jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Hannah M. Hynds | Kelly M. Hines
Source: Analytical Chemistry (article, 2024-01-09)
Field: Chemistry — Spectroscopy

MOCCal: A Multiomic CCS Calibrator for Traveling Wave Ion Mobility Mass Spectrometry Ion mobility mass spectrometry (IM-MS) is a rapid, gas-phase separation technology that can resolve ions on the basis of their <i>size-to-charge</i> and <i>mass-to-charge</i> ratios. Since each class of biomolecule has a unique relationship between size and mass, IM-MS spectra of complex biological samples are organized into trendlines that each contain one type of biomolecule (i.e., lipid, peptide, metabolite). These trendlines can aid in the identification of unknown ions by providing a general classification, while more specific identifications require the conversion of IM arrival times to collision cross section (CCS) values to minimize instrument-to-instrument variability. However, the process of converting IM arrival times to CCS values varies between the different IM devices. Arrival times from traveling wave ion mobility (TWIM) devices must undergo a calibration process to obtain CCS values, which can impart biases if the calibrants are not structurally similar to the analytes. For multiomic mixtures, several different types of calibrants must be used to obtain the most accurate CCS values from TWIM platforms. Here we describe the development of a multiomic CCS calibration tool, MOCCal, to automate the assignment of unknown features to the power law calibration that provides the most accurate CCS value. MOCCal calibrates every experimental arrival time with up to three class-specific calibration curves and uses the difference (in Å<sup>2</sup>) between the calibrated <sup>TW</sup>CCS<sub>N2</sub> value and <sup>DT</sup>CCS<sub>N2</sub> vs <i>m</i>/<i>z</i> regression lines to determine the best calibration curve. Using real and simulated multiomic samples, we demonstrate that MOCCal provides accurately calibrated <sup>TW</sup>CCS<sub>N2</sub> values for small molecules, lipids, and peptides. Ion-mobility spectrometry ; Calibration ; Analyte ; Chemistry ; Calibration curve ; Mass spectrometry ; Ion ; Analytical Chemistry (journal) ; Biological system ; Chromatography ; Statistics ; Mathematics Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Chromatography ; Metabolomics and Mass Spectrometry Studies
Authors: Susan Ortner | Paul Styman | Elliot J. Long
Source: Frontiers in Nuclear Engineering (article, 2024-02-07)
Field: Materials Science — Materials Chemistry

The effects of flux on the radiation-induced embrittlement of reactor pressure vessel steels: review of current understanding and application to high fluences It is necessary to quantify the effects of flux on reactor pressure vessel steel embrittlement under neutron irradiation, if surveillance or high-flux test reactor data is used to predict vessel embrittlement occurring at lower fluxes. This is particularly important when considering embrittlement occurring during extended (60–80 years) operation for which there is no direct experience. Dedicated investigations are time-consuming and expensive even when only small flux-fluence ranges are investigated, so collating data from multiple campaigns is necessary to provide sufficient information to cover the wide range of fluxes required for vessel assessment in the long term. This paper collates and reviews such data. The review finds that flux dependences probably differ in sign and strength in different regimes (low flux and fluence, intermediate flux at low and high fluence, high flux at low and high fluence) with the regime limits affected by composition and temperature. The current understanding of diffusion processes and microstructural development are invaluable in interpreting the trends and limits. Many contradictory data sets were found, however, and not all contradictions could be dismissed as resulting from poor quality data. Suggestions are made for investigations to clarify the uncertainties. One wide-ranging model of flux effects, based on an extensive data set, is used to compare high-fluence data from different sources, to assess whether embrittlement rates accelerate after a high, threshold fluence. The model helps to identify experiments which investigated comparable flux-fluence-temperature regimes. The comparable data are split evenly between data sets supporting acceleration after a particular fluence and data sets contradicting it. The model identifies regimes in which further campaigns would clarify the causes of these contrasting observations. Embrittlement ; Reactor pressure vessel ; Pressure vessel ; Materials science ; Current (fluid) ; Nuclear engineering ; Flux (metallurgy) ; Metallurgy ; Radiation ; Mechanics ; Nuclear physics ; Composite material ; Thermodynamics ; Physics ; Engineering Fusion materials and technologies ; Nuclear Materials and Properties ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Georgina Salud Cortes-Ramírez | José Ignácio Velasco | Miguel Ángel Plascencia-Espinosa | Ángel E. Absalón | Diana V. Cortés-Espinosa
Source: Coatings (article, 2024-12-03)
Field: Materials Science — Biomaterials

