jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Marcelo Augusto Malagutti | Ketan Lohani | Mirco D’Incau | Himanshu Nautiyal | Narges Ataollahi | Paolo Scardi
Source: Applied Sciences (article, 2023-09-10)
Field: Materials Science — Materials Chemistry

Optimizing CuFeS2 Chalcopyrite Thin Film Synthesis: A Comprehensive Three-Step Approach Using Ball-Milling, Thermal Evaporation, and Sulfurization Applied for Thermoelectric Generation CuFeS2 (CFS) stands out as a promising narrow band-gap semiconductor for thermoelectric (TE) applications. However, its high lattice thermal conductivity is one of the factors hampering its potential for TE generation. A common strategy for tackling this problem is to produce this material in thin film form. Thus, this study aims to practically understand and optimize the synthesis of CFS 2D materials using a simple three-step approach of ball-milling, thermal evaporation, and sulfurization of the CuFe metallic precursors. The tools for thin film characterization employ X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Energy-Dispersive X-ray Spectroscopy (EDXS), and Hall-effect measurements. DFT phase diagrams are also used to understand the energy of formation of the secondary phases present in the film. Here, we highlight that the ball-milling mechanisms, allied with high vacuum and high energy density during evaporation, are essential for the interdiffusion of Cu and Fe during the evaporation process. The film presented a flower-like morphology and p-type semiconducting behavior. A proof-of-concept Thermoelectric Generator (TEG) was designed in an in-plane geometry, showing a power output per unit active area of 114 nW cm−2 (ΔT = 180 °C), comparable to other Cu-based materials, thus demonstrating the feasibility of this method of synthesis for TE applications. Materials science ; Ball mill ; Thermoelectric generator ; Thermoelectric effect ; Thin film ; Chalcopyrite ; Scanning electron microscope ; Chemical engineering ; Semiconductor ; Thermoelectric materials ; Optoelectronics ; Thermal conductivity ; Metallurgy ; Nanotechnology ; Composite material ; Thermodynamics Advanced Thermoelectric Materials and Devices ; Chalcogenide Semiconductor Thin Films ; Quantum Dots Synthesis And Properties
Authors: Rui Zhang | Xinlei Gu | Kan Zhang | Xinxin Gao | Chang Liu | Changfeng Chen
Source: Advanced Materials (article, 2023-07-17)
Field: Materials Science — Materials Chemistry

Core Electron Count as a Versatile and Accurate New Descriptor for Sorting Mechanical Properties of Diverse Transition Metal Compounds Transition-metal light-element compounds show superb mechanical, chemical, and thermal properties, and accurate descriptors are important to sorting targeted properties among this vast class of materials. Valence electron concentration (VEC) can track broad trends of mechanical properties, but this widely used descriptor suffers low accuracy with sorted data strongly scattered along trendlines, necessitating an improved sorting strategy. Here, elastic parameters from first-principles calculations are examined for 81 ternary transition-metal nitrides (TMN) in cubic structure and 81 ternary transition-metal diborides (TMB<sub>2</sub> ) in hexagonal structure and identify core electron count (CEC) of the solvent atoms as a new descriptor. Combined with VEC, the composite VEC-CEC descriptor exhibits greatly improved ability to sort elastic parameters of distinct TMN and TMB<sub>2</sub> compounds. Unregulated property variations under the VEC description are well-captured by CEC, which tends to enhance ductility and reduce strength at fixed VEC and rising CEC. By invoking a full-electron consideration, the VEC-CEC descriptor accounts for the impact on bonding behaviors by both core and valence electrons with much-improved accuracy and versatility in sorting mechanical properties of diverse TM compounds compared to many other commonly used descriptors, opening a fresh path for rational design and optimization of TM compounds with tailored performance benchmarks. Materials science ; Sorting ; Core (optical fiber) ; Transition metal ; Nanotechnology ; Chemical physics ; Electron ; Composite material ; Computer science ; Organic chemistry ; Catalysis ; Nuclear physics Boron and Carbon Nanomaterials Research ; Intermetallics and Advanced Alloy Properties ; Metal and Thin Film Mechanics
Authors: Prashant Singh | Dongjoon Rhee | Sungpyo Baek | Hyun Ho Yoo | Jingjie Niu | Myeongjin Jung | Joohoon Kang | Sungjoo Lee
Source: EcoMat (article, 2023-02-14)
Field: Materials Science — Materials Chemistry

