jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Lionel Petit | Thomas Blon | B. Lassagne
Source: Journal of Applied Physics (article, 2024-12-23)
Field: Materials Science — Materials Chemistry

Quantifying inhomogeneous magnetic fields at the micrometer scale using graphene Hall-effect sensors The response of a graphene Hall-effect sensor to the inhomogeneous magnetic field generated by a dipole located above it is investigated numerically at room temperature as a function of the dipole position and orientation and as a function of the sensor conduction regime, i.e., diffusive or ballistic. By means of dedicated models, we highlight that the correction factor α frequently used to relate the Hall voltage to the magnetic field averaged over the sensor area can be greatly improved in the high proximity situation enabled by the use of graphene, particularly in the ballistic regime. In addition, it is demonstrated that by fine-tuning the dipole position in the sensor plane, the Hall response becomes highly selective with respect to the dipole orientation. These analyses show that diffusive graphene Hall sensors may be preferred for particle detection, while ballistic ones used as close as possible to a nanomagnet would be preferred for magnetometry. Then, with the help of micromagnetic simulations, the principle of measuring the magnetic hysteresis loop of an isolated nanomagnet with a ballistic Hall sensor is investigated. A large signal-to-noise ratio is demonstrated, which allows for effective probing of magnetization reversal. This shows that devices based on specially designed ballistic graphene Hall crosses promise to outperform state-of-the-art ballistic Hall sensors based on semiconductor quantum wells or micro-SQUID, especially for nano-magnetometry. Nanomagnet ; Hall effect sensor ; Condensed matter physics ; Hall effect ; Graphene ; Magnetometer ; Magnetic field ; Physics ; Ballistic conduction ; Quantum Hall effect ; Magnetic dipole ; Dipole ; Magnetization ; Materials science ; Magnet ; Electron ; Quantum mechanics Graphene research and applications ; Magnetic Field Sensors Techniques ; Quantum and electron transport phenomena
Authors: Bogdan G. Nita | Raluca Tampu | Cătălin Tâmpu | Bogdan Chiriță | Eugen Herghelegiu | Carol Schnakovszky
Source: Journal of Manufacturing and Materials Processing (article, 2024-08-24)
Field: Materials Science — Materials Chemistry

Review Regarding the Influence of Cryogenic Milling on Materials Used in the Aerospace Industry In the aerospace industry, an important number of machined parts are submitted for high-performance requirements regarding surface integrity. Key components are made of materials selected for their unique properties and they are obtained by milling processes. In most situations, the milling process uses cooling methods because, in their absence, the material surface could be affected by the generated heat (temperatures could reach up to 850 °C), the residual stress, the cutting forces, and other factors that can lead to bad integrity. Cryogenic cooling has emerged as a pivotal technology in the manufacturing of aeronautical materials, offering enhanced properties and efficiency in the production process. By utilizing extremely low temperatures, typically involving liquid nitrogen or carbon dioxide, cryogenic cooling can significantly enhance the material’s properties and machining processes. Cryogenic gases are tasteless, odorless, colorless, and nontoxic, and they evaporate without affecting the workers’ health or producing residues. Thus, cryogenic cooling is also considered an environmentally friendly method. This paper presents the advantages of cryogenic cooling compared with the classic cooling systems used industrially. Improvements in terms of surface finishing, tool life, and cutting force are highlighted. Aerospace ; Manufacturing engineering ; Materials science ; Engineering ; Aerospace engineering Metal Alloys Wear and Properties ; Engineering and Environmental Studies ; Advanced machining processes and optimization
Authors: David De Vocht | Alonso Millan Mejia | Angel Savov | Yuqing Jiao | E.A.J.M. Bente
Source: Optics Express (article, 2024-12-06)
Field: Materials Science — Surfaces, Coatings and Films