Development of Edible Coatings Based on Different Biopolymers to Enhance the Internal Shelf-Life Quality of Table Eggs Fresh hen eggs constitute a perishable food and are widely consumed worldwide because of their nutritional value. The eggshell is a natural barrier that protects the egg. However, it is very porous and fragile, which makes it susceptible to breakage, contamination, and deterioration, affecting its internal quality during storage, reducing the half-life of the egg for consumption, and causing economic losses to producers. This study aimed to evaluate different edible composites based on biopolymers and proteins for their application as coatings for preservation and shelf-life extension. First, 32 formulations were prepared and evaluated on eggs stored at 4 °C and 25 °C for 6 weeks. Subsequently, 11 coating solutions with the lowest weight loss were selected, and 216 eggs were evaluated; the response variables were HU, YI, and yolk pH and white pH during weeks 1, 3, and 6 of storage. Finally, four formulations, biobased in chitosan, pectin, and alginate derivative composites, presented the highest internal quality results for at least 3 weeks compared with uncoated eggs. These results expand the range of biopolymers available for use as egg coatings compared with the currently used chitosan, as their production process is less expensive than that of chitosan and more attractive to the poultry industry. Shelf life ; Yolk ; Chitosan ; Pectin ; Coating ; Egg white ; Food science ; Eggshell ; Haugh unit ; Food preservation ; Breakage ; Chemistry ; Pulp and paper industry ; Biology ; Materials science ; Composite material ; Body weight ; Ecology ; Biochemistry Nanocomposite Films for Food Packaging ; Animal Nutrition and Physiology ; Food and Agricultural Sciences
Authors: Bin Li | Cheng‐tao Su | Hai Yin | Ji‐ping Zou | Yande Liu
Source: Journal of Chemometrics (article, 2024-06-12)
Field: Chemistry — Analytical Chemistry

Detection of moisture content of edamame based on the fusion of reflectance and transmittance spectra of hyperspectral imaging Abstract Edamame is a nutritious and economically valuable soybean. The moisture content is an important indicator of the quality of the edamame. The traditional methods in the detection of moisture content of edamame have the disadvantage of large detection errors. In this research, the fusion of transmittance and reflectance spectra of hyperspectral imaging combined with chemometrics was proposed to predict the moisture content of edamame. Also, the effect of different preprocessing of the spectra on the predictive performance was analyzed. Single spectra, primary fusion spectra, and intermediate fusion spectra were established as the prediction models for partial least squares regression (PLSR) and partial least squares support vector regression (LSSVR), respectively. The results of the prediction models showed that the spectral transform absorption (STA) combined with PLSR has the best prediction performance for a single spectrum with predictive correlation (R P ) of 0.7749 and ratio of prediction to deviation (RPD) of 1.7. Standard normal variate (SNV) combined with LSSVR has the best prediction performance for primary fusion spectra with R P of 0.8821 and RPD of 1.9. SNV combined with LSSVR has the best prediction performance for intermediate fusion spectra with R P of 0.9149 and RPD of 2.4. The R p and RPD of prediction models of the moisture content of edamame based on fusion spectra were significantly improved compared with single spectra. Compared with primary fusion, intermediate fusion is a more suitable fusion strategy. This research provides experimental basis for the prediction of moisture content of edamame using spectral fusion combined with chemometrics. Partial least squares regression ; Hyperspectral imaging ; Fusion ; Water content ; Chemometrics ; Moisture ; Mathematics ; Chemistry ; Artificial intelligence ; Statistics ; Computer science ; Chromatography Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Water Quality Monitoring and Analysis
Authors: Enric Grau‐Luque | Ignacio Becerril‐Romero | Fabien Atlan | Daniel Huber | Martina Harnisch | Andreas Zimmermann | Alejandro Pérez‐Rodríguez | Maxim Guc | Víctor Izquierdo‐Roca
Source: Small Methods (article, 2024-03-28)
Field: Materials Science — Materials Chemistry

