack Penny | Gunnar N. Schroeder | José A. Bengoechea | Ben C. Collins
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2022-07-22)
Field: Chemistry — Spectroscopy

A gas phase fractionation acquisition scheme integrating ion mobility for rapid diaPASEF library generation Abstract Data independent acquisition (DIA or DIA/SWATH) mass spectrometry has emerged as a primary measurement strategy in the field of quantitative proteomics. diaPASEF is a recent adaptation that leverages trapped ion mobility spectrometry (TIMS) to improve selectivity and increase sensitivity. The complex fragmentation spectra generated by co-isolation of peptides in DIA mode are most typically analyzed with reference to prior knowledge in the form of spectral libraries. The best-established method for generating libraries uses data dependent acquisition (DDA) mode, or DIA mode if appropriately deconvoluted, often including offline fractionation to increase depth of coverage. More recently strategies for spectral library generation based on gas phase fractionation (GPF), where a representative sample is injected serially using narrow DIA windows that cover different mass ranges of the complete precursor space, have been introduced that performed comparably to deep offline fractionation-based libraries for DIA data analysis. Here, we investigated whether an analogous GPF-based library building approach that accounts for the ion mobility (IM) dimension is useful for the analysis of diaPASEF data and can remove the need for offline fractionation. To enable a rapid library development approach for diaPASEF we designed a GPF acquisition scheme covering the majority of multiply charged precursors in the m/z vs 1/K0 space requiring 7 injections of a representative sample and compared this with libraries generated by direct deconvolution-based analysis of diaPASEF data or by deep offline fractionation and ddaPASEF. We found that library generation by IM-GPF outperformed direct deconvolution of the diaPASEF data and had performance approaching that of a deep offline fractionation library, when analysing diaPASEF data. This establishes the ion mobility integrated GPF scheme as a pragmatic approach to rapid library generation for the analysis of diaPASEF data. Fractionation ; Ion-mobility spectrometry ; Data acquisition ; Deconvolution ; Computer science ; Mass spectrometry ; Chemistry ; Analytical Chemistry (journal) ; Algorithm ; Chromatography Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Pernille Uma Havmand | Lau Gustav Zachariassen | Richard Ipsen | Vera Kuzina Poulsen
Source: Journal of Dairy Research (article, 2022-04-07)
Field: Chemistry — Analytical Chemistry

Measurement of water-holding capacity in fermented milk using near-infrared spectroscopy combined with chemometric methods We investigated the use of near-infrared spectroscopy (NIR) for measuring water-holding capacity (WHC) in fermented milk. Increased WHC ensures improved texture and decreased syneresis in fermented dairy products and also improves cheese yield. NIR combined with partial least-squares-discriminant analysis (PLS-DA) was found to be a promising rapid and non-invasive method with no pretreatment of the samples for prediction of WHC in fermented milk samples. Analysis of the chemical bonds in the region 10 700-4500 cm-1 (935-2200 nm) of the electromagnetic spectrum was able to distinguish between samples with high vs. low WHC. This technique was successfully used to screen different strains of lactic acid bacteria for their ability to provide fermented milk with increased WHC, which is of great importance for use in various dairy products. Syneresis ; Fermentation ; Lactic acid ; Water holding capacity ; Fermented milk products ; Fermentation in food processing ; Dairy industry Spectroscopy and Chemometric Analyses ; Milk Quality and Mastitis in Dairy Cows ; Probiotics and Fermented Foods
Authors: Matthew Eady
Source: Journal of Spectral Imaging (review, 2022-10-14)
Field: Chemistry — Analytical Chemistry

