jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Batuhan Yildirim | Jacqueline M. Cole
Source: Journal of Chemical Information and Modeling (article, 2021-03-08)
Field: Materials Science — Materials Chemistry

Bayesian Particle Instance Segmentation for Electron Microscopy Image Quantification Automating the analysis portion of materials characterization by electron microscopy (EM) has the potential to accelerate the process of scientific discovery. To this end, we present a Bayesian deep-learning model for semantic segmentation and localization of particle instances in EM images. These segmentations can subsequently be used to compute quantitative measures such as particle-size distributions, radial- distribution functions, average sizes, and aspect ratios of the particles in an image. Moreover, by making use of the epistemic uncertainty of our model, we obtain uncertainty estimates of its outputs and use these to filter out false-positive predictions and hence produce more accurate quantitative measures. We incorporate our method into the ImageDataExtractor package, as ImageDataExtractor 2.0, which affords a full pipeline to automatically extract particle information for large-scale data-driven materials discovery. Finally, we present and make publicly available the Electron Microscopy Particle Segmentation (EMPS) data set. This is the first human-labeled particle instance segmentation data set, consisting of 465 EM images and their corresponding semantic instance segmentation maps. Segmentation ; Pipeline (software) ; Artificial intelligence ; Computer science ; Data set ; Particle filter ; Bayesian probability ; Particle (ecology) ; Set (abstract data type) ; Pattern recognition (psychology) ; Image segmentation Machine Learning in Materials Science ; Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications
Authors: Bin Jiao | Huimin Ye | Xinwei Liu | Jiexun Bu | Junhan Wu | Wenpeng Zhang | Yunfeng Zhang | Zheng Ouyang
Source: Analytical Chemistry (article, 2021-11-15)
Field: Chemistry — Spectroscopy

Handheld Mass Spectrometer with Intelligent Adaptability for On-Site and Point-of-Care Analysis The development of miniature mass spectrometry (MS) systems with simple analysis procedures is important for the transition of applying MS analysis outside traditional analytical laboratories. Here, we present Mini 14, a handheld MS instrument with disposable sample cartridges designed based on the ambient ionization concept for intrasurgical tissue analysis and surface analysis. The instrumentation architecture consists of a single-stage vacuum chamber with a discontinuous atmospheric interface and a linear ion trap. A major effort in this study for technical advancement is on making handheld MS systems capable of automatically adapting to complex conditions for in-field analysis. Machine learning is used to establish the model for autocorrecting the mass offsets in the mass scale due to temperature variations and a new strategy is developed to extend the dynamic concentration range for analysis. Mini 14 weighs 12 kg and can operate on battery power for more than 3 h. The mass range exceeds <i>m</i>/<i>z</i> 2000, and the full peak width at half-maximum is Δ<i>m</i>/<i>z</i> 0.4 at a scanning speed of 700 Th/s. The direct analysis of human brain tissue for identifying glioma associated with isocitrate dehydrogenase mutations has been achieved and a limit of detection of 5 ng/mL has been obtained for analyzing illicit drugs in blood. Mass spectrometry ; Chemistry ; Mobile device ; Analytical Chemistry (journal) ; Chromatography ; Computer science ; Operating system Mass Spectrometry Techniques and Applications ; Ion-surface interactions and analysis ; Microfluidic and Capillary Electrophoresis Applications
Authors: Zhilong Wang | Haikuo Zhang | Jiahao Ren | Xirong Lin | Tianli Han | Jinyun Liu | Jinjin Li
Source: npj Computational Materials (article, 2021-01-29)
Field: Materials Science — Materials Chemistry