Dual focus wavefront tilting silicon nitride-based metalenses manufactured using deep-ultraviolet scanner lithography We present a dual focus wavefront tilting metalens, a lens of a few micrometers thick that compensates for incidence angles of ±5° and focuses them to the same target. The metalens comprises an array of Si<sub>3</sub>N<sub>4</sub> nanopillars. We manufactured the metalens using 193 nm deep-ultraviolet scanner lithography, suitable for high-volume manufacturing. Using this metalens, we demonstrate a proof-of-concept for chip-to-free-space coupling by directing light from one fibre collimator at +5° towards a mirror and recoupling this light into another fibre collimator at -5°. The metalens achieved a focusing efficiency of 9.4%. This efficiency has the potential to be improved to 64%. The metalens can be integrated into photonic circuits for enhanced coupling with distant objects. This work paves the way for further miniaturization of gas and metrology sensors. Optics ; Scanner ; Lithography ; Materials science ; Extreme ultraviolet lithography ; Focus (optics) ; Wavefront ; Ultraviolet ; Silicon nitride ; X-ray lithography ; Optoelectronics ; Silicon ; Physics ; Resist ; Nanotechnology Optical Coatings and Gratings ; Photonic and Optical Devices ; Photonic Crystals and Applications
Authors: Muhammad Sufyan Ramzan | Caterina Cocchi
Source: physica status solidi (RRL) - Rapid Research Letters (article, 2024-11-17)
Field: Materials Science — Materials Chemistry

Strain‐Engineered Level Alignment in the MoTe<sub>2</sub>/WSe<sub>2</sub> Heterobilayer When stacked into heterostructures, layered transition metal dichalcogenides (TMDCs) exhibit peculiar electronic and optical properties that may differ substantially from those of their constituents and that largely depend on the level alignment. For example, the MoTe 2 /WSe 2 heterobilayer exhibits a type I band lineup, which can be exploited in emitting devices but limits charge separation. In this first‐principle study based on density functional theory and many‐body perturbation theory, strain is proposed as an effective means to make MoTe 2 /WSe 2 a type II heterostructure. By exploring several configurations where biaxial strain is applied to either or both monolayers, the top of the valence band and the bottom of the conduction band are found at different points in k‐space leading to an indirect‐to‐direct bandgap transition when the lattice constant of WSe 2 is expanded by 3.2% or more. In terms of optical properties, all considered systems exhibit a first dark excitation, consistently shifting in energy with the direct electronic gap, while the absorption onset does not vary significantly with strain. Our findings suggest strain as a powerful tool for fine tuning the electronic and optical properties of TMDC heterostructures while preserving their fundamental characteristics, thus opening new avenues for designing optoelectronic applications. Strain (injury) ; Materials science ; Biology ; Anatomy 2D Materials and Applications ; MXene and MAX Phase Materials ; Advanced Photocatalysis Techniques
Authors: Jixiang Yang | Xiaoyan Shi | Shenyong Ye | Chiho Yoon | Zhengguang Lu | Vivek Kakani | Tonghang Han | Junseok Seo | Lihan Shi | Kenji Watanabe | Takashi Taniguchi | Fan Zhang | Long Ju
Source: arXiv (Cornell University) (preprint, 2024-08-19)
Field: Materials Science — Materials Chemistry

Impact of Spin-Orbit Coupling on Superconductivity in Rhombohedral Graphene Spin-orbit coupling (SOC) has played an important role in many topological and correlated electron materials. In graphene-based systems, SOC induced by transition metal dichalcogenide (TMD) at proximity was shown to drive topological states and strengthen superconductivity. However, in rhombohedral multilayer graphene, a robust platform for electron correlation and topology, superconductivity and the role of SOC remain largely unexplored. Here we report transport measurements of TMD-proximitized rhombohedral trilayer graphene (RTG). We observed a new hole-doped superconducting state SC4 with Tc = 230 mK. On the electron-doped side, we identified a new isospin-symmetry breaking three-quarter-metal (TQM) phase and observed the nearby weak superconducting state SC3 is significantly enhanced. Surprisingly, the original superconducting state SC1 in bare RTG is strongly suppressed in the presence of TMD - opposite to the effect of SOC on all other graphene superconductivities. Our observations form the basis of exploring superconductivity and non-Abelian quasiparticles in rhombohedral graphene devices. Superconductivity ; Graphene ; Condensed matter physics ; Trigonal crystal system ; Coupling (piping) ; Spin–orbit interaction ; Orbit (dynamics) ; Spin (aerodynamics) ; Physics ; Materials science ; Quantum mechanics ; Chemistry ; Aerospace engineering ; Engineering ; Crystallography ; Metallurgy ; Crystal structure Graphene research and applications ; Quantum and electron transport phenomena ; Physics of Superconductivity and Magnetism
Authors: Amirreza Dana | L. Mu | Simon Gelin | Susan B. Sinnott | Ismaïla Dabo
Source: Computational Materials Science (article, 2024-05-15)
Field: Materials Science — Materials Chemistry

