jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Riccardo Bertoglio | Manuel Piliego | Paolo Guadagna | Matteo Gatti | Stefano Poni | Matteo Matteucci
Source: Computers and Electronics in Agriculture (article, 2024-08-24)
Field: Chemistry — Analytical Chemistry

On-the-go table grape ripeness estimation via proximal snapshot hyperspectral imaging The monitoring of grapes for ripeness estimation is a practice that enables fruit harvesting at the optimal time. Hyperspectral Imaging (HSI) represents a non-destructive and high-throughput alternative to traditional laboratory analyses. Current literature approaches perform hyperspectral measurements using line scan sensors or low-resolution static snapshot cameras, which hinder a fast per-bunch ripeness characterization. We propose a framework for on-the-go collection and processing of proximal snapshot hyperspectral images to estimate single bunch ripeness parameters. Focusing on table grapes ( Vitis vinifera L. cv. Red Globe), we collected images under natural illumination with a hyperspectral camera (500–900 nm) mounted on a moving vehicle in an experimental block sited in Piacenza, Italy. We investigated images collected in August and September 2021 representing two ripening stages. The composition of the imaged grape bunches was determined through laboratory chemical analyses to predict Total Soluble Solids (TSS) and anthocyanin concentration. The images were pre-processed via multimodal image registration to correct the unalignment of bands due to the vehicle motion, and the single bunches were automatically identified on false RGB images through a Mask Region-Convolutional Neural Network (Mask R-CNN) instance segmentation network. The mean spectra of the bunches were used as input features of a Partial Least Squares Regression (PLSR) model to predict the chemical parameters at single bunch and whole vine scales. The regression model of TSS had an R 2 (10-fold nested cross-validation) of 0.75 and 0.85 on a per-bunch and per-vine basis, respectively. The regression model of anthocyanin had an R 2 of 0.68 and 0.49 on a per-bunch and per-vine basis, respectively. The results suggest the potential of using snapshot hyperspectral images for high-throughput analysis of a per-bunch grape ripeness estimation. The method described in this study could give valuable information to improve grape ripening monitoring and management of harvest operations and even allow for precise and automated robotic harvesting. • On-the-go snapshot HSI was used to predict TSS and anthocyanin concentration in grape bunches. • Multimodal registration has effectively corrected band misalignment due to vehicle movement. • Mask R-CNN was used to identify single bunches on false RGB hyperspectral images. • TSS predictions outperformed those of anthocyanins. • Savitzky–Golay outperformed Standard Normal Variate and Multiplicative Scatter Correction. Ripeness ; Hyperspectral imaging ; Snapshot (computer storage) ; Artificial intelligence ; Computer vision ; Computer science ; Mathematics ; Remote sensing ; Geology ; Biology ; Food science Spectroscopy and Chemometric Analyses ; Horticultural and Viticultural Research ; Fermentation and Sensory Analysis
Authors: Menad Nait Amar | Noureddine Zeraibi | Chahrazed Benamara | Hakim Djema | Redha Saifi | Mourad Gareche
Source: Fuel (article, 2024-08-05)
Field: Chemistry — Analytical Chemistry

Modeling wax disappearance temperature using robust white-box machine learning Wax ; White box ; White (mutation) ; Computer science ; Artificial intelligence ; Materials science ; Machine learning ; Chemistry ; Composite material Petroleum Processing and Analysis ; Heat transfer and supercritical fluids ; Mass Spectrometry Techniques and Applications
Authors: Shingo Urata | Aik Rui Tan | Rafael Gómez‐Bombarelli
Source: Physical Review Materials (article, 2024-03-07)
Field: Materials Science — Ceramics and Composites