Accelerating the Development of Thin Film Photovoltaic Technologies: An Artificial Intelligence Assisted Methodology Using Spectroscopic and Optoelectronic Techniques Thin film photovoltaic (TFPV) materials and devices present a high complexity with multiscale, multilayer, and multielement structures and with complex fabrication procedures. To deal with this complexity, the evaluation of their physicochemical properties is critical for generating a model that proposes strategies for their development and optimization. However, this process is time-consuming and requires high expertise. In this context, the adoption of combinatorial analysis (CA) and artificial intelligence (AI) strategies represents a powerful asset for accelerating the development of these complex materials and devices. This work introduces a methodology to facilitate the adoption of AI and CA for the development of TFPV technologies. The methodology covers all the necessary steps from the synthesis of samples for CA to data acquisition, AI-assisted data analysis, and the extraction of relevant information for research acceleration. Each step provides details on the necessary concepts, requirements, and procedures and are illustrated with examples from the literature. Then, the application of the methodology to a complex set of samples from a TFPV production line highlights its ability to rapidly glean significant insights even in intricate scenarios. The proposed methodology can be applied to other types of materials and devices beyond PV and using different characterization techniques. Computer science ; Photovoltaic system ; Context (archaeology) ; Process (computing) ; Set (abstract data type) ; Characterization (materials science) ; Systems engineering ; Artificial intelligence ; Nanotechnology ; Materials science ; Engineering ; Electrical engineering Machine Learning in Materials Science ; Quantum Dots Synthesis And Properties ; Chalcogenide Semiconductor Thin Films
Authors: Jose A. Diaz-Olivares | Ryad Bendoula | Wouter Saeys | Maxime Ryckewaert | Ines Adriaens | Xinyue Fu | Matti Pastell | Jean‐Michel Roger | Ben Aernouts
Source: Analytica Chimica Acta (article, 2024-07-10)
Field: Chemistry — Analytical Chemistry

PROSAC as a selection tool for SO-PLS regression: A strategy for multi-block data fusion Partial least squares regression ; Block (permutation group theory) ; Selection (genetic algorithm) ; Sensor fusion ; Fusion ; Regression ; Feature selection ; Data mining ; Identification (biology) ; Pattern recognition (psychology) ; Artificial intelligence ; Data processing ; Chemistry ; Machine learning ; Computer science ; Statistics ; Mathematics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: John‐Lewis Zinia Zaukuu | Zeenatu Suglo Adams | Nana Ama Donkor-Boateng | Eric Tetteh Mensah | Donald Bimpong | Lois Adofowaa Amponsah
Source: Scientific Reports (article, 2024-05-07)
Field: Chemistry — Analytical Chemistry

Non-invasive prediction of maca powder adulteration using a pocket-sized spectrophotometer and machine learning techniques Discriminating different cultivars of maca powder (MP) and detecting their authenticity after adulteration with potent adulterants such as maize and soy flour is a challenge that has not been studied with non-invasive techniques such as near infrared spectroscopy (NIRS). This study developed models to rapidly classify and predict 0, 10, 20, 30, 40, and 50% w/w of soybean and maize flour in red, black and yellow maca cultivars using a handheld spectrophotometer and chemometrics. Soy and maize adulteration of yellow MP was classified with better accuracy than in red MP, suggesting that red MP may be a more susceptible target for adulteration. Soy flour was discovered to be a more potent adulterant compared to maize flour. Using 18 different pretreatments, MP could be authenticated with R<sup>2</sup><sub>CV</sub> in the range 0.91-0.95, RMSE<sub>CV</sub> 6.81-9.16 g/,100 g and RPD 3.45-4.60. The results show the potential of NIRS for monitoring Maca quality. Computer science ; Artificial intelligence ; Machine learning Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Meat and Animal Product Quality
Authors: J. R. Capers | L. D. Stanfield | J. R. Sambles | S. J. Boyes | Alexander W. Powell | Alastair P. Hibbins | S. A. R. Horsley
Source: Physical Review Applied (article, 2024-01-04)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Multiscale design of large and irregular metamaterials Next-generation microwave communications systems face several challenges, particularly from congested communications frequencies and complex propagation environments. We present, and experimentally test, a framework based on the coupled-dipole approximation for designing structures composed of a single simple emitter with a passive disordered scattering structure of rods that is optimized to provide a desired radiation pattern. Our numerical method provides an efficient way to model, and then design and test, otherwise inaccessibly large scattering systems. Published by the American Physical Society 2024 Metamaterial ; Scattering ; Computer science ; Discrete dipole approximation ; Microwave ; Radiation pattern ; Simple (philosophy) ; Common emitter ; Dipole ; Rod ; Radiation ; Physics ; Computational physics ; Electronic engineering ; Optics ; Telecommunications ; Optoelectronics ; Engineering Metamaterials and Metasurfaces Applications ; Antenna Design and Analysis ; Millimeter-Wave Propagation and Modeling
Authors: Iryna Knysh | Denez Raimbault | Ivan Duchemin | Xavier Blase | Denis Jacquemin
Source: The Journal of Chemical Physics (article, 2024-04-11)
Field: Chemistry — Physical and Theoretical Chemistry

