jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Dominique Ausserré | Refahi Abou Khachfe | Takashi Taniguchi | Kenji Watanabe | Fabien Vialla
Source: physica status solidi (b) (article, 2023-05-24)
Field: Materials Science — Materials Chemistry

Backside Absorbing Layer Microscopy: Monolayer Counting in 2D Crystal Flakes The properties of two‐dimensional (2D) material stacks critically depend on the number of monolayers ( m ) in the stack. It is therefore important to quantify this number, which is a local quantity since 2D stacks are essentially heterogeneous. Optical interferential techniques based on contrast‐enhancing surfaces may be sensitive enough to visualize m variations but the experimental determination of m requires heavy and unstable comparisons with multiparameter numerical models. Focusing on the recent backside absorbing layer microscopy, the most sensitive to date among interferential techniques, a self‐calibrating method is demonstrated allowing instantaneous monolayer counting all over the sample surface which does not require the knowledge of the instrumental parameters, the sample or ambient refractive indices or the detailed structure of the contrast‐enhancing layer. This method is introduced step by step using examples of hexagonal boron nitride (hBN) stacks with increasing complexity. Exact monolayer counting up to 36 hBN monolayers is obtained using basic image analysis. Monolayer ; Microscopy ; Layer (electronics) ; Materials science ; Stack (abstract data type) ; Hexagonal crystal system ; Optical microscope ; Contrast (vision) ; Optics ; Optoelectronics ; Nanotechnology ; Chemistry ; Crystallography ; Computer science ; Composite material ; Physics ; Scanning electron microscope Graphene research and applications ; 2D Materials and Applications ; Surface and Thin Film Phenomena
Authors: Xianpeng Yang | Chengbao Xie | Ning Liu | Xin Du | Suqing Wang | Huasheng Jiang | Zhengang Zhang
Source: Journal of Materials Science and Chemical Engineering (article, 2023-01-01)
Field: Materials Science — Surfaces, Coatings and Films

Overview of Precious Metal Content Analysis Methods in Automotive Catalytic Converter With the increasing awareness of environmental protection, people’s concern of pollution issues arising. Vehicles, as the most important means of transportation, its exhaust emission has received considerable attention. The catalytic converter is able to purify harmful substances in exhaust gas. The absolute content of precious metals in the catalytic converter dominates the exhaust gas purification effect. Accurate detection of precious metal content is of great significance for controlling the cost of catalysts, ensuring catalytic performance and recovering precious metals from spent catalysts. We herein summarized several instruments for precious metals content exploration, such as X-ray fluorescence spectrometer (XRF), atomic absorption spectrometer (AAS), inductively coupled plasma emission spectrometer (ICP) and spectrophotometer. In this thesis, the feasibility of using various devices for characterizing precious metal content in catalytic converters is analyzed and their strengths or weaknesses are elaborated. Precious metal ; Catalytic converter ; Catalysis ; Materials science ; Exhaust gas ; Inductively coupled plasma ; Spectrometer ; Atomic absorption spectroscopy ; Automotive industry ; Metal ; Process engineering ; Waste management ; Environmental science ; Analytical Chemistry (journal) ; Environmental chemistry ; Metallurgy ; Plasma ; Chemistry ; Engineering ; Organic chemistry Electron and X-Ray Spectroscopy Techniques ; Nuclear Physics and Applications ; Analytical chemistry methods development
Authors: Ming Zhong | Siru Ouyang | Minhao Jiang | Vivian Hu | Yizhu Jiao | Xuan Wang | Jiawei Han
Source: arXiv (Cornell University) (preprint, 2023-07-04)
Field: Materials Science — Materials Chemistry

ReactIE: Enhancing Chemical Reaction Extraction with Weak Supervision Structured chemical reaction information plays a vital role for chemists engaged in laboratory work and advanced endeavors such as computer-aided drug design. Despite the importance of extracting structured reactions from scientific literature, data annotation for this purpose is cost-prohibitive due to the significant labor required from domain experts. Consequently, the scarcity of sufficient training data poses an obstacle to the progress of related models in this domain. In this paper, we propose ReactIE, which combines two weakly supervised approaches for pre-training. Our method utilizes frequent patterns within the text as linguistic cues to identify specific characteristics of chemical reactions. Additionally, we adopt synthetic data from patent records as distant supervision to incorporate domain knowledge into the model. Experiments demonstrate that ReactIE achieves substantial improvements and outperforms all existing baselines. Computer science ; Scarcity ; Obstacle ; Domain (mathematical analysis) ; Annotation ; Work (physics) ; Information extraction ; Data science ; Artificial intelligence ; Engineering Machine Learning in Materials Science ; Advanced Text Analysis Techniques ; Computational Drug Discovery Methods
Authors: Peng Liu | Kaifan Yang | Jiahong Zhang | Renjun Xu
Source: arXiv (Cornell University) (preprint, 2023-06-28)
Field: Materials Science — Materials Chemistry