Predicting adsorption ability of adsorbents at arbitrary sites for pollutants using deep transfer learning Abstract Accurately evaluating the adsorption ability of adsorbents for heavy metal ions (HMIs) and organic pollutants in water is critical for the design and preparation of emerging highly efficient adsorbents. However, predicting adsorption capabilities of adsorbents at arbitrary sites is challenging, with currently unavailable measuring technology for active sites and the corresponding activities. Here, we present an efficient artificial intelligence (AI) approach to predict the adsorption ability of adsorbents at arbitrary sites, as a case study of three HMIs (Pb(II), Hg(II), and Cd(II)) adsorbed on the surface of a representative two-dimensional graphitic-C 3 N 4 . We apply the deep neural network and transfer learning to predict the adsorption capabilities of three HMIs at arbitrary sites, with the predicted results of Cd(II) &gt; Hg(II) &gt; Pb(II) and the root-mean-squared errors less than 0.1 eV. The proposed AI method has the same prediction accuracy as the ab initio DFT calculation, but is millions of times faster than the DFT to predict adsorption abilities at arbitrary sites and only requires one-tenth of datasets compared to training from scratch. We further verify the adsorption capacity of g-C 3 N 4 towards HMIs experimentally and obtain results consistent with the AI prediction. It indicates that the presented approach is capable of evaluating the adsorption ability of adsorbents efficiently, and can be further extended to other interdisciplines and industries for the adsorption of harmful elements in aqueous solution. Adsorption ; Artificial neural network ; Aqueous solution ; Computer science ; Ion ; Chemistry ; Materials science ; Artificial intelligence ; Physical chemistry ; Organic chemistry Machine Learning in Materials Science ; Gas Sensing Nanomaterials and Sensors ; Advanced Photocatalysis Techniques
Authors: Shabnam Keykavous-Amand | Reza Peymanfar
Source: Scientific Reports (article, 2021-10-21)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Fabrication of clay soil/CuFe2O4 nanocomposite toward improving energy and shielding efficiency of buildings In this research, the energy and shielding efficiency of brick, fabricated by clay soil, as a practical building material was reinforced using CuFe<sub>2</sub>O<sub>4</sub> nanoparticles. Initially, the nanoparticles were fabricated using the sol-gel method and then loaded in the brick matrix as a guest. The architected samples were characterized by X-ray powder diffraction (XRD), Fourier transform infrared (FTIR), diffuse reflection spectroscopy (DRS), field emission scanning electron microscopy (FE-SEM), High-resolution transmission electron microscopy (HRTEM), vibrating-sample magnetometer (VSM), differential scanning calorimetry (DSC) thermograms, and vector network analyzer (VNA) analyses. IR absorption of the tailored samples was monitored under an IR source using an IR thermometer. IR absorption and energy band gap attested that inserting the nanoparticles in brick medium led to the acceleration of a warming brick, desirable for energy efficiency in cold climates. It is worth noting that the brick/CuFe<sub>2</sub>O<sub>4</sub> nanocomposite achieved a strong reflection loss (RL) of 58.54 dB and gained an efficient bandwidth as wide as 4.22 GHz (RL > 10 dB) with a thickness of 2.50 mm, meanwhile it shielded more than 58% of the electromagnetic waves at X-band by only a filler loading of 10 wt%. The microwave absorbing and shielding characteristics of the composite are mainly originated from conductive loss, electron hopping, natural and exchange resonance, relaxation loss, secondary fields, as well as eddy current loss. Interestingly, the shielding property of the nanocomposite was significantly generated from its absorbing features, reducing the secondary electromagnetic pollutions produced by the shielding materials applying the impedance mismatching mechanism. Materials science ; Reflection loss ; Electromagnetic shielding ; Nanocomposite ; Composite material ; Scanning electron microscope ; Fourier transform infrared spectroscopy ; High-resolution transmission electron microscopy ; Transmission electron microscopy ; Optics ; Nanotechnology ; Composite number Electromagnetic wave absorption materials ; Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies
Authors: Lipei Fu | Qianli Ma | Kaili Liao | Junnan An | Jinmei Bai | Yanfeng He
Source: Nanotechnology Reviews (article, 2021-12-03)
Field: Materials Science — Materials Chemistry

Application of Pickering emulsion in oil drilling and production Abstract When surfactant is used as emulsifier, the stability of emulsion is often greatly reduced with the influence of reservoir conditions (temperature, pressure, salinity, etc. ), which shortens the validity period of emulsion. Pickering emulsion has a wide range of applications in the oil and gas field due to its advantages of good stability and easy regulation. In this article, the formation, stabilization mechanism, and influencing factors of Pickering emulsions were introduced, and the application status and prospects of Pickering emulsions in oil and gas field were summarized. It was pointed out that Pickering emulsion has many advantages and important research value when applied in deep strata and complicated reservoirs. It is expected that this article can effectively reflect the application value of Pickering emulsion in oil and gas field and promote the application of Pickering emulsion in petroleum industry. Pickering emulsion ; Emulsion ; Petroleum engineering ; Materials science ; Chemical engineering ; Engineering Pickering emulsions and particle stabilization ; Enhanced Oil Recovery Techniques ; Geological formations and processes
Authors: Marie Juramy | Romain Chèvre | Paolo Cerreia Vioglio | Fabio Ziarelli | Eric Besson | Stéphane Gastaldi | Stéphane Viel | Pierre Thureau | Kenneth D. M. Harris | Giulia Mollica
Source: Journal of the American Chemical Society (article, 2021-04-15)
Field: Chemistry — Spectroscopy