Potential for spectral imaging applications on the small farm: a review Advancements in optics and miniaturisation have resulted in multi- and hyperspectral imaging systems becoming more approachable in terms of cost, practicality and useability. Globally, the majority of farms are considered to be small farms (&lt;2 hectares). Many spectral imaging applications have been associated with agricultural commodities over the years. However, due to the cost, technology hurdles and complex statistical modelling methods, these applications have mainly been implemented in larger monoculture settings where the method development time required can be met with and substantiated through higher profits gained and reduced labour in the long term. Recent years have seen advancements in spectral imaging technologies as well as open-source systems that have the potential for application on smaller, more diversified farms. There are many hurdles to face before spectral imaging technologies see widespread application on smaller farms, but technologies are advancing rapidly. Here, the current state of spectral imaging in small farm applications is evaluated, along with the potential for low-cost and open-source spectral imaging systems. Emphasis is placed on challenges which require addressing prior to approachable spectral imaging for the small farm. Hyperspectral imaging ; Spectral imaging ; Computer science ; Imaging technology ; Emerging technologies ; Remote sensing ; Artificial intelligence ; Geography Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Chi Young Moon | Gina M. Magnotti | Brandon Sforzo | Aniket Tekawade | Alan Kastengren | Christopher F. Powell
Source: Frontiers in Mechanical Engineering (article, 2022-05-27)
Field: Materials Science — Materials Chemistry

Experimental Investigation of Cavitation-Induced Erosion Using X-Ray Imaging and Tomography High injection pressure in diesel engines can lead to cavitation-induced erosion in injector nozzles. One important factor affecting the severity of erosion is the fuel and its properties. Traditionally, modeling and simulation studies have used single-component representations of fuels, but realistic fuels feature a multitude of components and can even include volatile additives such as water and alcohol. To provide realistic benchmarks and comparisons, experimental measurements quantifying erosion characteristics were made using ultra-low sulfur diesel (ULSD) and two alternative diesel fuels (ADF). X-ray imaging and computed tomography were used to investigate cavitation-induced erosion onset and progression. Hard X-ray tomography revealed injector internal geometry, including details such as surface marks from the manufacturing process and erosion patterns from repeated injections. Erosion progression was measured using X-ray tomography and imaging performed between injections. The critical erosion site was found to be similar across different fuel blends, while the erosion rate and incubation time were sensitive to the fuel blend. The injector geometry and the erosion characteristics were also prepared for numerical model development and validation. Erosion ; Injector ; Diesel fuel ; Cavitation ; Nozzle ; Materials science ; Tomography ; Cavitation erosion ; Fuel injection ; Environmental science ; Petroleum engineering ; Mechanical engineering ; Mechanics ; Waste management ; Engineering ; Optics ; Geology ; Physics Nuclear Materials and Properties ; Nuclear reactor physics and engineering ; Heat transfer and supercritical fluids
Authors: Silvia Giordano | Angela Marika Siciliano | Matteo Donadon | Cristiana Soldani | Barbara Franceschini | Ana Lleò | Luca Di Tommaso | Matteo Cimino | Guido Torzilli | Hidekazu Saiki | Hiroki Nakajima | Sén Takeda | Enrico Davoli
Source: Applied Sciences (article, 2022-04-22)
Field: Chemistry — Spectroscopy

Versatile Mass Spectrometry-Based Intraoperative Diagnosis of Liver Tumor in a Multiethnic Cohort Currently used techniques for intraoperative assessment of tumor resection margins are time-consuming and laborious and, more importantly, lack specificity. Moreover, pathological diagnosis during surgery does not often give a clear outcome. Recent advances in mass spectrometry (MS) and instrumentation have made it possible to obtain detailed molecular information from tissue specimens in real-time, with minimal sample pre-treatment. Probe Electro Spray Ionization MS (PESI-MS), combined with artificial intelligence (AI), has demonstrated its effectiveness in distinguishing liver cancer tissues from healthy tissues in a large Italian population group. As the MS profile can reflect the patient’s ethnicity, dietary habits, or particular operating room procedures, the AI algorithm must be well trained to distinguish different groups. We used a large dataset composed of liver tumor and healthy specimens, from the Italian and Japanese populations, to develop a versatile algorithm free from ethnic bias. The system can classify tissues with discrepancies &lt;5% from the pathologist’s diagnosis. These results demonstrate the potential of the PESI-MS system to distinguish tumor from surrounding non-tumor tissues in patients, with minimal bias from race/ethnicity or etiological characteristics or operating room procedures. Medicine ; Pathological ; Cohort ; Oncology ; Pathology ; Internal medicine Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Laser-induced spectroscopy and plasma
Authors: Gashaw Ashagre Walle | Desalegn Atalie | Ermiyas Tarekegn | Addisu Wudneh | Addisu Desalegn
Source: Mehran University Research Journal of Engineering and Technology (article, 2022-01-01)
Field: Materials Science — Polymers and Plastics