S2SNet: A Pretrained Neural Network for Superconductivity Discovery Superconductivity allows electrical current to flow without any energy loss, and thus making solids superconducting is a grand goal of physics, material science, and electrical engineering. More than 16 Nobel Laureates have been awarded for their contribution to superconductivity research. Superconductors are valuable for sustainable development goals (SDGs), such as climate change mitigation, affordable and clean energy, industry, innovation and infrastructure, and so on. However, a unified physics theory explaining all superconductivity mechanism is still unknown. It is believed that superconductivity is microscopically due to not only molecular compositions but also the geometric crystal structure. Hence a new dataset, S2S, containing both crystal structures and superconducting critical temperature, is built upon SuperCon and Material Project. Based on this new dataset, we propose a novel model, S2SNet, which utilizes the attention mechanism for superconductivity prediction. To overcome the shortage of data, S2SNet is pre-trained on the whole Material Project dataset with Masked-Language Modeling (MLM). S2SNet makes a new state-of-the-art, with out-of-sample accuracy of 92% and Area Under Curve (AUC) of 0.92. To the best of our knowledge, S2SNet is the first work to predict superconductivity with only information of crystal structures. This work is beneficial to superconductivity discovery and further SDGs. Code and datasets are available in https://github.com/zjuKeLiu/S2SNet Superconductivity ; Economic shortage ; Work (physics) ; Crystal (programming language) ; Computer science ; Physics ; Sustainable development ; Condensed matter physics ; Engineering physics ; Political science ; Quantum mechanics ; Law Machine Learning in Materials Science ; Superconductivity in MgB2 and Alloys ; Inorganic Chemistry and Materials
Authors: Giovanni Trezza | Eliodoro Chiavazzo
Source: arXiv (Cornell University) (preprint, 2023-11-16)
Field: Materials Science — Materials Chemistry

Classification-based detection and quantification of cross-domain data bias in materials discovery It stands to reason that the amount and the quality of data is of key importance for setting up accurate AI-driven models. Among others, a fundamental aspect to consider is the bias introduced during sample selection in database generation. This is particularly relevant when a model is trained on a specialized dataset to predict a property of interest, and then applied to forecast the same property over samples having a completely different genesis. Indeed, the resulting biased model will likely produce unreliable predictions for many of those out-of-the-box samples. Neglecting such an aspect may hinder the AI-based discovery process, even when high quality, sufficiently large and highly reputable data sources are available. In this regard, with superconducting and thermoelectric materials as two prototypical case studies in the field of energy material discovery, we present and validate a new method (based on a classification strategy) capable of detecting, quantifying and circumventing the presence of cross-domain data bias. Data science ; Quality (philosophy) ; Process (computing) ; Computer science ; Big data ; Key (lock) ; Data quality ; Selection (genetic algorithm) ; Database ; Data mining ; Artificial intelligence ; Computer security ; Engineering ; Physics Machine Learning in Materials Science ; Expert finding and Q&A systems
Authors: Janak Tiwari | Tianli Feng
Source: arXiv (Cornell University) (preprint, 2023-12-18)
Field: Materials Science — Materials Chemistry

