jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yue Yang | Weizhi Yang | Hanhan Zhang | Xu Jing | Xiu Jin | Xiaodan Zhang | Zhengfeng Ye | Xiaomei Tang | Lun Liu | Wei Heng | Bing Jia | Liu Li
Source: Sensors (article, 2024-09-29)
Field: Chemistry — Analytical Chemistry

Nondestructive Detection of Corky Disease in Symptomless ‘Akizuki’ Pears via Raman Spectroscopy ‘Akizuki’ pear (Pyrus pyrifolia Nakai) corky disease is a physiological disease that strongly affects the fruit quality of ‘Akizuki’ pear and its economic value. In this study, Raman spectroscopy was employed to develop an early diagnosis model by integrating support vector machine (SVM), random forest (RF), gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), and convolutional neural network (CNN) modeling techniques. The effects of various pretreatment methods and combinations of methods on modeling results were studied. The relative optimal index formula was utilized to identify the SG and SG+WT as the most effective preprocessing methods. Following the optimal preprocessing method, the performance of the majority of the models was markedly enhanced through the process of model reconditioning, among which XGBoost achieved 80% accuracy under SG+WT pretreatment, and F1 and kappa both performed best. The results show that RF, GBDT, and XGBoost are more sensitive to the pretreatment method, whereas SVM and CNN are more dependent on internal parameter tuning. The results of this study indicate that the early detection of Raman spectroscopy represents a novel approach for the nondestructive identification of asymptomatic ‘Akizuki’ pear corky disease, which is of paramount importance for the realization of large-scale detection across orchards. PEAR ; Support vector machine ; Preprocessor ; Artificial intelligence ; Convolutional neural network ; Random forest ; Computer science ; Raman spectroscopy ; Pattern recognition (psychology) ; Decision tree ; Biological system ; Machine learning ; Horticulture ; Biology ; Physics ; Optics Spectroscopy and Chemometric Analyses ; Postharvest Quality and Shelf Life Management ; Plant Pathogens and Fungal Diseases
Authors: Mandeep Purwa | Gaykwad Chandrakanth | Abhilash Rana | Amirreza Mottafegh | Sanjeev Kumar | Dong‐Pyo Kim | Ajay K. Singh
Source: Chemistry - An Asian Journal (article, 2024-06-24)
Field: Chemistry — Inorganic Chemistry

Auto‐Optimized Electro‐Flow Reactor Platform for the <i>in‐situ</i> Reduction of P(V) Oxide to P(III) and Their Application Trivalent phosphine catalysis is mostly utilized to activate the carbon-carbon multiple bonds to form carbanion intermediate species and is highly sensitive to certain variables. Random manual multi-variables are critical for understanding the batch disabled regeneration of trivalent phosphine chemistry. We need the artificial intelligence-based system which can change the variable based on previously conducted failed experiment. Herein, we report an auto-optimized electro-micro-flow reactor platform for the in-situ reduction of stable P(V) oxide to sensitive P(III) and further utilized the method for Corey-Fuchs reaction. In situ ; Phosphine oxide ; Carbanion ; Carbon fibers ; Phosphine ; Oxide ; Flow chemistry ; Flow (mathematics) ; Chemistry ; Reduction (mathematics) ; Catalysis ; Chemical engineering ; Materials science ; Computer science ; Organic chemistry ; Physics ; Engineering ; Mathematics ; Algorithm ; Mechanics Asymmetric Hydrogenation and Catalysis ; Chemical Synthesis and Reactions ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Seongjoo Hwang | Seokhyeon Son | Minsuk Park | In‐Seung Choi | Sang‐Yong Ju
Source: Small Science (article, 2024-03-08)
Field: Materials Science — Materials Chemistry

