jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Chaejin Park | Sanmun Kim | Anthony W. Jung | Juho Park | Dongjin Seo | Yongha Kim | Chanhyung Park | Chan Young Park | Min Seok Jang
Source: arXiv (Cornell University) (preprint, 2023-06-07)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Physics-informed reinforcement learning for sample-efficient optimization of freeform nanophotonic devices In the field of optics, precise control of light with arbitrary spatial resolution has long been a sought-after goal. Freeform nanophotonic devices are critical building blocks for achieving this goal, as they provide access to a design potential that could hardly be achieved by conventional fixed-shape devices. However, finding an optimal device structure in the vast combinatorial design space that scales exponentially with the number of freeform design parameters has been an enormous challenge. In this study, we propose physics-informed reinforcement learning (PIRL) as an optimization method for freeform nanophotonic devices, which combines the adjoint-based method with reinforcement learning to enhance the sample efficiency of the optimization algorithm and overcome the issue of local minima. To illustrate these advantages of PIRL over other conventional optimization algorithms, we design a family of one-dimensional metasurface beam deflectors using PIRL, obtaining more performant devices. We also explore the transfer learning capability of PIRL that further improves sample efficiency and demonstrate how the minimum feature size of the design can be enforced in PIRL through reward engineering. With its high sample efficiency, robustness, and ability to seamlessly incorporate practical device design constraints, our method offers a promising approach to highly combinatorial freeform device optimization in various physical domains. Reinforcement learning ; Maxima and minima ; Computer science ; Robustness (evolution) ; Nanophotonics ; Computation ; Sample (material) ; Computer engineering ; Optimal design ; Optimization problem ; Artificial intelligence ; Algorithm ; Machine learning ; Physics ; Mathematics ; Optics Metamaterials and Metasurfaces Applications ; Photonic Crystals and Applications ; Neural Networks and Reservoir Computing
Authors: Bo Yin | Rongping Zhou | Zhonglong Guo | Sun Jing | Jihua Zhu | Zhenbin Wang | Cunhua Ma | Mingjin Zhang
Source: Research Square (preprint, 2023-08-23)
Field: Materials Science — Materials Chemistry

A smartphone-based sensing for portable and sensitive visual detection of Hg (II) via nitrogen doped carbon quantum dots modified paper strip Abstract The development of portable and cost-effective sensing system for Hg2+ quantitation is highly demanded for environmental monitoring. Herein, an on-site, rapid and portable smartphone readout device based Hg2+ sensing system integrating nitrogen-doped carbon quantum dots (NCDs) modified paper strip was proposed, and the physicochemical properties of NCDs were characterized by high resolution TEM, FTIR, UV-vis absorption spectrum and fluorescence spectral analysis. The modified paper strip was prepared via “ink-jet” printing technology and exhibits sensitive fluorescence response to Hg2+ with fluorescence color of bright blue (at the excitation/emission wavelength of 365/440 nm). This portable smartphone-based sensing platform is highly selective and sensitive to Hg2+ with the limit of detection (LOD) of 10.6 nM and the concentration range of 0-130 nM. In addition, the recoveries of tap water and local lake water were in the range of 89.4% to 109%. The cost-effective sensing system based on smartphone shows a great potential for trace amounts of Hg2+ monitoring in environmental water samples. Detection limit ; Fluorescence ; Tap water ; Quantum dot ; Materials science ; Absorption (acoustics) ; Carbon fibers ; Analytical Chemistry (journal) ; Doping ; Fourier transform infrared spectroscopy ; Nanotechnology ; Optoelectronics ; Chemistry ; Environmental chemistry ; Environmental science ; Optics ; Chromatography ; Environmental engineering ; Physics ; Composite number Carbon and Quantum Dots Applications ; Advanced biosensing and bioanalysis techniques ; Advanced Nanomaterials in Catalysis
Authors: Sina Kazemian | Giovanni Fanchini
Source: arXiv (Cornell University) (preprint, 2023-05-27)
Field: Materials Science — Materials Chemistry