Modifying ring structures in lithium borate glasses under compression: MD simulations using a machine-learning potential Machine-learning potentials (MLPs) are advantageous in modeling boron coordination and three-membered rings (3-rings) in borate glasses. In this study, the prominent ability of MLP enables us to study how boron coordination varies during deformation, and the change in microstructure circumvents the overload stress in lithium borate and lithium borosilicate glasses via molecular dynamics simulations. Under uniaxial and triaxial compressive deformations, some of the threefold coordinated boron, $^{3}\mathrm{B}$, atoms were altered to be fourfold coordinated boron ($^{4}\mathrm{B}$) at a strain range beyond elastic deformations. According to the local deformation analysis, a microstructure at around $^{4}\mathrm{B}$ was determined to be rigid, specifically, that around $^{4}\mathrm{B}$ forming a 3-ring exhibited the least flexibility. Conversely, the local region at around $^{3}\mathrm{B}$ and oxygen atoms in nonring structures flexibly deformed following the entire deformation. As a result, nonbridging oxygen located in the vicinity of $^{3}\mathrm{B}$ was found to migrate to form $^{4}\mathrm{B}$ due to compression. Remarkably, most of the boron atoms became $^{4}\mathrm{B}$, and they formed abundant three membered rings in the borate glasses at a certain strain owing to the triaxial compression. Consequently, it is inferred that such a drastic structural variation can be the origin of high damage resistance of borate glasses. Materials science ; Lithium borate ; Lithium (medication) ; Compression (physics) ; Boron ; Ring (chemistry) ; Molecular dynamics ; Composite material ; Computational chemistry ; Borate glass ; Optoelectronics ; Organic chemistry Glass properties and applications ; High-pressure geophysics and materials ; Phase-change materials and chalcogenides
Authors: Andreas E. Robertson | Adam P. Generale | Conlain Kelly | Michael Buzzy | Surya R. Kalidindi
Source: Integrating materials and manufacturing innovation (article, 2024-02-12)
Field: Materials Science — Materials Chemistry

MICRO2D: A Large, Statistically Diverse, Heterogeneous Microstructure Dataset Microstructure ; Computer science ; Salient ; Set (abstract data type) ; Artificial intelligence ; Materials science Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Electron and X-Ray Spectroscopy Techniques
Authors: Huan Ye | Zhaoyang Hu | Rongzhang Yin | Teak D. Boyko | Yunpeng Liu | Yanzhang Li | Chunjiang Li | Anhuai Lu | Yan Li
Source: Geochimica et Cosmochimica Acta (article, 2024-10-24)
Field: Chemistry — Inorganic Chemistry

Electron transfer at birnessite/organic compound interfaces: mechanism, regulation, and two-stage kinetic discrepancy in structural rearrangement and decomposition Birnessite ; Decomposition ; Kinetic energy ; Mechanism (biology) ; Electron transfer ; Chemistry ; Stage (stratigraphy) ; Photochemistry ; Geology ; Physics ; Organic chemistry ; Paleontology ; Manganese Radioactive element chemistry and processing ; Electrochemical Analysis and Applications ; Geochemistry and Elemental Analysis
Authors: Yujia Jin | Shifa Wang | Yuanyuan Zhang | Huajing Gao | Xianju Zhou | Dengfeng Li | Hua Yang | Leiming Fang | V. Jagadeesha Angadi | Mohd Ubaidullah | Bidhan Pandit | H Zhang
Source: Ceramics International (article, 2024-02-07)
Field: Materials Science — Materials Chemistry

Rare earth ions (Er, Ho and Sm) regulate the optical and photoluminescence properties of CaAl12O19: Performance prediction and anti-counterfeiting application Materials science ; Phosphor ; Ion ; Photoluminescence ; Luminescence ; Optoelectronics ; Chemistry Luminescence Properties of Advanced Materials ; Carbon and Quantum Dots Applications ; Luminescence and Fluorescent Materials
Authors: Golam Azom | Anne Milet | Rolf David | Revati Kumar
Source: The Journal of Physical Chemistry C (article, 2024-09-24)
Field: Materials Science — Materials Chemistry