Sorting of Carbon Nanotubes Based on Dispersant Binding Affinities Sorting single-walled carbon nanotubes (SWNTs) that are heterogeneous into homogeneous groups based on their electronic type, chirality, and handedness is crucial for optoelectronic and biological applications. To achieve this, researchers have utilized dispersants with different binding affinities to sort SWNTs according to their chiralities. This review article provides an overview of the methods developed for sorting SWNTs using dispersants, with a particular focus on the role played by dispersant binding affinities. The article is organized into six sections, including an introduction, a background on SWNTs and dispersant-based individualization of SWNTs, information on dispersants and their binding affinities, separation methods for SWNTs based on controlling the dispersant binding affinity, parameters used to control dispersant binding affinity, and a conclusion. It is hoped that this review will enhance understanding of the intricate interactions between dispersants and SWNTs, leading to the development of new SWNT sorting methods for future applications. Dispersant ; Affinities ; Binding affinities ; Sorting ; Carbon nanotube ; Homogeneous ; Nanotechnology ; Materials science ; Chemistry ; Computer science ; Stereochemistry ; Dispersion (optics) ; Biochemistry ; Receptor ; Mathematics Carbon Nanotubes in Composites ; Graphene research and applications ; Nanopore and Nanochannel Transport Studies
Authors: Nur Arina Mat Rusni | Azuraida Amat | Wan Yusmawati Wan Yusoff | Nor Azlian Abdul-Manaff | Nurazlin Ahmad | L. Hasnimulyati | Hiroyo Segawa
Source: Journal of Advanced Research in Fluid Mechanics and Thermal Sciences (article, 2024-12-10)
Field: Materials Science — Ceramics and Composites

Simulation-Based Radiation Shielding and Optical Properties of Thulium-Doped Bismuth Tellurite Glass Lead-based radiation shielding material is currently used in industry to shield against high-penetration radiation such as gamma rays. However, lead is harmful to humans, animals, and plants. This study proposed a new composition of transparent lead-free glass. Using the melt and quench technique, thulium-doped bismuth tellurite glass with composition (TeO2)1-x (Bi2O3)x (Tm2O3)0.02 where x = 0.05, 0.10, 0.15, and 0.20 mol % was fabricated. Significantly, the glasses with Bi2O3 concentration of 5 mol % and 10 mol% have a higher density than the commercial glass containing lead indicating the fabricated glasses would perform better as a radiation shielding material. Comparing the simulated-radiation shielding properties using software Phy-X and XCom, the glass with 10 mol% of Bi2O3 performs better as radiation shielding material than 5 mol% of Bi2O3. Meanwhile, glass with 5 mol% of Bi2O3 performs better than 10 mol% of Bi2O3 in terms of optical properties. Considering both radiation shielding and optical properties, the fabricated lead-free glass can be widely used in radiation shielding applications that require transparency. Bismuth ; Thulium ; Electromagnetic shielding ; Doping ; Materials science ; Radiation shielding ; Radiation ; Optoelectronics ; Glass recycling ; Optics ; Physics ; Composite material ; Metallurgy Glass properties and applications ; Luminescence Properties of Advanced Materials ; Radiation Shielding Materials Analysis
Authors: Huan Chen | Changxiong Huang | Zhenyu Liao | Xinyao Ma | Jun Fan
Source: The Journal of Physical Chemistry Letters (article, 2024-04-02)
Field: Materials Science — Materials Chemistry

The Role of MXene Surface Terminations on Peptide Transportation in Nanopore Sensing Nanopores with two-dimensional materials have various advantages in sensing, but the fast translocation of molecules hinders their scale-up applications. In this work, we investigate the influence of -F, -O, and -OH surface terminations on the translocation of peptides through MXene nanopores. We find that the longest dwell time always occurs when peptides pass through the Ti<sub>3</sub>C<sub>2</sub>O<sub>2</sub> nanopores. This elongated dwell time is induced by the strongest interaction between peptides and the Ti<sub>3</sub>C<sub>2</sub>O<sub>2</sub> membrane, in which the van der Waals interactions dominate. Compared to the other two MXene nanopores, the braking effect is indicated during the whole translocation process, which evidence the advantage of Ti<sub>3</sub>C<sub>2</sub>O<sub>2</sub> in nanopore sensing. Our work demonstrates that membrane surface chemistry has a great influence on the translocation of peptides, which can be introduced in the design of nanopores for a better performance. Nanopore ; Chromosomal translocation ; Dwell time ; Membrane ; van der Waals force ; Nanotechnology ; Peptide ; Chemistry ; Materials science ; Biophysics ; Molecule ; Chemical physics ; Biochemistry ; Biology ; Organic chemistry MXene and MAX Phase Materials ; Nanopore and Nanochannel Transport Studies ; Advanced biosensing and bioanalysis techniques
Authors: Weijian Zheng | Jun‐Sang Park | Péter Kenesei | Ahsan Ali | Zhengchun Liu | Ian Foster | Nicholas Schwarz | Rajkumar Kettimuthu | Antonino Miceli | Hemant Sharma
Source: Journal of Applied Crystallography (article, 2024-07-04)
Field: Materials Science — Materials Chemistry