Monitoring Crystallization Processes in Confined Porous Materials by Dynamic Nuclear Polarization Solid-State Nuclear Magnetic Resonance Establishing mechanistic understanding of crystallization processes at the molecular level is challenging, as it requires both the detection of transient solid phases and monitoring the evolution of both liquid and solid phases as a function of time. Here, we demonstrate the application of dynamic nuclear polarization (DNP) enhanced NMR spectroscopy to study crystallization under nanoscopic confinement, revealing a viable approach to interrogate different stages of crystallization processes. We focus on crystallization of glycine within the nanometric pores (7-8 nm) of a tailored mesoporous SBA-15 silica material with wall-embedded TEMPO radicals. The results show that the early stages of crystallization, characterized by the transition from the solution phase to the first crystalline phase, are straightforwardly observed using this experimental strategy. Importantly, the NMR sensitivity enhancement provided by DNP allows the detection of intermediate phases that would not be observable using standard solid-state NMR experiments. Our results also show that the metastable β polymorph of glycine, which has only transient existence under bulk crystallization conditions, remains trapped within the pores of the mesoporous SBA-15 silica material for more than 200 days. Crystallization ; Metastability ; Chemistry ; Mesoporous material ; Chemical physics ; Spectroscopy ; Nuclear magnetic resonance spectroscopy ; Nanoscopic scale ; Solid-state nuclear magnetic resonance ; Mesoporous silica ; Chemical engineering ; Crystallography ; Nanotechnology ; Nuclear magnetic resonance ; Materials science ; Organic chemistry Advanced NMR Techniques and Applications ; Solid-state spectroscopy and crystallography ; Zeolite Catalysis and Synthesis
Authors: Rijwan Khan | Santosh Kumar | Niharika Dhingra | Neha Bhati
Source: Journal of Food Quality (article, 2021-11-23)
Field: Chemistry — Analytical Chemistry

The Use of Different Image Recognition Techniques in Food Safety: A Study Food safety refers to preparing, transporting, and storing food to avoid foodborne sickness and harm. From farm to factory and factory to fork, food items may meet various health dangers. Therefore, food safety is crucial both monetarily and morally. The implications of failing to comply with food safety requirements are varied. The requirement for accurate, quick, and nonpartisan quality assessments of these features in food products continues to rise with increased demands for dietary materials and high-quality requirements. Computer vision provides an automatic, nondestructive, and economic approach to achieving these aims. A substantial research has demonstrated its effectiveness for fruit and vegetable assessment and classification. It stresses the critical components of image processing technology and a survey of the most current advances across the food sector. This article outlines the essential parts of a computer vision system. In order to avoid foodborne disease and ensure food security, fast and effective detection of pathogenic microorganisms is crucial for public safety biomonitoring. Over the years, microorganism detection techniques have evolved. Food safety ; Harm ; Risk analysis (engineering) ; Quality (philosophy) ; Food security ; Factory (object-oriented programming) ; Business ; Computer science ; Biotechnology ; Food science ; Biology Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Listeria monocytogenes in Food Safety
Authors: Min Liu | Liran Ma
Source: Friction (article, 2021-07-29)
Field: Materials Science — Surfaces, Coatings and Films