Cluster expansion by transfer learning for phase stability predictions Stability (learning theory) ; Cluster (spacecraft) ; Convergence (economics) ; Computer science ; Cluster expansion ; Bayesian probability ; Inference ; Bayesian inference ; Phase (matter) ; Statistical physics ; Dimension (graph theory) ; Machine learning ; Artificial intelligence ; Physics ; Mathematics ; Thermodynamics Machine Learning in Materials Science ; nanoparticles nucleation surface interactions ; Advanced Materials Characterization Techniques
Authors: Yonggang Cheng | Pedro S.F. Mendes | Parviz Yazdani | Joris Thybaut
Source: International Journal of Chemical Kinetics (article, 2024-07-03)
Field: Materials Science — Materials Chemistry

Microkinetic analysis of the CO<sub>2</sub> effect on OCM over a La‐Sr/CaO catalyst Abstract Given its role as a primary side product and a potential soft oxidant in the oxidative coupling of methane (OCM), understanding the effect of CO 2 co‐feeding on OCM emerges as a key milestone to optimize the process. To grasp the molecular impact of CO 2 , a mechanistic investigation over a La‐Sr/CaO catalyst was carried out via microkinetic modeling. Seven catalyst descriptors with a precise physico‐chemical meaning were regressed for both pure O 2 and CO 2 co‐feeding in order to assess eventual structural changes induced in the catalyst by the presence of CO 2 in the feed. Global significance was achieved in both regressions and experimental trends were successfully reproduced by the specifically determined catalyst descriptors. CO 2 co‐feeding is deemed responsible for generating a new active phase, for example, by converting metal oxides into (oxy‐)carbonates, among others, resulting in a decrease in active site density (D 16 ) from 10 × 10 −5 mol/m 2 to 7 × 10 −5 mol/m 2 . In the presence of the CO 2 ‐induced phase, the catalyst exhibits higher attraction for unsaturated hydrocarbons as indicated by the higher initial sticking probabilities of CH 3 • (D 11 ) and C 2 H 4 (D 15 ), which increase from 4.9 × 10 −4 to 8 × 10 −2 and from 2.1 × 10 −2 to 3 × 10 −2 , respectively. Additionally, there are also lower the overall energy barriers for the activation of hydrocarbons on the catalyst, stemming from the decrease in the H abstraction enthalpy from CH 4 (D 1 ) from 14 to 6 kJ/mol. The operating conditions, in particular the O 2 content, are critical in distinguishing the effect of CO 2 co‐feeding. While at typical operating conditions, CO 2 promotes the total oxidation of methane, in the prerequisite of reduced amount of O 2 , it may also act as an additional oxygen donor. This work provides molecular details on the CO 2 induced changes in catalyst properties but also provides unprecedent quantified insights of the reaction mechanism underlying experimental observations. Chemistry ; Catalysis ; Nuclear chemistry ; Chemical engineering ; Physical chemistry ; Organic chemistry Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions ; Catalysts for Methane Reforming
Authors: Yongkang Xie | Xiaping Fu
Source: Journal of Food Safety (article, 2024-12-01)
Field: Chemistry — Analytical Chemistry

Quality Detection of Fresh‐Cut Pineapples During Cold Storage Based on Diffuse Reflectance and Fluorescence Hyperspectral Imaging Technique ABSTRACT The fresh‐cut fruits and vegetables industry has developed rapidly in recent years, with pineapple being a popular fruit. The quality of pineapple plays a crucial role in determining its market value. This research explored the potential of diffuse reflectance hyperspectral imaging (HSI) and fluorescence hyperspectral imaging (FHSI) in monitoring L*a*b*, pH, and soluble solids content (SSC) of fresh‐cut pineapples during cold storage. Fresh‐cut pineapples were stored at a temperature of 4°C for 0–5 days, with daily acquisition of diffuse reflectance and fluorescence hyperspectral images at 380–1000 nm, along with measurement of quality indices. Changes in spectral properties and quality indices during cold storage were analyzed. Seven preprocessing algorithms were used to preprocess two types of spectra. Subsequently, five feature selection methods were employed to extract feature variables from the preprocessed spectra. The Partial Least Squares Regression (PLSR) models were constructed to predict the various quality indices. Data fusion methods were introduced to leverage the complementary information from different spectra. Both feature‐level and decision‐level fusion methods demonstrated improvement in model accuracy. The hybrid fusion method, combining the advantages of these two fusion methods, effectively enhanced the prediction accuracy of all quality indices. The determination coefficients ( R 2 ) for predicting L*a*b* consistently exceeded 0.8, while the R 2 for predicting pH was close to 0.8, and the R 2 for predicting SSC reached 0.91. In summary, the quality indices of fresh‐cut pineapples can be accurately predicted using diffuse reflectance HSI and FHSI, with model accuracy further enhanced through multi‐level data fusion methods. Hyperspectral imaging ; Fluorescence ; Reflectivity ; Remote sensing ; Diffuse reflection ; Quality (philosophy) ; Materials science ; Chemistry ; Optics ; Geology ; Physics Spectroscopy and Chemometric Analyses ; Date Palm Research Studies ; Identification and Quantification in Food
Authors: J. Scott P. McCain | Gregory L. Britten | Sean R. Hackett | Michael J. Follows | Gene‐Wei Li
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2024-08-16)
Field: Chemistry — Spectroscopy