Rapid detection of rare events from <i>in situ</i> X-ray diffraction data using machine learning High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk form. These methods are often combined with external stimuli such as thermo-mechanical loading to take snapshots of the evolving microstructure and attributes over time. However, the extreme data volumes and the high costs of traditional data acquisition and reduction approaches pose a barrier to quickly extracting actionable insights and improving the temporal resolution of these snapshots. This article presents a fully automated technique capable of rapidly detecting the onset of plasticity in high-energy X-ray microscopy data. The technique is computationally faster by at least 50 times than the traditional approaches and works for data sets that are up to nine times sparser than a full data set. This new technique leverages self-supervised image representation learning and clustering to transform massive data sets into compact, semantic-rich representations of visually salient characteristics (<i>e.g.</i> peak shapes). These characteristics can rapidly indicate anomalous events, such as changes in diffraction peak shapes. It is anticipated that this technique will provide just-in-time actionable information to drive smarter experiments that effectively deploy multi-modal X-ray diffraction methods spanning many decades of length scales. Computer science ; Diffraction ; Set (abstract data type) ; Cluster analysis ; Data set ; Energy (signal processing) ; Representation (politics) ; Crystallite ; Artificial intelligence ; Context (archaeology) ; Pattern recognition (psychology) ; Materials science ; Optics ; Physics ; Geology Machine Learning in Materials Science ; Advanced X-ray and CT Imaging ; Advanced Electron Microscopy Techniques and Applications
Authors: Jiatong Li | Yunqing Liu | Wei Liu | Jinhong Le | Di Zhang | Wenqi Fan | Dongzhan Zhou | Yuqiang Li | Qing Li
Source: arXiv (Cornell University) (preprint, 2024-11-22)
Field: Materials Science — Materials Chemistry

MolReFlect: Towards In-Context Fine-grained Alignments between Molecules and Texts Molecule discovery is a pivotal research field, impacting everything from the medicines we take to the materials we use. Recently, Large Language Models (LLMs) have been widely adopted in molecule understanding and generation, yet the alignments between molecules and their corresponding captions remain a significant challenge. Previous endeavours often treat the molecule as a general SMILES string or molecular graph, neglecting the fine-grained alignments between the molecular sub-structures and the descriptive textual phrases, which are crucial for accurate and explainable predictions. In this case, we introduce MolReFlect, a novel teacher-student framework designed to contextually perform the molecule-caption alignments in a fine-grained way. Our approach initially leverages a larger teacher LLM to label the detailed alignments by directly extracting critical phrases from molecule captions or SMILES strings and implying them to corresponding sub-structures or characteristics. To refine these alignments, we propose In-Context Selective Reflection, which retrieves previous extraction results as context examples for teacher LLM to reflect and lets a smaller student LLM select from in-context reflection and previous extraction results. Finally, we enhance the learning process of the student LLM through Chain-of-Thought In-Context Molecule Tuning, integrating the fine-grained alignments and the reasoning processes within the Chain-of-Thought format. Our experimental results demonstrate that MolReFlect enables LLMs like Mistral-7B to significantly outperform the previous baselines, achieving SOTA performance on the ChEBI-20 dataset. This advancement not only enhances the generative capabilities of LLMs in the molecule-caption translation task, but also contributes to a more explainable framework. Context (archaeology) ; Computer science ; Geography ; Archaeology Machine Learning in Materials Science ; Biomedical Text Mining and Ontologies ; Computational Drug Discovery Methods
Authors: Hosung Seo | Viktor Ivády | Yuan Ping
Source: Applied Physics Letters (article, 2024-09-30)
Field: Materials Science — Materials Chemistry