<scp>SnS</scp>/<scp>MoS<sub>2</sub></scp> van der Waals heterojunction for <scp>in‐plane</scp> ferroelectric <scp>field‐effect</scp> transistors with multibit memory and logic characteristics Abstract Ferroelectric two dimensional (2D) materials hold great potential to develop modern miniaturized electronic and memory devices. 2D ferroelectrics exhibiting spontaneous polarization in the out‐of‐plane direction have been extensively investigated to date, but the loss of their polarization during device operation has been problematic. Although 2D materials with in‐plane ferroelectric behavior are more stable against depolarization and thus promising for memory and logic applications, experimental realization of in‐plane 2D ferroelectric devices is still scarce. Here, we demonstrate in‐plane ferroelectric field effect transistors (FETs) based on a van der Waals heterojunction (vdWHJ), which can perform multibit memory and logic operations. Tin monosulfide (SnS), a 2D material with in‐plane ferroelectricity, is partially stacked on top of a semiconducting molybdenum disulfide (MoS2) on a silicon dioxide (SiO2)‐coated silicon substrate to fabricate vdWHJ FETs in back‐gate configuration. Switching of the in‐plane polarization direction in the SnS channel modulates the contact barriers at the electrode/SnS and SnS/MoS2 interfaces, thereby creating high resistance states and low resistance states (LRS). The device exhibits a logic transfer characteristic with a high drain current on/off ratio (&gt;106) in LRS and non‐volatile memory performance with excellent retention characteristics (extrapolated retention time &gt; 10 years). With exquisite tuning of the channel resistance by SnS polarization and gate bias, we realize multiple states with distinct current levels for multibit memory and logic operations suitable for programmable logic‐in‐memory applications. image Ferroelectricity ; Non-volatile memory ; Materials science ; Optoelectronics ; Polarization (electrochemistry) ; Heterojunction ; Field-effect transistor ; JFET ; Transistor ; Nanotechnology ; Electrical engineering ; Voltage ; Dielectric ; Chemistry ; Engineering 2D Materials and Applications ; Perovskite Materials and Applications ; Ferroelectric and Negative Capacitance Devices
Authors: Souvik Mandal | Chantal Daniel
Source: Physical Chemistry Chemical Physics (article, 2023-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Spin–vibronic mechanism at work in a luminescent square-planar cyclometalated tridentate Pt(<scp>ii</scp>) complex: absorption and ultrafast photophysics The absorption spectrum of [Pt(dpybMe)Cl] (dpyb = 2,6-di-(2-pyridyl)benzene), representative of luminescent halide-substituted tridentate cyclometalated square planar Pt(II) neutral complexes, has been revisited by means of non-adiabatic wavepacket quantum dynamics. The early photophysics has been investigated on the basis of four singlet and five triplet excited states, namely nineteen "spin-orbit states", coupled with both vibronic and spin-orbit couplings, and includes eighteen normal modes. It is shown that in-plane scissoring and rocking normal modes of the cyclometalated tridentate ligand are responsible for the vibronic structure observed at around 400 nm in the experimental spectrum of the complex. The ultrafast decay of [Pt(dpybMe)Cl], within 1 ps, follows a spin-vibronic mechanism governed by excited state electronic characters, spin-orbit, and active tuning mode interplay. Both spin-orbit coupling and Pt(II) coordination sphere stretching modes and in-plane scissoring/rocking of the cyclometalated ligand activate the ultrafast decay within 20 fs of absorption. At longer time-scales (>100 fs) an asynchronous stretching of the Pt-C and Pt-N bonds activates the depopulation of the upper "reservoir" electronic states to populate the two lowest luminescent T1 and T2 electronic states. The in-plane rocking motion of the ligand controls the T1/T2 population exchange which is equilibrated at about 1 ps. Stabilization of the upper non-radiative metal-centered (MC) states by out-of-plane ligand distortion of low frequency is not competitive with the ultrafast spin-vibronic mechanism discovered here for [Pt(dpybMe)Cl]. Modifying the Pt-C covalent bond position and rigidifying the cyclometalated ligand will have a dramatic influence on the spin-vibronic mechanism and consequently on the luminescence properties of this class of molecules. Luminescence ; Ultrashort pulse ; Planar ; Absorption (acoustics) ; Photochemistry ; Spin (aerodynamics) ; Work (physics) ; Chemistry ; Square (algebra) ; Materials science ; Chemical physics ; Molecular physics ; Optoelectronics ; Physics ; Optics ; Quantum mechanics ; Laser ; Computer science Magnetism in coordination complexes ; Organic Light-Emitting Diodes Research ; Lanthanide and Transition Metal Complexes
Authors: Yun Wang | Jia Jia | Jie Zhang | Ruixue Xiao | Wenjia Xu | Yuhua Feng
Source: Small (article, 2023-04-13)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Modulating the Charge Transfer Plasmon in Bridged Au Core‐Satellite Homometallic Nanostructures Abstract The localized surface plasmon resonance (LSPR) is one of the important properties for noble metal nanoparticles. Tuning the LSPR on demand thus has attracted tremendous interest. Beyond the size and shape control, manipulating intraparticle coupling is an effective way to tailor their LSPR. The charge transfer plasmon (CTP) is the most important mode of conductive coupling between subunits linked by conductive bridges that are well studied for structures prepared on substrates by lithography method. However, the colloidal synthesis of CTP structure remains a great challenge. This work reports the colloidal synthesis of extraordinary bridged Au core‐satellite structures by exploiting the buffer effect of polydopamine shell on Au core for Au atom diffusion, in which the Au bridge is well controlled in terms of width and length. Benefiting from the tunable Au bridges, the resonance energy of the CTP can be readily controlled. As a result, the LSPR absorptions of the core‐satellite structures are continuously tuned within the NIR spectral range (from 900 to &gt;1300 nm), demonstrating their great potentials for ultrafast nano‐optics and biomedical applications. Surface plasmon resonance ; Materials science ; Nanotechnology ; Nanoparticle ; Plasmon ; Nanostructure ; Localized surface plasmon ; Optoelectronics Gold and Silver Nanoparticles Synthesis and Applications ; Plasmonic and Surface Plasmon Research ; Quantum Dots Synthesis And Properties
Authors: Yanting Guo | Trishika Chowdhury | Meena Seshadri | Kellye A. Cupp‐Sutton | Qingyu Wang | Dahang Yu | Si Wu
Source: Journal of Proteome Research (article, 2023-01-05)
Field: Chemistry — Spectroscopy