Microbial reaction rate estimation using proteins and proteomes Microbes transform their environments using diverse enzymatic reactions. However, it remains challenging to measure microbial reaction rates in natural environments. Despite advances in global quantification of enzyme abundances, the individual relationships between enzyme abundances and their reaction rates have not been systematically examined. Using matched proteomic and reaction rate data from microbial cultures, we show that enzyme abundance is often insufficient to predict its corresponding reaction rate. However, we discovered that global proteomic measurements can be used to make accurate rate predictions of individual reaction rates (median <i>R</i> <sup><i>2</i></sup> = 0.78). Accurate rate predictions required only a small number of proteins and they did not need explicit prior mechanistic knowledge or environmental context. These results indicate that proteomes are encoders of cellular reaction rates, potentially enabling proteomic measurements <i>in situ</i> to estimate the rates of microbially mediated reactions in natural systems. Proteome ; Context (archaeology) ; Reaction rate ; Abundance (ecology) ; Computational biology ; Biology ; Biological system ; Biochemical engineering ; Ecology ; Bioinformatics ; Biochemistry Advanced Proteomics Techniques and Applications ; Bioinformatics and Genomic Networks ; Microbial Metabolic Engineering and Bioproduction
Authors: Pronit Biswas | Juli Jain | Whidul Hasan | Devasish Bose | Rajesh Singh Yadav
Source: Toxicology Research (article, 2024-11-05)
Field: Chemistry — Analytical Chemistry

Biochemical Alterations and Motor Dysfunctions in Corpus Striatum of Rats Brain Exposed to Azo Dyes Azo food dyes are prohibited in most countries, but their injudicious use is still reported particularly in the developing Nations. Continuous use of contaminated food raises health concerns and given this the present study designed to investigate the effects of 3 non-permitted azo dyes (metanil yellow - MY, malachite green - MG, and sudan III - SIII) on neurobehavioral, neurochemicals, mitochondrial dysfunction, oxidative stress, and histopathological changes in the corpus striatum of rats. Rats were grouped and treated with MY (430 mg/kg), MG (13.75 mg/kg), SIII (250 mg/kg) & mixture (YGR) (MY 143.33 + MG 4.52 + SIII 83.33 mg/kg) p.o. for 60 days showed a significant decrease in grip strength and motor activity, the activity of acetylcholinesterase (AChE), monoamine oxidase - B (MAO-B), and mitochondrial complex I and II compared to the control. The treated groups showed a significant increase in lipid peroxidation and a decrease in the level of reduced glutathione, superoxide dismutase, and catalase as compared to the control. Histopathology of the corpus striatum revealed immense damage. Data from the present study correlate between azo dyes and changes in the behavior of rats which have been associated with the altered biochemicals and neurochemicals activities. In conclusion, exposure to azo dyes caused neurotoxicity involving motor impairments associated with enhanced oxidative stress, mitochondrial dysfunctions, AChE and MAO-B inhibition, and neuronal damage in the corpus striatum of rats. Striatum ; Oxidative stress ; Catalase ; Monoamine oxidase ; Superoxide dismutase ; Acetylcholinesterase ; Neurotoxicity ; Lipid peroxidation ; Chemistry ; Aché ; Biochemistry ; Internal medicine ; Endocrinology ; Pharmacology ; Toxicity ; Dopamine ; Medicine ; Enzyme Dye analysis and toxicity ; Medicinal Plants and Neuroprotection ; Heavy Metal Exposure and Toxicity
Authors: Andrew I. Cooper
Source: Faraday Discussions (article, 2024-11-04)
Field: Materials Science — Materials Chemistry