Accurate prediction of thermal conductivity of Al2O3 at ultrahigh temperatures Many complex crystals show a flattening or even increasing lattice thermal conductivity at high temperatures, which deviates from the traditional 1/T decay trend given by conventional phonon theory. In this work, we predict the thermal conductivity of Al2O3 that matches with experimental data from room temperature to near melting point (2200 K). The lattice thermal conductivity is found to be composed of contributions of phonon, diffuson, and radiation. Phonon particle thermal conductivity decays approximately as ~T^-1.14 after considering four-phonon scattering as well as finite temperature corrections to lattice constant, harmonic, and anharmonic force constants. Diffuson (inter-band tunneling) thermal conductivity increases roughly as ~T^0.43. Radiation thermal conductivity increases as ~T2.51, being slightly smaller than ~T^3 due to the increase of phonon linewidth with temperature, which increases photon extinction coefficient and reduces photon mean free path. At room temperature, phonon, diffuson, and radiation contribute about 99%, 1%, and 0, respectively. At 2200 K, the contributions change to 61%, 20%, and 19%, respectively. Four-phonon scattering is important at ultra-high temperature, decreasing the phonon thermal conductivity by a maximum of 24%. The finite-temperature softening effects of harmonic and anharmonic force constants increase the phonon thermal conductivity by a maximum of 36% at ultra-high temperatures. We also verify that Green-Kubo MD can capture phonons' both particle and wave natures, similar to the Wigner formalism. Phonon ; Thermal conductivity ; Anharmonicity ; Condensed matter physics ; Phonon scattering ; Scattering ; Materials science ; Physics ; Thermodynamics ; Optics Thermal properties of materials ; Machine Learning in Materials Science ; Advanced Thermoelectric Materials and Devices
Authors: Ilaria Fratelli | Ralph N. James | William C. Barber | D. Greiffenberg | Sebastian Useche | Juha Kalliopuska | Kohei Toyoda | S.-M Peralva | Maria Pia | Reshma Ughade | Jaime Zabalza | Jinyuan Wu | Makiko Kuwahara | Daisuke Matsukura | Zhong He | A. Castoldi | Anton Khaplanov | Keitaro Hitomi | Matthew J. Martin | M. Petryk | Ana Nobre Silva | Francesco Fallavollita | R. Giordano | K. Hagino | Richard Carson | Marc D. Normandin | Kris Thielemans | Melanie Ganz-Benjaminsen | Ramsey D. Badawi | Anne C. Smith | M. L. Purschke | Jinfu Zhu | Quentin Wingering | Daniel Durini-Romero
Source:  (article, 2023-11-04)
Field: Materials Science — Materials Chemistry

Short Timetable – Table of Content Development of a novel crucible free crystal growth Crucible (geodemography) ; Table (database) ; Computer science ; Content (measure theory) ; Database ; Mathematics ; Chemistry Crystallization and Solubility Studies ; Solidification and crystal growth phenomena ; Crystallography and molecular interactions
Authors: Pawan Kumar | Jiazheng Chen | Andrew C. Meng | Wei‐Chang Yang | Surendra B. Anantharaman | James P. Horwath | Juan Carlos Idrobo | Himani Mishra | Yuanyue Liu | Albert V. Davydov | Eric A. Stach | Deep Jariwala
Source: arXiv (Cornell University) (preprint, 2023-07-11)
Field: Materials Science — Materials Chemistry

Ultra-fast Vacancy Migration: A Novel Approach for Synthesizing Sub-10 nm Crystalline Transition Metal Dichalcogenide Nanocrystals Two-dimensional materials, such as transition metal dichalcogenides (TMDCs), have the potential to revolutionize the field of electronics and photonics due to their unique physical and structural properties. This research presents a novel method for synthesizing crystalline TMDCs crystals with &lt; 10 nm size using ultra-fast migration of vacancies at elevated temperatures. Through in-situ and ex-situ processing and using atomic-level characterization techniques, we analyze the shape, size, crystallinity, composition, and strain distribution of these nanocrystals. These nanocrystals exhibit electronic structure signatures that differ from the 2D bulk i.e., uniform mono and multilayers. Further, our in-situ, vacuum-based synthesis technique allows observation and comparison of defect and phase evolution in these crystals formed under van der Waals heterostructure confinement versus unconfined conditions. Overall, this research demonstrates a solid-state route to synthesizing uniform nanocrystals of TMDCs and lays the foundation for materials science in confined 2D spaces under extreme conditions. Materials science ; Nanocrystal ; Crystallinity ; Nanotechnology ; Heterojunction ; Characterization (materials science) ; Vacancy defect ; van der Waals force ; Transition metal ; In situ ; Chemical physics ; Optoelectronics ; Crystallography ; Molecule ; Chemistry ; Composite material 2D Materials and Applications ; MXene and MAX Phase Materials ; Gas Sensing Nanomaterials and Sensors
Authors: Matthew G. Boebinger | Dündar E. Yılmaz | Ayana Ghosh | Sudhajit Misra | Tyler S. Mathis | Sergei V. Kalinin | Stephen Jesse | Yury Gogotsi | Adri C. T. van Duin | Raymond R. Unocic
Source: arXiv (Cornell University) (preprint, 2023-11-29)
Field: Materials Science — Materials Chemistry