From Graphene Oxide to Graphene: Changes in Interfacial Water Structure and Reactivity Using Deep Neural Network Force Fields Graphene oxides (GO) are thin graphene sheets containing oxygen-bearing defects. These sheets have a complex structure with sp3 carbons interspersed among sp2 carbons, which results in competition between aromatic and hydrophilic domains at the GO–water interface. The GO–water as well as neat graphene–water interfacial regions play a crucial role in various applications. While ab initio molecular dynamics simulations provide high accuracy in studying this complex region, they require significant computational resources, which limits the investigation of the interface at both time and length scales. To tackle this issue, a deep neural network force field (DNNF), trained and validated on AIMD data, was developed. It achieves DFT-level accuracy using only a fraction of the computational cost. This DNNF has been successfully used for simulating graphene oxide to reduced graphene oxide right up to fully reduced graphene–water interfaces. The ordering of water near the interface was studied as a function of oxidation level from fully oxidized graphene oxide to graphene. The vibrational sum frequency generation spectrum of the graphene–water interface was determined and compared to experimental data as well as spectra from graphene oxide–water sheets at different oxidation levels. Connections between different spectral signatures and the orientation of different waters were determined. The reactivity and buckling of the different sheets were examined. The analyses of the trajectories revealed the formation of multiple hydronium formation events with sustained proton hopping over more than a 100 ps in the fully oxidized GO–water systems. Graphene ; Oxide ; Materials science ; Nanotechnology ; Reactivity (psychology) ; Artificial neural network ; Chemical physics ; Network structure ; Chemical engineering ; Chemistry ; Computer science ; Artificial intelligence ; Engineering ; Distributed computing ; Metallurgy Machine Learning in Materials Science ; Spectroscopy and Quantum Chemical Studies ; Electrochemical Analysis and Applications
Authors: Tommaso Ferri | Anita Caracciolo | G. Borghi | Marco Carminati | S. Altieri | Nicoletta Protti | C. Fiorini
Source: IEEE Transactions on Nuclear Science (article, 2024-04-08)
Field: Materials Science — Materials Chemistry

Imaging Study and First Measurements of a LaBr<sub>3</sub> Gamma Detector for BNCT Applications In this study we present the preliminary imaging results obtained with a gamma module called BeNEdiCTE, specifically designed for Boron Neutron Capture Therapy (BNCT). The primary objective of the BNCT-SPECT system is to quantitatively assess and pinpoint the <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">10</sup> B contribution to the dose administered to a patient during BNCT treatment by detecting the 478 keV gamma rays emitted from the <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">10</sup> B(n,α) <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">7</sup> Li reactions. Starting from a feasibility study of a collimator suitable for a BNCT-SPECT system, we end up presenting the first images obtained by reconstructing vials containing boron powder thanks to the aid of an Artificial Neural Network. However, the extremely high-intensity neutron flux of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">9</sup> n/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> /s and the presence of mixed radiation fields in the irradiation room pose significant challenges to this task. To overcome these challenges, the implementation of an appropriate collimator becomes essential. Thanks to Monte Carlo simulations we designed a lead pinhole collimator, with a twofold focus on enhancing spatial resolution (achieving < 1 cm) and maximizing geometric efficiency (attaining >10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-6</sup> ). Detector ; Physics ; Gamma ray ; Gamma spectroscopy ; Nuclear physics ; Particle detector ; Optics ; Materials science ; Medical physics ; Radiochemistry ; Chemistry Boron and Carbon Nanomaterials Research ; Nuclear Physics and Applications ; Inorganic Chemistry and Materials
Authors: Jing Xu | Shu Zhang | Si-Heng Luo | Chen-ru Xiong | Minghuai Zhu | Jing Chang | Bo Zou | Bin Ren | Zhong‐Qun Tian | Guokun Liu
Source: Analytical Chemistry (article, 2024-05-28)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Rapid Sample Pretreatment Facilitating SERS Detection of Trace Weak Organic Acids/Bases in Complex Matrices Fast and efficient sample pretreatment is the prerequisite for realizing surface-enhanced Raman spectroscopy (SERS) detection of trace targets in complex matrices, which is still a big issue for the practical application of SERS. Recently, we have proposed a highly performed liquid-liquid extraction (LLE)-back extraction (BE) for weak acids/bases extraction in drinking water and beverage samples. However, the performance efficiency decreased drastically on facing matrices like food and biological blood. Based on the total interaction energies among target, interferent, and extractant molecules, solid-phase extraction (SPE) with a higher selectivity was introduced in advance of LLE-BE, which enabled the sensitive (μg L<sup>-1</sup> level) and rapid (within 10 min) SERS detection of both koumine (a weak base) and celastrol (a weak acid) in different food and biological samples. Further, the high SERS sensitivity was determined unmanned by Vis-CAD (a machine learning algorithm), instead of the highly demanded expert recognition. The generality of SPE-LLE-BE for various weak acids/bases (2 < p<i>K</i><sub>a</sub> < 12), accompanied by the high efficiency, easy operation, and low cost, offers SERS as a powerful on-site and efficient inspection tool in food safety and forensics. Chemistry ; Complex matrix ; TRACE (psycholinguistics) ; Sample (material) ; Chromatography Gold and Silver Nanoparticles Synthesis and Applications ; Electrochemical Analysis and Applications ; Identification and Quantification in Food
Authors: Manoj Kumar Agrawal | VVSH Prasad | Ginni Nijhawan | Sarah Salah Jalal | B Rajalakshmi | Shashi Prakash Dwivedi
Source: E3S Web of Conferences (review, 2024-01-01)
Field: Materials Science — Surfaces, Coatings and Films