Concluding remarks: <i>Faraday Discussion</i> on data-driven discovery in the chemical sciences This <i>Faraday Discussion</i> was the first to focus on the increasingly central role of big data, machine learning, and artificial intelligence in the chemical sciences. The aim was to critically discuss these topics, and to explore the question of how data can enable new discoveries in chemistry, both now and in the future. The programme spanned computational and experimental work, and encompassed emerging topics such as natural language processing, machine-learned potentials, optimization strategies, and robotics and self-driving laboratories. Here I provide some brief introductory comments on the history of this field, along with some personal views on the discussion topics covered, concluding with three future challenges for this area. Epistemology ; Philosophy Machine Learning in Materials Science ; History and advancements in chemistry ; Scientific Computing and Data Management
Authors: Fuzhan Rahmanian | Stefan Fuchs | Maximilian Fichtner | Helge S. Stein
Source: ChemRxiv (preprint, 2024-01-02)
Field: Materials Science — Materials Chemistry

Autonomous millimeter scale high throughput battery research system (Auto-MISCHBARES) Discoveries of novel electrolyte-electrode combinations require comprehensive structure-property-interface correlations. Herein, we present an autonomous millimeter scale high-throughput battery research system (MISCHBARES) operated by hierarchical autonomous laboratory automation and orchestration (HELAO) which integrates modular research instrumentation and AI control. This paper will present cathode electrolyte interphase (CEI) formation in lithium-ion batteries at various potentials by correlating high-throughput electrochemistry and spectroscopy. We believe quality control and complex data analysis to be the missing puzzle piece towards more complex workflow automation. Auto-MISCHBARES integrates automatic quality control for both hardware and software to ensure high reliability through an on-the-fly fidelity assessment of each individual experiment. Data analysis is achieved through our Modular and Autonomous Data Analysis Platform (MADAP) in our presented platform, which is capable of performing a fully automated analysis of various voltammetry measurements in real-time. Integration of MISCHBARES and MADAP through HELAO enables versatile and complex active learning workflows in the discovery of new materials. We demonstrate this integrated workflow for reliable charging/discharging protocols. Workflow ; Modular design ; Throughput ; Automation ; Computer science ; Interface (matter) ; Battery (electricity) ; Orchestration ; Software ; Laboratory automation ; Plug and play ; Instrumentation (computer programming) ; Embedded system ; Engineering ; Operating system ; Database Machine Learning in Materials Science ; Machine Learning and Algorithms ; Fault Detection and Control Systems
Authors: Fuzhan Rahmanian | Stefan Fuchs | Maximilian Fichtner | Helge S. Stein
Source: ChemRxiv (preprint, 2024-01-08)
Field: Materials Science — Materials Chemistry

Autonomous millimeter scale high throughput battery research system (Auto-MISCHBARES) Discoveries of novel electrolyte-electrode combinations require comprehensive structure-property-interface correlations. Herein, we present an autonomous millimeter scale high-throughput battery research system (MISCHBARES) operated by hierarchical autonomous laboratory automation and orchestration (HELAO) which integrates modular research instrumentation and AI control. This paper will present cathode electrolyte interphase (CEI) formation in lithium-ion batteries at various potentials by correlating high-throughput electrochemistry and spectroscopy. We believe quality control and complex data analysis to be the missing puzzle piece towards more complex workflow automation. Auto-MISCHBARES integrates automatic quality control for both hardware and software to ensure high reliability through an on-the-fly fidelity assessment of each individual experiment. Data analysis is achieved through our Modular and Autonomous Data Analysis Platform (MADAP) in our presented platform, which is capable of performing a fully automated analysis of various voltammetry measurements in real-time. Integration of MISCHBARES and MADAP through HELAO enables versatile and complex active learning workflows in the discovery of new materials. We demonstrate this integrated workflow for reliable charging/discharging protocols. Workflow ; Automation ; Modular design ; Throughput ; Computer science ; Interface (matter) ; Battery (electricity) ; Orchestration ; Software ; Laboratory automation ; Plug and play ; Embedded system ; Instrumentation (computer programming) ; Engineering ; Operating system ; Database ; Bubble Machine Learning in Materials Science ; Machine Learning and Algorithms ; Fault Detection and Control Systems