Direct Fabrication of Atomically Defined Pores in MXenes Controlled fabrication of nanopores in atomically thin two-dimensional material offers the means to create robust membranes needed for ion transport, nanofiltration, and DNA sensing. Techniques for creating nanopores have relied upon either plasma etching or direct irradiation using electrons or ions; however, aberration-corrected scanning transmission electron microscopy (STEM) offers the advantage of combining a highly energetic, sub-angstrom sized electron beam for atomic manipulation along with atomic resolution imaging. Here, we utilize a method for automated nanopore fabrication with real-time atomic visualization to enhance our mechanistic understanding of beam-induced transformations. Additionally, an electron beam simulation technique, Electron-Beam Simulator (E-BeamSim) was developed to observe the atomic movements and interactions resulting from electron beam irradiation. Using the 2D MXene Ti3C2Tx, we explore the influence of temperature on nanopore fabrication by tracking atomic transformation pathways and find that at room temperature, electron beam irradiation induces random displacement of atoms and results in a pileup of titanium atoms at the nanopore edge. This pileup was confirmed and demonstrated in E-BeamSim simulations around the small, milled area in the MXene monolayer. At elevated temperatures, the surface functional groups on MXene are effectively removed, and the mobility of atoms increases, which results in atomic transformations that lead to the selective removal of atoms layer by layer. Through controllable manufacture using e-beam milling fabrication, the production and then characterization of the fabricated defects can be better understood for future work. This work can lead to the development of defect engineering techniques within functionalized MXene layers. Nanopore ; Fabrication ; Materials science ; MXenes ; Nanotechnology ; Focused ion beam ; Etching (microfabrication) ; Transmission electron microscopy ; Cathode ray ; Ion beam ; Electron beam processing ; Resist ; Electron-beam lithography ; Scanning electron microscope ; Electron ; Layer (electronics) ; Optoelectronics ; Ion ; Chemistry ; Composite material MXene and MAX Phase Materials ; Advanced biosensing and bioanalysis techniques ; Nanopore and Nanochannel Transport Studies
Authors: Petukhova E.A. | Kharton V.V. | Kveder V.V.
Source: Физика твердого тела (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Memory effects and nonlinear electrical conductivity of doped perovskite-like lanthanum-strontium ferrite, La-=SUB=-0.5-=/SUB=-Sr-=SUB=-0.5-=/SUB=-Fe-=SUB=-0.75-=/SUB=-Al-=SUB=-0.2-=/SUB=-Ni-=SUB=-0.05-=/SUB=-O-=SUB=-3-delta-=/SUB=- Analysis of the existence of memory phenomena in model heterostructures based on doped ferrite La 0.5 Sr 0.5 Fe 0.75 Al 0.2 Ni 0.05 O 3-delta with a perovskite structure has been carried out. It was demonstrated that one 5-10 μm thick ferrite layer sandwiched between Pt and Ni electrodes exhibits an analog memristor behavior. Under positive polarity, this heterostructure shows a smooth increase in electrical conductivity, with an opposite effect under negative polarity. Such phenomena are presumably associated with changing local concentrations of oxygen vacancies due to their drift in the electric field. Since lanthanum-strontium ferrites are sufficiently tolerant with respect to oxygen non-stoichiometry variations, no dendrite growth due to reductive decomposition is observed. The current vs. voltage dependencies display a strong nonlinearity resulting from the Poole--Frenkel effect, namely, a decrease in the activation energy of electron holes trapped on oxygen vacancies. In addition to the Poole--Frenkel effect, pre-exponential factor of the conductivity vs. temperature dependence also increases under electric field, indicating an increase in the effective electron-hole mobility. Keywords: perovskite, lanthanum-strontium ferrites, memory effects, nonlinear electronic transport, memristors. Materials science ; Lanthanum ; Strontium ; Ferrite (magnet) ; Perovskite (structure) ; Electrical resistivity and conductivity ; Conductivity ; Condensed matter physics ; Doping ; Heterojunction ; Lanthanum manganite ; Analytical Chemistry (journal) ; Electrode ; Inorganic chemistry ; Chemistry ; Optoelectronics ; Electrical engineering ; Physical chemistry ; Crystallography ; Composite material ; Physics Phase-change materials and chalcogenides ; Semiconductor materials and interfaces ; Solid-state spectroscopy and crystallography
Authors: Mikhail Tarasov | Przemysław Radwański
Source: Biophysical Journal (article, 2023-02-01)
Field: Chemistry — Electrochemistry