RETRACTED: A Comprehensive Review of Electron Microscopy in Materials Science: Technological Advances and Applications This proceeding volume has been retracted from the publication because we found some solid reasons to believe that it has infringed our integrity criteria and now presents a risk for our journal and scholarly science in general. Different types of malpractice are involved, in particular citation manipulation and inappropriate references. We are extremely concerned by such malpractice which considerably impacts the image of our title and our Publisher’s reputation. For further details, please refer to our publishing ethics policies . If you have any questions, please contact us at contact@webofconferences.org See the retraction notice E3S Web of Conferences 505 , 00001 (2024), https://doi.org/10.1051/e3sconf/202450500001 Nanotechnology ; Electron microscope ; Materials science ; Engineering physics ; Engineering ; Physics ; Optics Electron and X-Ray Spectroscopy Techniques ; Semiconductor materials and interfaces ; Chalcogenide Semiconductor Thin Films
Authors: Holger‐Dietrich Saßnick | Fabiana Machado Ferreira De Araujo | Joshua Edzards | Caterina Cocchi
Source: Inorganic Chemistry (article, 2024-01-17)
Field: Chemistry — Inorganic Chemistry

Impact of Ligand Substitution and Metal Node Exchange in the Electronic Properties of Scandium Terephthalate Frameworks The search for sustainable alternatives to established materials is a sensitive topic in materials science. Due to their unique structural and physical characteristics, the composition of metal-organic frameworks (MOFs) can be tuned by the exchange of metal nodes and the functionalization of organic ligands, giving rise to a large configurational space. Considering the case of scandium terephthalate MOFs and adopting an automatized computational framework based on density-functional theory, we explore the impact of metal substitution with the earth-abundant isoelectronic elements Al and Y, and ligand functionalization of varying electronegativity. We find that structural properties are strongly impacted by metal ion substitution and only moderately by ligand functionalization. In contrast, the energetic stability, the charge density distribution, and the electronic properties, including the size of the band gap, are primarily affected by the termination of the linker molecules. Functional groups such as OH and NH<sub>2</sub> lead to particularly stable structures thanks to the formation of hydrogen bonds and affect the electronic structure of the MOFs by introducing midgap states. Chemistry ; Scandium ; Electronegativity ; Density functional theory ; Metal-organic framework ; Ligand (biochemistry) ; Surface modification ; Computational chemistry ; Electronic structure ; Band gap ; Molecule ; Chemical physics ; Metal ; Hydrogen bond ; Inorganic chemistry ; Organic chemistry ; Physical chemistry ; Materials science Metal-Organic Frameworks: Synthesis and Applications ; X-ray Diffraction in Crystallography ; Magnesium Oxide Properties and Applications
Authors: James R. Howard | Julia R. Shuluk | Arya Bhakare | Eric V. Anslyn
Source: Chem (article, 2024-06-12)
Field: Chemistry — Spectroscopy

Data-science-guided calibration curve prediction of an MLCT-based ee determination assay for chiral amines Calibration curve ; Calibration ; Chemistry ; Chromatography ; Mathematics ; Statistics Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Chromatography ; thermodynamics and calorimetric analyses
Authors: Eman M. Fayyad | Fatma Nabhan | Aboubakr M. Abdullah
Source: Coatings (article, 2024-12-20)
Field: Materials Science — Materials Chemistry