Drag reduction methods at solid-liquid interfaces Abstract Friction drag is a nonnegligible matter when relative motion happens between solid and liquid phase, which brings many inconveniences in ship navigation, fluid transportation, microfluid devices, etc. Thereby various methods have been developed focusing on friction drag reduction. In this article, a review of several widely studied drag reduction methods is given, specially, their advantages and limitations in practical applications are discussed. Besides, a comparison of different methods is made and the development prospect of drag reduction is concluded. Drag ; Reduction (mathematics) ; Parasitic drag ; Phase (matter) ; Materials science ; Computer science ; Aerospace engineering ; Nanotechnology ; Marine engineering ; Engineering ; Physics ; Mathematics ; Geometry Surface Modification and Superhydrophobicity ; Adhesion, Friction, and Surface Interactions ; Rheology and Fluid Dynamics Studies
Authors: Ibrahim Dubdub | Mohammed Al‐Yaari
Source: Polymers (article, 2021-10-05)
Field: Materials Science — Polymers and Plastics

Thermal Behavior of Mixed Plastics at Different Heating Rates: I. Pyrolysis Kinetics The amount of generated plastic waste has increased dramatically, up to 20 times, over the past 70 years. More than 50% of municipal plastic waste is composed of polystyrene (PS), polypropylene (PP), and low-density polyethylene (LDPE) products. Therefore, this work has developed a kinetic model that can fully describe the thermal decomposition of plastic mixtures, contributing significantly towards the efficiency of plastic waste management and helping to save the environment. In this work, the pyrolysis of different plastic mixtures, consisting of PP, PS, and LDPE, was performed using a thermogravimetric analyzer (TGA) at three different heating rates (5, 20, and 40 K/min). Four isoconversional models, namely Friedman, Flynn-Wall-Qzawa (FWO), Kissinger-Akahira-Sunose (KAS), and Starink, have been used to obtain the kinetic parameters of the pyrolysis of different plastic mixtures with different compositions. For the equi-mass binary mixtures of PP and PS, the average values of the activation energies were 181, 144 ± 2 kJ/mol obtained using the Freidman and integral (FWO, KAS, and Starink) models, respectively. However, higher values were obtained for the equi-mass ternary plastic mixtures of PP, PS, and LDPE (Freidman: 255 kJ/mol, FWO: 222 kJ/mol, KAS: 223 kJ/mol, and Starink: 222 kJ/mol). The most suitable reaction mechanisms were obtained using the Coats-Redfern model. The results confirm that the most controlling reaction mechanisms obey the first-order (F1) and the third-order (F3) reactions for the pyrolysis of the equi-mass binary (PS and PP) and equi-mass ternary (PS, PP, and LDPE) mixtures, respectively. Finally, the values of the pre-exponential factor (A) were obtained using the four isoconversional models and the linear relationship between <i>ln</i> A and the activation energy was confirmed. Low-density polyethylene ; Polypropylene ; Materials science ; Ternary operation ; Pyrolysis ; Polystyrene ; Thermogravimetric analysis ; Polyethylene ; Kinetics ; Thermal decomposition ; Chemical engineering ; Order of reaction ; Polymer chemistry ; Composite material ; Thermodynamics ; Organic chemistry ; Chemistry ; Polymer ; Reaction rate constant Polymer crystallization and properties ; Thermochemical Biomass Conversion Processes ; Microplastics and Plastic Pollution
Authors: Nathan J. McLaughlin | Hailong Wang | Mengqi Huang | Eric Lee-Wong | Lun‐Hui Hu | Hanyi Lu | Gerald Q. Yan | Genda Gu | Congjun Wu | Yi‐Zhuang You | Chunhui Du
Source: Nano Letters (article, 2021-08-20)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Strong Correlation Between Superconductivity and Ferromagnetism in an Fe-Chalcogenide Superconductor The interplay among topology, superconductivity, and magnetism promises to bring a plethora of exotic and unintuitive behaviors in emergent quantum materials. The family of Fe-chalcogenide superconductors FeTe<sub><i>x</i></sub>Se<sub>1-<i>x</i></sub> are directly relevant in this context due to their intrinsic topological band structure, high-temperature superconductivity, and unconventional pairing symmetry. Despite enormous promise and expectation, the local magnetic properties of FeTe<sub><i>x</i></sub>Se<sub>1-<i>x</i></sub> remain largely unexplored, which prevents a comprehensive understanding of their underlying material properties. Exploiting nitrogen vacancy (NV) centers in diamond, here we report nanoscale quantum sensing and imaging of magnetic flux generated by exfoliated FeTe<sub><i>x</i></sub>Se<sub>1-<i>x</i></sub> flakes, demonstrating strong correlation between superconductivity and ferromagnetism in FeTe<sub><i>x</i></sub>Se<sub>1-<i>x</i></sub>. The coexistence of superconductivity and ferromagnetism in an established topological superconductor opens up new opportunities for exploring exotic spin and charge transport phenomena in quantum materials. The demonstrated coupling between NV centers and FeTe<sub><i>x</i></sub>Se<sub>1-<i>x</i></sub> may also find applications in developing hybrid architectures for next-generation, solid-state-based quantum information technologies. Superconductivity ; Condensed matter physics ; Magnetism ; Chalcogenide ; Ferromagnetism ; Context (archaeology) ; Physics ; Quantum ; Topology (electrical circuits) ; Materials science ; Quantum mechanics Iron-based superconductors research ; Diamond and Carbon-based Materials Research ; 2D Materials and Applications
Authors: Xiaobo Tian | Hjalmar P. Permentier | Rainer Bischoff
Source: Mass Spectrometry Reviews (review, 2021-06-06)
Field: Chemistry — Spectroscopy