First-principles computational methods for quantum defects in two-dimensional materials: A perspective Quantum defects are atomic defects in materials that provide resources to construct quantum information devices such as single-photon emitters and spin qubits. Recently, two-dimensional (2D) materials gained prominence as a host of quantum defects with many attractive features derived from their atomically thin and layered material formfactor. In this Perspective, we discuss first-principles computational methods and challenges to predict the spin and electronic properties of quantum defects in 2D materials. We focus on the open quantum system nature of the defects and their interaction with external parameters such as electric field, magnetic field, and lattice strain. We also discuss how such prediction and understanding can be used to guide experimental studies, ranging from defect identification to tuning of their spin and optical properties. This Perspective provides significant insights into the interplay between the defect, the host material, and the environment, which will be essential in the pursuit of ideal two-dimensional quantum defect platforms. Qubit ; Quantum ; Quantum computer ; Quantum information ; Quantum technology ; Photon ; Quantum information science ; Physics ; Open quantum system ; Quantum entanglement ; Quantum mechanics 2D Materials and Applications ; Electronic and Structural Properties of Oxides ; Graphene research and applications
Authors: Emily E. Claveau | Evangelos Miliordos
Source: Frontiers in Chemistry (article, 2024-12-11)
Field: Materials Science — Materials Chemistry

Electronic structure of metal oxide dications with ammonia ligands and their reactivity towards the selective conversion of methane to methanol High-level quantum chemical calculations are performed for the (NH<sub>3</sub>)MO<sup>2+</sup> and (NH<sub>3</sub>)<sub>5</sub>MO<sup>2+</sup> species (M = Ti-Cu), extending our previous work on the bare MO<sup>2+</sup> ions. The potential energy curves along the M-O distance are constructed for the ground and multiple excited electronic states of (NH<sub>3</sub>)MO<sup>2+</sup> and are compared to those of MO<sup>2+</sup>. We see that ammonia stabilizes the oxo states (M<sup>4+</sup>O<sup>2-</sup>) over the oxyl (M<sup>3+</sup>O<sup>⋅-</sup>) ones. This trend is intensified in the (NH<sub>3</sub>)<sub>5</sub>MO<sup>2+</sup> species. We then examined the reaction of the latter species with both methane and methanol. We find that the oxyl states activate a C-H bond easily with barriers smaller than 10 kcal/mol across all first-row transition metals, while the barriers for the oxo states start from about 50 kcal/mol for M = Ti and decrease linearly to 10 kcal/mol going toward M = Ni. This is attributed to the increasing spin density on the oxygen atom observed for the oxo states. The most important finding is that the formation of hydrogen bonds between the OH group of methanol and the N-H bonds of the ammonia ligands increases the activation barriers for methanol considerably, making them comparable to and slightly higher than those of methane. This finding suggests a new strategy to slow the oxidation of methanol, leading to the long-desired higher methane-to-methanol selectivity. Chemistry ; Methanol ; Methane ; Oxide ; Ammonia ; Metal ; Inorganic chemistry ; Reactivity (psychology) ; Transition metal ; Excited state ; Hydrogen bond ; Catalysis ; Molecule ; Organic chemistry Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions ; CO2 Reduction Techniques and Catalysts
Authors: Daniel S. Müller | Paul Charki | Marie Cordier≈ | Urs Gellrich
Source: The Journal of Organic Chemistry (article, 2024-06-10)
Field: Chemistry — Spectroscopy

Utilization of <sup>13</sup>C NMR Carbon Shifts for the Attribution of Diastereomers in Methyl-Substituted Cyclohexanes In this report, we address the challenge of assigning diastereomers for methyl cyclohexanes, particularly those with quaternary centers, which remains nontrivial despite modern NMR techniques. By utilizing a HSQC NMR experiment to identify methyl-carbons coupled with a simple conformational analysis, we identified an effective and quite general method for assigning stereochemistry, even in cases where diastereomeric mixtures are inseparable. Cyclohexanes ; Diastereomer ; Chemistry ; Carbon-13 NMR ; Stereochemistry ; Heteronuclear single quantum coherence spectroscopy ; Proton NMR ; Chemical shift ; Nuclear magnetic resonance spectroscopy ; Organic chemistry ; Physical chemistry Molecular spectroscopy and chirality ; Analytical Chemistry and Chromatography ; Protein Structure and Dynamics
Authors: Chinedu E. Ekuma
Source: Computer Physics Communications (article, 2024-03-28)
Field: Materials Science — Materials Chemistry