The machine learning pipeline to unravel the functional effects of interactions between sodium channels Gating ; Pipeline (software) ; Sodium channel ; Computer science ; Noise (video) ; Channel (broadcasting) ; Markov chain ; Artificial intelligence ; Chemistry ; Machine learning ; Biological system ; Biophysics ; Biology ; Sodium ; Telecommunications Electrochemical Analysis and Applications ; Advanced Chemical Sensor Technologies ; Fuel Cells and Related Materials
Authors: Florina Ștefania Rus | J. N. Gonçalves
Source: Crystals (article, 2023-09-21)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A Computational Study on Polar ABiO3 (A = Ca, Zn, Mg) Compounds with Large Electric Polarization Bismuth-based oxides with chemical formula ABiO3, where A = Ca, Zn, Mg, have been recently synthesized and suggested to host ferroelectricity. As these materials possess favorable optical properties, the presence of ferroelectricity with large polarization would further enhance the possible applications, for example, in photovoltaics by improving the separation of charge carriers. In this work, first-principles Density Functional Theory (DFT) calculations are performed to study the relative stability of the different polymorphs and to investigate the structural, electronic, and ferroelectric properties. Furthermore, the effect of compressive and tensile in-plane strain on the polarization and electronic properties is also considered. Our study suggests that CaBiO3 should have a large electric polarization (1.8 C/m2) comparable to the one of BiFeO3. Interestingly, the very high polarization appears with only slightly anomalous values of Born effective charges, which would point out a dominant ionic contribution. Our results call for further studies, both from experimental and theoretical sides, to confirm the large electric polarization CaBiO3 predicted in this work. For ZnBiO3 and MgBiO3, we have demonstrated that, up to large values of strain, the perovskite structure retains favorable ferroelectric and electronic (band gap) properties. Ferroelectricity ; Polarization (electrochemistry) ; Materials science ; Density functional theory ; Polarization density ; Condensed matter physics ; Ionic bonding ; Band gap ; Electronic structure ; Chemical physics ; Optoelectronics ; Dielectric ; Chemistry ; Computational chemistry ; Physical chemistry ; Ion ; Physics Multiferroics and related materials ; Ferroelectric and Piezoelectric Materials ; Dielectric properties of ceramics
Authors: Maha A. Younus | Sumayha M. Abbas
Source: Journal of Wasit for Science and Medicine (article, 2023-08-31)
Field: Materials Science — Biomaterials

Synthesis, Characterization and Antimicrobial Study of Polyacetal-Co complex/Nano Chitosan polymer blend Polycyclicacetal was prepared by the reaction of PEG with 4-nitrobenzaldehyde. Cobalt was used for producing a polymer metal complex and solution casting was used to produce a polymer blend including nano chitosan. All produced compounds have been characterized by FT-IR, DSC/ TGA, and SEM techniques as well as biological activity. The production of polyacetal is illustrated by the FT-IR analysis. The DSC/TGA results indicate the prepared polymer blends' thermal stability. Staphylococcus aureas, Klebsiella pneumoniae, Bacillus subtilis, and Escherichia coli were the four types of bacteria selected to study and evaluate the antibacterial activity of produced polyacetal, its metal complex, and polymer blend. Results indicates that there is a greater potential to kill bacteria by increasing the amount of polyacetal-Co complex. Chitosan ; Polymer ; Materials science ; Thermal stability ; Nuclear chemistry ; Casting ; Bacillus subtilis ; Chemical engineering ; Polymer chemistry ; Chemistry ; Bacteria ; Organic chemistry ; Composite material Nanocomposite Films for Food Packaging ; Conducting polymers and applications ; Multicomponent Synthesis of Heterocycles