Focused Review on Graphitic Carbon Nitride (g-C3N4) in Corrosion and Erosion Applications Inorganic, organic, and metallic coatings have received much attention due to their great protection applications in oil and gas industries and their development through finding eco-friendly materials for the coatings. Their unique structure, low cost, and facile synthesis are some of the few properties of graphitic carbon nitride (g-C3N4) materials that make them useful in a number of applications. Moreover, g-C3N4 offers exceptional chemical and thermal stability and a high specific surface area, and it is well known for its outstanding biocompatibility and biological activity. Numerous investigations have reported various types of C3N4-incorporated coatings that have enhanced corrosion, wear, and mechanical resistance properties. This review highlights the new applications of g-C3N4 (standalone, in an alloy, or composite) as a coating in the wear and corrosion protection fields. Furthermore, a strong focus on the structure, unique properties, and preparation technique of g-C3N4 are summarized, especially in metallic coatings, which is a highly novel trend. Lastly, various important issues based on current research are proposed for future prospective work that should be further studied in this attractive research topic. Graphitic carbon nitride ; Erosion ; Corrosion ; Erosion corrosion ; Materials science ; Environmental science ; Metallurgy ; Geology ; Chemistry ; Geomorphology ; Photocatalysis MXene and MAX Phase Materials ; Advanced Photocatalysis Techniques ; ZnO doping and properties
Authors: Charalampos Livas | Pantelis N. Trikalitis | George E. Froudakis
Source: Journal of Chemical Information and Modeling (article, 2024-10-31)
Field: Chemistry — Inorganic Chemistry

MOFSynth: A Computational Tool toward Synthetic Likelihood Predictions of MOFs In the past decade, high-throughput computational studies of materials have increased significantly mainly due to advances in computer capabilities and have attracted a great deal of interest. In the field of metal-organic frameworks (MOFs), over a million hypothetical MOFs have been designed in silico, yet only a small fraction of these have been synthesized. For validating the computational-hypothetical results and accelerating the progress in the field, there is a pressing need for distinguishing MOFs that are more likely to be synthesized for real-life applications. This study presents a comprehensive investigation into the synthesizability likelihood of MOFs, utilizing a novel computational approach based on the disparities in energy and geometry between the linker conformation within the MOF structure and its isolated, free-gas state since both of these have been proven to be critical factors influencing MOF synthesis. Our user-friendly tool streamlines synthesizability evaluation, requiring minimal expertise in computational chemistry. By deconstructing over 40,000 MOFs from databases, including QMOF, CoRE MOF, and ToBaCCo, we analyze key parameters defining the linker strain within the MOF unit cell. Our results indicate that QMOF and CoRE MOF contain more promising candidates for synthesis, while ToBaCCo exhibits a relatively poor synthesizability likelihood due to unoptimized materials. Through extensive analysis, we identify optimal linker candidates for highly synthesizable MOFs. Consistent trends in energy distribution across databases that are confirmed by high Pearson and Spearman coefficients suggest the potential for omitting optimization calculations, significantly reducing computational costs. This study underscores the importance of linker deformation and energy disparities and enhances our understanding of synthetic accessibility in MOF research, offering valuable insights for future advancements in the field. Computer science Metal-Organic Frameworks: Synthesis and Applications ; Machine Learning in Materials Science ; X-ray Diffraction in Crystallography
Authors: Wenwen Liu | Hongling Li | Roland Yingjie Tay
Source: Nanoscale (article, 2024-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Recent progress of high-performance in-plane zinc ion hybrid micro-supercapacitors: design, achievements, and challenges With the increasing demand for wearable and miniature electronics, in-plane zinc (Zn) ion hybrid micro-supercapacitors (ZIHMSCs), as a promising and compatible energy power source, have attracted tremendous attention due to their unique merits. Despite enormous development and breakthroughs in this field, there is still a lack of a systematic and comprehensive review to update the recent progress of in-plane ZIHMSCs in the design and fabrication of both micro-anodes and micro-cathodes, the exploration and optimization of new electrolytes, and the investigation of related-energy storage mechanisms. This minireview summarizes the key breakthroughs and recent advances in the construction of high-performance in-plane ZIHMSCs. First, the background and fundamentals of in-plane ZIHMSCs are briefly introduced. Then, new concepts, strategies, and latest exciting developments in the preparation and interfacial engineering of Zn metal micro-anodes, the fabrication of advanced micro-cathodes, and the exploration of new electrolyte systems are discussed, respectively. Finally, the key challenges and future directions for the development of high-performance in-plane ZIHMSCs are presented as well. This review not only accounts for the recent research progress in the field of the in-plane ZIHMSCs, but also provides important new insights into the design of next-generation miniaturized energy storage devices. Supercapacitor ; Nanotechnology ; Energy storage ; Fabrication ; Anode ; Materials science ; Computer science ; Power (physics) ; Capacitance ; Chemistry ; Physics Supercapacitor Materials and Fabrication ; Advanced battery technologies research ; Advancements in Battery Materials