SMATool: Strength of materials analysis toolkit Computer science ; Python (programming language) ; Software ; Mechanical engineering ; Computational science ; Finite element method ; Structural engineering ; Engineering ; Programming language Machine Learning in Materials Science ; Graphene research and applications ; Boron and Carbon Nanomaterials Research
Authors: Jiannan Sun | Ke Yan | Aizhao Pan | Pan Zhang | Xuehang Chen | Xinyi Shi | Chengyu Shi
Source: Physical Chemistry Chemical Physics (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Shell thickness-induced thermal dependence: highly sensitive core–shell CdSe/ZnS/POSS-based temperature probes Fluorescence nanothermometry based on quantum dots is a current research hotspot for novel non-contact temperature monitoring, and is of vital significance for the modulation and design of the sensing properties of sensors. Herein, a design strategy to modulate the temperature-sensing characteristics of quantum dots based on the thickness of a shell is proposed. In this study, CdSe/ZnS quantum dot/POSS-based temperature probe films with varying fluorescence characteristics were developed, and the influence of the ZnS shell on temperature sensing was examined by varying the thickness of the ZnS shell. The temperature dependency, linearity, range of applications, and reversibility of quantum dot thin film probes were all considerably regulated by the ZnS shell, according to research on quantum dot/POSS-based films coated with various shell thicknesses. The CdSe/ZnS temperature probe with 4 monolayers (MLs) stood out among the rest due to its strong thermal stability (at least 5 cycles), large usable temperature range (20-80 °C), and excellent temperature sensitivity (<i>R</i><sup>2</sup> > 0.994). The results demonstrated that the temperature sensing performance of quantum dots was the consequence of the combined effect of multiple temperature response properties induced by the thickness of the shell, and the shell control of quantum dots to optimize the temperature sensing performance was an essential approach for the design of temperature probes. This work demonstrates the great potential of the shell in tuning the temperature sensing performance of quantum dots and provides a viable approach for the design of quantum dot temperature probes. Shell (structure) ; Materials science ; Core (optical fiber) ; Thermal ; Chemical physics ; Nanotechnology ; Chemical engineering ; Composite material ; Chemistry ; Thermodynamics ; Physics Quantum Dots Synthesis And Properties ; Chalcogenide Semiconductor Thin Films ; Advanced Semiconductor Detectors and Materials
Authors: Xiaoliang Zhang | Ronghan Guo | Xiao Feng | Jiawei Fang | Jiaqiang Xu | Xuehui Wang | Jun Zhang
Source: Processes (article, 2024-10-31)
Field: Materials Science — Materials Chemistry

Thermal Oxidation Characteristics and Kinetics of Micron Aluminum Powder in Different Ambient Oxygen Concentration Atmospheres This paper examines the effect of oxygen concentration on the oxidation process and properties of aluminum particles, providing valuable insights for production and storage. Micron-grade aluminum powders were tested at heating rates of 5, 7.5, 10, and 15 K/min under oxygen concentrations of 7, 11, 15, 21, and 30 vol%. Results indicate a two-step mass gain oxidation process, with less pronounced mass gain at lower oxygen concentrations. SEM and XRD characterized the morphological and crystalline changes during oxidation. Lowering oxygen concentration from 30 vol% to 7 vol% increased the onset oxidation temperature by 17.1 °C. Increasing the proportion of inert gas in the atmosphere increases the ignition temperature of aluminum powder. The mathematical modeling approach of AKTS was used to decouple and analyze the thermal effects of simultaneous melting and oxidation, using the Friedman method to show that the apparent activation energy is about 350 kJ/mol in low-oxygen atmospheres (7 vol% and 11 vol%). The kinetics of aluminum oxidation were found to be closely related to the oxygen concentration, and based on the kinetics parameter, it is possible to predict a minimum limiting oxygen concentration. Kinetics ; Oxygen ; Aluminium ; Thermal oxidation ; Materials science ; Thermal ; Atmosphere (unit) ; Chemical engineering ; Metallurgy ; Chemistry ; Thermodynamics ; Oxide ; Organic chemistry Catalytic Processes in Materials Science ; Advanced ceramic materials synthesis ; Magnesium Oxide Properties and Applications