Optimization of Higher-Energy Collisional Dissociation Fragmentation Energy for Intact Protein-Level Tandem Mass Tag Labeling Isobaric chemical tag labeling (e.g., TMT) is a commonly used approach in quantitative proteomics, and quantification is enabled through detection of low-mass reporter ions generated after MS2 fragmentation. Recently, we have introduced and optimized an intact protein-level TMT labeling platform that demonstrated >90% labeling efficiency in complex samples with top-down proteomics. Higher-energy collisional dissociation (HCD) is commonly utilized for isobaric tag-labeled peptide fragmentation because it produces accurate reporter ion intensities and avoids loss of low mass ions. HCD energies have been optimized for isobaric tag labeled-peptides but have not been systematically evaluated for isobaric tag-labeled intact proteins. In this study, we report a systematic evaluation of normalized HCD fragmentation energies (NCEs) on TMT-labeled HeLa cell lysate using top-down proteomics. Our results suggested that reporter ions often result in higher ion intensities at higher NCEs. Optimal fragmentation of intact proteins for identification, however, required relatively lower NCE. We further demonstrated that a stepped NCE scheme with energies from 30% to 50% resulted in optimal quantification and identification of TMT-labeled HeLa proteins. These parameters resulted in an average reporter ion intensity of ∼4E4 and average proteoform spectrum matches (PrSMs) of >1000 per RPLC-MS/MS run with a 1% false discovery rate (FDR) cutoff. Fragmentation (computing) ; Chemistry ; Tandem mass tag ; Quantitative proteomics ; Isobaric labeling ; Mass spectrometry ; Tandem mass spectrometry ; Ion ; Isobaric process ; Proteomics ; Dissociation (chemistry) ; Collision-induced dissociation ; Analytical Chemistry (journal) ; Chromatography ; Protein mass spectrometry ; Biochemistry ; Physics ; Biology Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Biosensors and Analytical Detection
Authors: Suman Jyoti De | Ankur Das | Sumathi Rao | Ribhu K. Kaul | Ganpathy Murthy
Source: Physical review. B./Physical review. B (article, 2023-03-27)
Field: Materials Science — Materials Chemistry