Assessing the accuracy of TD-DFT excited-state geometries through optimal tuning with <i>GW</i> energy levels We study the accuracy of excited state (ES) geometries using optimally tuned LC-PBE functionals with tuning based on GW quasiparticle energies. We compare the results obtained with the PBE, PBE0, non-tuned, and tuned LC-PBE functionals with available high-level CC reference values as well as experimental data. First, we compare ES geometrical parameters obtained for three different types of systems: molecules composed of a few atoms, 4-(dimethylamino)benzonitrile (DMABN), and conjugated dyes. To this end, we used wave-function results as benchmarks. Next, we evaluate the accuracy of the theoretically simulated spectra as compared to the experimental ones for five large dyes. Our results show that, besides small compact molecules for which tuning LC-PBE does not allow obtaining geometries more accurate than those computed with standard functionals, tuned range-separated functionals are clearly to be favored, not only for ES geometries but also for 0-0 energies, band shapes, and intensities for absorption and emission spectra. In particular, the results indicate that GW-tuned LC-PBE functionals provide improved matching with experimental spectra as compared to conventionally tuned functionals. It is an open question whether TD-DFT with GW-tuned functionals can qualitatively mimic the actual many-body Bethe-Salpeter (BSE/GW) formalism for which analytic ionic gradients remain to be developed. Excited state ; Spectral line ; Computational physics ; Hybrid functional ; Formalism (music) ; Range (aeronautics) ; Density functional theory ; Quasiparticle ; Molecular physics ; Materials science ; Physics ; Atomic physics ; Chemistry ; Computational chemistry ; Quantum mechanics Photochemistry and Electron Transfer Studies ; Spectroscopy and Quantum Chemical Studies ; Advanced Chemical Physics Studies
Authors: Michael S. Watt | Honey Jane C. Estarija | Michael Bartlett | Russell Main | Dalila Pasquini | Warren Yorston | Emily McLay | Maria Zhulanov | K. Dobbie | Katherine Wardhaugh | Zulfikar Hossain | Stuart Fraser | Henning Buddenbaum
Source: Remote Sensing (article, 2024-03-15)
Field: Chemistry — Analytical Chemistry

Early Detection of Myrtle Rust on Pōhutukawa Using Indices Derived from Hyperspectral and Thermal Imagery Myrtle rust is a very damaging disease, caused by the fungus Austropuccinia psidii, which has recently arrived in New Zealand and threatens the iconic tree species pōhutukawa (Metrosideros excelsa). Canopy-level hyperspectral and thermal images were taken repeatedly within a controlled environment, from 49 inoculated (MR treatment) and 26 uninoculated (control treatment) pōhutukawa plants. Measurements were taken prior to inoculation and six times post-inoculation over a 14-day period. Using indices extracted from these data, the objectives were to (i) identify the key thermal and narrow-band hyperspectral indices (NBHIs) associated with the pre-visual and early expression of myrtle rust and (ii) develop a classification model to detect the disease. The number of symptomatic plants increased rapidly from three plants at 3 days after inoculation (DAI) to all 49 MR plants at 8 DAI. NBHIs were most effective for pre-visual and early disease detection from 3 to 6 DAI, while thermal indices were more effective for detection of disease following symptom expression from 7 to 14 DAI. Using results compiled from an independent test dataset, model performance using the best thermal indices and NBHIs was excellent from 3 DAI to 6 DAI (F1 score 0.81–0.85; accuracy 73–80%) and outstanding from 7 to 14 DAI (F1 score 0.92–0.93; accuracy 89–91%). Hyperspectral imaging ; Remote sensing ; Environmental science ; Geology Spectroscopy and Chemometric Analyses ; Remote Sensing and Land Use
Authors: Yang Lin | Hangyan Wang | Jiayou Guo | Shuiting Zhou | Liange Ouyang
Source: Polymer Composites (article, 2024-08-18)
Field: Materials Science — Materials Chemistry