Prediction of Mechanical, Evenness and Imperfection Properties of 100% Cotton Ring Spun Yarns with Different Twist Levels The purpose of this research work is to develop a model to predict the effect of twist on mechanical, evenness and imperfection properties of 100% cotton ring spun yarns. Eight yarns were manufactured from 30Tex with four yarn twist increments (700, 740, 780 and 820TPM), and 15Tex with twist levels of 900, 1020, 1080 and 1140TPM (turns/meter). Except yarn count and twist level, the yarns were made from the same fiber properties and machine settings. Yarn mechanical properties such as tensile strength, elongation and abrasion resistance, evenness (CVm) and imperfection characteristics like hairiness, neps, thin and thick places were measured and statistically analyzed. Equations were developed to predict the desired mechanical, evenness, and imperfection properties of yarns based on yarn count and twist levels. Statistical analysis showed that yarn properties are significantly influenced by count and twist level changes. The tensile strength, elongation, abrasion resistance, CVm, hairiness and thick places of the studied yarns were significant at P-values of 0.000, 0.003, 0.000, 0.004, 0.000 and 0.015 respectively. Generally, as yarn twist increases, breaking strength and abrasion resistance increase, whereas elongation, hairiness, coefficient of mass variation (CVm), thin and thick places, and nep of yarn decrease. Therefore, the formulated multiple regression equations would be useful in predicting yarn properties based on its count and twist. Yarn ; Twist ; Ultimate tensile strength ; Composite material ; Elongation ; Materials science ; Abrasion (mechanical) ; Mathematics ; Species evenness ; Geometry Textile materials and evaluations ; Mechanical Engineering and Vibrations Research ; Structural Analysis and Optimization
Authors: Megan Duffy | Cheyenne M. Adams | Khadijah Homolka | Jacquelyn Neibauer | Lawrence M. Mayer | Richard G. Keil
Source: Frontiers in Marine Science (article, 2022-01-21)
Field: Chemistry — Spectroscopy

Degradation of Diatom Protein in Seawater: A Peptide-Level View Peptides and proteins were identified during a controlled laboratory degradation of the marine diatom Thalassiosira weissflogii by a surface seawater microbiome. Samples from each time point were processed both with and without the protease trypsin, allowing a partial differentiation between peptides produced naturally by microbial enzymatic degradation and peptides produced from the laboratory digestion of intact protein. Over the 12-day degradation experiment, 31% of the particulate organic carbon was depleted, and there was no preferential degradation of the overall protein pool. However, there was distinct differentiation in the cellular location, secondary structure and modifications between peptides produced by microbial vs. laboratory breakdown. During the initial period of rapid algal decay and bacterial growth, intracellular components from the cytoplasm were consumed first, resulting in the accumulation of membrane-associated proteins and peptides in the detrital pool. Accompanying the enrichment of membrane protein material was an increase in the importance of ɑ-helix motifs. Methylated arginine, a post-translational modification common in cell senescence, was found in high amounts within the microbially produced detrital peptide pool, suggesting a link between in-cell modification and resistance to immediate degradation. Another modification—asparagine deamidation—accumulated within the detrital peptides. Protein taxonomies showed the bacterial community decomposing the algal material was rich in Proteobacteria, and protein annotations showed abundant transportation of solubilized carbohydrates and small peptides across membranes. At this early stage of diagenesis, no changes in bulk amino acids (THAA) were observed, yet a proteomic approach allowed us to observe selective changes in diatom protein preservation by using amino acid sequences to infer subcellular location, secondary structures, and post-translational modifications (PTMs). Protein degradation ; Diatom ; Biochemistry ; Proteolysis ; Chemistry ; Amino acid ; Peptide ; Deamidation ; Trypsin ; Protease ; Biology ; Enzyme ; Botany Advanced Proteomics Techniques and Applications ; Microbial Community Ecology and Physiology ; Mass Spectrometry Techniques and Applications
Authors: Yangwen Luo | Luchen Shan | Lipeng Xu | Srinivas Patnala | Isadore Kanfer | Jiahao Li | Pei Yu | Jun Xu
Source: PLoS ONE (article, 2022-08-25)
Field: Chemistry — Organic Chemistry