Global phase diagram of charge-neutral graphene in the quantum Hall regime for generic interactions Monolayer graphene at charge neutrality in a quantizing magnetic field is a quantum Hall ferromagnet. Due to the spin and valley (near) degeneracies, there is a plethora of possible ground states. Previous theoretical work, based on a stringent ultra-short-range assumption on the symmetry-allowed interactions, predicts a phase diagram with distinct regions of spin-polarized, canted antiferromagnetic, intervalley coherent, and charge density wave order. While early experiments suggested that the system was in the canted antiferromagnetic phase at a perpendicular field, recent scanning tunneling studies universally find Kekul\'e bond order, and sometimes also charge density wave order. Recently, it was found that if one relaxes the stringent assumption mentioned above a phase with coexisting canted antiferromagnetic and Kekul\'e order exists in the region of the phase diagram believed to correspond to real samples. In this paper, starting from the continuum limit appropriate for experiments, we present the complete phase diagram of $\ensuremath{\nu}=0$ graphene in the Hartree-Fock approximation, using generic symmetry-allowed interactions, assuming translation-invariant ground states up to an intervalley coherence. Allowing for a sublattice potential (valley Zeeman coupling), we find numerous phases with different types of coexisting order. We conclude with a discussion of the physical signatures of the various states. Physics ; Condensed matter physics ; Phase diagram ; Antiferromagnetism ; Charge (physics) ; Quantum mechanics ; Zeeman effect ; Magnetic field ; Phase (matter) Graphene research and applications ; Quantum and electron transport phenomena ; Topological Materials and Phenomena
Authors: Stefan Ernst | Patrick Scheidegger | S. Diesch | Christian L. Degen
Source: Physical review. B./Physical review. B (article, 2023-08-24)
Field: Materials Science — Materials Chemistry

Modeling temperature-dependent population dynamics in the excited state of the nitrogen-vacancy center in diamond The nitrogen vacancy (NV) center in diamond is well known for its outstanding optical and spin properties, enabling various applications in quantum sensing and quantum information at both cryogenic and ambient temperatures. Despite a large body of work, however, the NV center's dynamics at intermediate temperatures are incompletely understood. This paper describes a basic rate model able to explain the NV population dynamics over the full parameter space of temperature, crystallographic strain, and magnetic field. Numerical simulations of the model are in excellent agreement with experiments discussed in the accompanying PRL. Diamond ; Excited state ; Nitrogen-vacancy center ; Vacancy defect ; Population ; Atomic physics ; Condensed matter physics ; Materials science ; Spin (aerodynamics) ; Work (physics) ; Quantum ; Dynamics (music) ; Center (category theory) ; Physics ; Quantum mechanics ; Thermodynamics ; Chemistry Diamond and Carbon-based Materials Research ; High-pressure geophysics and materials ; Metal and Thin Film Mechanics
Authors: Kamran-ul-Haq Khan | Suhaib Masroor | Ghaus Rizvi
Source: Journal of Polymer Engineering (article, 2023-06-26)
Field: Materials Science — Biomaterials

Electrospinning and electrospun based polyvinyl alcohol nanofibers utilized as filters and sensors in the real world Abstract Electrospinning is a contemporary and effective technique for producing fine fibers with diameters as small as nanometers by using an electric field. These fibers have numerous industrial applications, including filtration, sensors, composite materials, and membranes. This study provides an overview of the electrospinning process and discusses a few applications of polyvinyl alcohol based electrospun nanofibers in the development of filters and sensors. Electrospinning ; Polyvinyl alcohol ; Materials science ; Nanofiber ; Nanometre ; Filtration (mathematics) ; Composite material ; Membrane ; Composite number ; Fiber ; Nanotechnology ; Polymer Electrospun Nanofibers in Biomedical Applications ; Advanced Sensor and Energy Harvesting Materials ; Conducting polymers and applications
Authors: Kimberly L. Bassett | Tylan Watkins | Jonathan Coleman | Nathan Bianco | Lauren S. Bailey | Jamin Ryan Pillars | Samuel Garrett Williams | Tomas F. Babuska | John F. Curry | Frank W. DelRio‬ | Amelia Henriksen | Anthony Garland | Justin Hall | Brandon A. Krick | Brad Boyce
Source: Integrating materials and manufacturing innovation (article, 2023-10-26)
Field: Materials Science — Materials Chemistry