Transverse tensile properties of laminar unidirectional carbon fiber‐reinforced polymers enhanced with multiscale fiber‐interleaving: Experiments and modeling Abstract In this study, a micromechanics model, based on a hierarchical/gradient interface design, for predicting randomly hybrid carbon nanotube (CNT)/aramid pulp (AP) micro/nano‐fibers interleaved in a laminar unidirectional carbon fiber‐reinforced polymer (UD‐CFRP) is proposed. The model emphasizes the gradient interfaces that are formed in situ because of the graded penetration mechanisms of the CNT and AP. Additionally, via an experimental study, it is analytically verified that CNT/AP‐interleaving enhances the transverse tensile strength and modulus of the UD‐CFRP. The modeling and experimental results show a strong correlation. The increase in transverse tensile strength and modulus of the UD‐CFRP with CNT/AP hybrid interleaving and the associated hierarchical toughening mechanism are confirmed theoretically and experimentally. Furthermore, new insights into the multiscale toughening mechanisms of transverse tensile properties are obtained via systematic analysis. The hierarchical gradient interfacial structure formed by the penetration of CNT/AP‐interleaving and multiscale fiber‐bridging results in a transformation of the failure mechanism. Finally, the effects of the failure mechanism on model predictions and the applicability of micromechanical models are further discussed. Highlights A micromechanics modeling of UD‐CFRP with CNT/AP‐interleaving is proposed. The enhancements of CNT and AP are confirmed theoretically and experimentally. The contribution of CNT and AP to the properties of CFRP is theoretically verified. The effect of the hierarchical fiber‐bridging toughening mechanism is revealed. Materials science ; Composite material ; Ultimate tensile strength ; Micromechanics ; Carbon nanotube ; Modulus ; Composite number Carbon Nanotubes in Composites ; Fiber-reinforced polymer composites ; Mechanical Behavior of Composites
Authors: Olivia Gampp | Luca Wenchel | Peter Güntert | Roland Riek
Source: Angewandte Chemie International Edition (article, 2024-09-30)
Field: Chemistry — Spectroscopy

Homonuclear Super‐Resolution NMR Spectroscopy In homonuclear <sup>1</sup>H NMR (nuclear magnetic resonance) spectra such as [<sup>1</sup>H,<sup>1</sup>H]-NOESY (Nuclear Overhauser Enhancement spectroscopy), which is a historic cornerstone spectrum for biomolecular NMR structural biology, hundreds to thousands of cross peaks are present within a square of approximately 100 ppm<sup>2</sup> leading to a lot of signal overlap. Spectral resolution is thus a limiting factor for unambiguous chemical shift assignment and data interpretation for dynamics and structure elucidation. Acquiring the spectra at higher magnetic fields such as at a 1.2 GHz <sup>1</sup>H frequency helps to reduce spectral crowding, since resolution scales proportionally to the magnetic field strength. Here, we show that the linewidths of cross peaks in [<sup>1</sup>H,<sup>1</sup>H]-NOESY and [<sup>1</sup>H,<sup>1</sup>H]-TOCSY spectra can be further reduced by a factor of 2-3 in each dimension by super-resolution spectroscopy. In the indirect dimension a composite exponential-cosine weighted number of scans along the time increments are recorded and digitally smoothened by a window function, while in the direct dimension an exponential-cosine window function is applied. Furthermore, measurement time saving by reduced-acquisition super-resolution (RASR) is introduced. Application to the 20 kDa protein KRAS shows that highly resolved NMR spectra suitable for automated analysis can be acquired within less than 3 hours. The method opens an avenue towards automated chemical shift assignment, dynamics and structure determination of unlabeled small and medium size proteins within 24 hours. Homonuclear molecule ; Two-dimensional nuclear magnetic resonance spectroscopy ; Spectroscopy ; Nuclear magnetic resonance spectroscopy ; Nuclear Overhauser effect ; Resolution (logic) ; Nuclear magnetic resonance ; Spectral line ; Chemistry ; Spectral resolution ; Free induction decay ; Analytical Chemistry (journal) ; Physics ; Artificial intelligence ; Spin echo ; Computer science ; Molecule ; Magnetic resonance imaging Advanced NMR Techniques and Applications ; Protein Structure and Dynamics ; Advanced MRI Techniques and Applications