Chemical isotope labeling for quantitative proteomics Advancements in liquid chromatography and mass spectrometry over the last decades have led to a significant development in mass spectrometry-based proteome quantification approaches. An increasingly attractive strategy is multiplex isotope labeling, which significantly improves the accuracy, precision and throughput of quantitative proteomics in the data-dependent acquisition mode. Isotope labeling-based approaches can be classified into MS1-based and MS2-based quantification. In this review, we give an overview of approaches based on chemical isotope labeling and discuss their principles, benefits, and limitations with the goal to give insights into fundamental questions and provide a useful reference for choosing a method for quantitative proteomics. As a perspective, we discuss the current possibilities and limitations of multiplex, isotope labeling approaches for the data-independent acquisition mode, which is increasing in popularity. Chemistry ; Proteomics ; Quantitative proteomics ; Mass spectrometry ; Proteome ; Multiplex ; Stable isotope labeling by amino acids in cell culture ; Chromatography ; Isotopic labeling ; Computational biology ; Bioinformatics ; Biochemistry Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Ignacio Sanchez‐Burgos | Eduardo Sanz | Carlos Vega | Jorge R. Espinosa
Source: Physical Chemistry Chemical Physics (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Fcc <i>vs.</i> hcp competition in colloidal hard-sphere nucleation: on their relative stability, interfacial free energy and nucleation rate Hard-sphere crystallization has been widely investigated over the last six decades by means of colloidal suspensions and numerical methods. However, some aspects of its nucleation behaviour are still under debate. Here, we provide a detailed computational characterisation of the polymorphic nucleation competition between the face-centered cubic (fcc) and the hexagonal-close packed (hcp) hard-sphere crystal phases. By means of several state-of-the-art simulation techniques, we evaluate the melting pressure, chemical potential difference, interfacial free energy and nucleation rate of these two polymorphs, as well as of a random stacking mixture of both crystals. Our results highlight that, despite the fact that both polymorphs have very similar stability, the interfacial free energy of the hcp phase could be marginally higher than that of the fcc solid, which in consequence, mildly decreases its propensity to nucleate from the liquid compared to the fcc phase. Moreover, we analyse the abundance of each polymorph in grown crystals from different types of inserted nuclei: fcc, hcp and stacking disordered fcc/hcp seeds, as well as from those spontaneously emerged from brute force simulations. We find that post-critical crystals fundamentally grow maintaining the polymorphic structure of the critical nucleus, at least until moderately large sizes, since the only crystallographic orientation that allows stacking close-packed disorder is the fcc (111) plane, or equivalently the hcp (0001) one. Taken together, our results contribute with one more piece to the intricate puzzle of colloidal hard-sphere crystallization. Nucleation ; Crystallization ; Colloid ; Materials science ; Stacking ; Hard spheres ; Chemical physics ; Work (physics) ; Colloidal particle ; Surface energy ; Colloidal crystal ; Crystallography ; Nanotechnology ; Thermodynamics ; Chemical engineering ; Chemistry ; Physical chemistry ; Physics ; Composite material ; Organic chemistry Material Dynamics and Properties ; Phase Equilibria and Thermodynamics ; Pickering emulsions and particle stabilization