A Workflow for Accelerating Multimodal Data Collection for Electrodeposited Films Abstract Future machine learning strategies for materials process optimization will likely replace human capital-intensive artisan research with autonomous and/or accelerated approaches. Such automation enables accelerated multimodal characterization that simultaneously minimizes human errors, lowers costs, enhances statistical sampling, and allows scientists to allocate their time to critical thinking instead of repetitive manual tasks. Previous acceleration efforts to synthesize and evaluate materials have often employed elaborate robotic self-driving laboratories or used specialized strategies that are difficult to generalize. Herein we describe an implemented workflow for accelerating the multimodal characterization of a combinatorial set of 915 electroplated Ni and Ni–Fe thin films resulting in a data cube with over 160,000 individual data files. Our acceleration strategies do not require manufacturing-scale resources and are thus amenable to typical materials research facilities in academic, government, or commercial laboratories. The workflow demonstrated the acceleration of six characterization modalities: optical microscopy, laser profilometry, X-ray diffraction, X-ray fluorescence, nanoindentation, and tribological (friction and wear) testing, each with speedup factors ranging from 13–46x. In addition, automated data upload to a repository using FAIR data principles was accelerated by 64x. Workflow ; Computer science ; Characterization (materials science) ; Automation ; Acceleration ; Data collection ; Artificial intelligence ; Process engineering ; Materials science ; Nanotechnology ; Mechanical engineering ; Database ; Engineering Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides ; Electron and X-Ray Spectroscopy Techniques
Authors: Lance Kavalsky | Vinay I. Hegde | Eric S. Muckley | Matthew S. Johnson | Bryce Meredig | Venkatasubramanian Viswanathan
Source: Digital Discovery (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

By how much can closed-loop frameworks accelerate computational materials discovery? A combination of task automation, calculation runtime improvements, machine learning surrogatization, and sequential learning-guided candidate selection within a closed-loop computational workflow can accelerate materials discovery by up to 20×. Workflow ; Computer science ; Task (project management) ; Automation ; Selection (genetic algorithm) ; Loop (graph theory) ; Closed loop ; Artificial intelligence ; Machine learning ; Distributed computing ; Control engineering ; Engineering ; Systems engineering ; Database Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides ; X-ray Diffraction in Crystallography
Authors: Daniel Pacheco Gutiérrez | Linnea M. Folkmann | Hermann Tribukait | Loı̈c M. Roch
Source: CHIMIA International Journal for Chemistry (article, 2023-02-22)
Field: Materials Science — Materials Chemistry

How to Accelerate R&amp;D and Optimize Experiment Planning with Machine Learning and Data Science Accelerating R&D is essential to address some of the challenges humanity is currently facing, such as achieving the global sustainability goals. Today's Edisonian approach of trial-and-error still prevalent in R&D labs takes up to two decades of fundamental and applied research for new materials to reach the market. Turning around this situation calls for strategies to upgrade R&D and expedite innovation. By conducting smart experiment planning that is data-driven and guided by AI/ML, researchers can more efficiently search through the complex - often constrained - space of possible experiments and find or hit the global optima much faster than with the current approaches. Moreover, with digitized data management, researchers will be able to maximize the utility of their data in the short and long terms with the aid of statistics, ML and visualization tools. In what follows, we describe a framework and lay out the key technologies to accelerate R&D and optimize experiment planning. Upgrade ; Computer science ; Big data ; Space (punctuation) ; Key (lock) ; Data science ; Visualization ; Artificial intelligence ; Data mining Machine Learning in Materials Science ; Scientific Computing and Data Management