A network pharmacology-based approach to explore the therapeutic potential of Sceletium tortuosum in the treatment of neurodegenerative disorders Sceletium tortuosum (SCT) has been utilized medicinally by indigenous Koi-San people purportedly for mood elevation. SCT extracts are reported to be neuroprotective and have efficacy in improving cognition. However, it is still unclear which of the pharmacological mechanisms of SCT contribute to the therapeutic potential for neurodegenerative disorders. Hence, this study investigated two aspects-firstly, the abilities of neuroprotective sub-fractions from SCT on scavenging radicals, inhibiting some usual targets relevant to Alzheimer's disease (AD) or Parkinson's disease (PD), and secondly utilizing the network pharmacology related methods to search probable mechanisms using Surflex-Dock program to show the key targets and corresponding SCT constituents. The results indicated sub-fractions from SCT could scavenge 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical, inhibit acetylcholinesterase (AChE), monoamine oxidase type B (MAO-B) and N-methyl-D-aspartic acid receptor (NMDAR). Furthermore, the results of gene ontology and docking analyses indicated the key targets involved in the probable treatment of AD or PD might be AChE, MAO-B, NMDAR subunit2B (GluN2B-NMDAR), adenosine A2A receptor and cannabinoid receptor 2, and the corresponding constituents in Sceletium tortuosum might be N-trans-feruloyl-3-methyldopamine, dihydrojoubertiamine and other mesembrine type alkaloids. In summary, this study has provided new evidence for the therapeutic potential of SCT in the treatment of AD or PD, as well as the key targets and notable constituents in SCT. Therefore, we propose SCT could be a natural chemical resource for lead compounds in the treatment of neurodegenerative disorders. Neuroprotection ; Acetylcholinesterase ; Pharmacology ; Medicine ; Chemistry ; Biochemistry ; Enzyme Chemical synthesis and alkaloids ; Cholinesterase and Neurodegenerative Diseases ; Alkaloids: synthesis and pharmacology
Authors: Shuofeng Li | Bing Li | Jin Li | Bin Liu | Xin Li
Source: Agriculture (article, 2022-08-16)
Field: Chemistry — Analytical Chemistry

Semantic Segmentation Algorithm of Rice Small Target Based on Deep Learning At present, rice is generally in a state of dense adhesion and small granular volume during processing, resulting in no effective semantic segmentation method for rice to extract complete rice. Aiming at the above problems, this paper designs a small object semantic segmentation network model based on multi-view feature fusion. The overall structure of the network is divided into a multi-view feature extraction module, a super-resolution feature building module and a semantic segmentation module. The extraction ability of small target features is improved by super-resolution construction of small target detail features, and the learning ability of the network for small target features is enhanced and expanded through multi-view. At the same time, a dataset of quality inspection during rice processing was constructed. We train and test the model on this dataset. The results show that the average segmentation accuracy of the semantic segmentation model in this paper reaches 87.89%. Compared with the semantic segmentation models such as SegNet, CBAM, RefineNet, DeepLabv3+ and G-FRNet, it has obvious advantages in various indicators, which can provide rice quality detection and an efficient method of rice grain extraction. Segmentation ; Computer science ; Artificial intelligence ; Pattern recognition (psychology) ; Feature (linguistics) ; Scale-space segmentation ; Feature extraction ; Segmentation-based object categorization ; Image segmentation ; Semantic feature Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Smart Agriculture and AI