Influence of higher order electron-phonon interaction on the electron-related lattice thermal properties of 2d Dirac crystal To understand the essential properties of Dirac crystals, such as their thermal conductivity, we require models that consider the interaction between Dirac electrons and dispersive acoustic phonons. The exceptionally high thermal conductivity in 2D Dirac crystals is attributed to near-ideal phonon quantum gases, while undesired limitations arise from electron-phonon (e-ph) interactions which have been shown to limit the thermal conductivity up to several microns away. The e-ph thermal conductivity is directly linked to the phonon scattering rate. Conventional calculations overlook phonons with short-dispersive wavelengths, rendering them inadequate for analyzing 2D Dirac crystals. The phonon scattering rate is typically calculated up to the first-order magnitude, considering 3-particle interactions involving the decay of an electron and phonon (EP-E*) to create a new electron. However, processes involving the decay of an electron and the creation of a new electron and phonon (E-E*P*) are neglected. In this study, we present an accurate expression for the phonon scattering rate and e-ph thermal conductivity in 2D Dirac crystals, accounting for short-dispersive wavelength phonons. We demonstrate the significance of the E-E*P* process even at room temperature in calculating the phonon scattering rate and e-ph thermal conductivity, particularly for first-order e-ph interactions. Furthermore, we emphasize the importance of incorporating second-order e-ph interactions, specifically the EP-E*P* interaction involving the decay of an electron and phonon and the creation of a new electron-phonon pair, to accurately determine the phonon scattering rate and e-ph thermal conductivity at high temperatures and low Fermi energies. This 4-particle interaction process plays a crucial role in characterizing these properties effectively. Phonon ; Thermal conductivity ; Condensed matter physics ; Scattering rate ; Scattering ; Phonon scattering ; Electron ; Physics ; Quantum mechanics Thermal properties of materials ; Topological Materials and Phenomena ; Superconductivity in MgB2 and Alloys
Authors: Demetrios A. Tzelepis | Arman Khoshnevis | Mohsen Zayernouri | Valeriy V. Ginzburg
Source: PubMed (preprint, 2023-11-13)
Field: Materials Science — Polymers and Plastics

Polyurea-Graphene Nanocomposites -- the Influence of Hard-Segment Content and Nanoparticle Loading on Mechanical Properties Polyurethane and polyurea-based adhesives are widely used in various applications, from automotive to electronics and medical applications. The adhesive performance depends strongly on its composition, and developing the formulation-structure-property relationship is crucial to making better products. Here, we investigate the dependence of the linear viscoelastic properties of polyurea nanocomposites, with an IPDI-based polyurea (PUa) matrix and exfoliated graphene nanoplatelet (xGnP) fillers, on the hard-segment weight fraction (HSWF) and the xGnP loading. We characterize the material using scanning electron microscopy (SEM) and dynamic mechanical analysis (DMA). It is found that changing the HSWF leads to a significant variation in the stiffness of the material, from about 10 MPa for 20% HSWF to about 100 MPa for 30% HSWF and about 250 MPa for the 40% HSWF polymer (as measured by the tensile storage modulus at room temperature). The effect of the xGNP loading was significantly more limited and was generally within experimental error, except for the 20% HSWF material, where the xGNP addition led to about an 80% increase in stiffness. To correctly interpret the DMA results, we developed a new physics-based rheological model for the description of the storage and loss moduli. The model is based on the fractional calculus approach and successfully describes the material rheology in a broad range of temperatures (-70 °C-+70 °C) and frequencies (0.1-100 s<sup>-1</sup>), using only six physically meaningful fitting parameters for each material. The results provide guidance for the development of nanocomposite PUa-based materials. Polyurea ; Nanocomposite ; Materials science ; Composite material ; Nanoparticle ; Graphene ; Nanotechnology Polymer Nanocomposites and Properties ; Polymer composites and self-healing ; Polymer crystallization and properties
Authors: Ruchi Singh | Huda Khanam | Jyoti Pandey
Source:  (article, 2023-11-15)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Optimization, First-Order Hyperpolarizability Studies of o, m, and p-Cl Benzaldehydes Using DFT Studies In this paper, we first optimized the structures of Cl benzaldehydes using Gaussian 09 software with the B3LYP/631-G’ (d,p) basis set. The title compound’s polarizability and hyperpolarizabilities values have been computed, along with an examination of its nonlinear optical characteristics. The title molecule’s total initial static hyperpolarizability as determined by DFT studies may be a topic for future NLO content that is appealing. Hyperpolarizability ; Order (exchange) ; Computer science ; Chemistry ; Computational chemistry ; Physics ; Nonlinear optical ; Nonlinear system ; Quantum mechanics Nonlinear Optical Materials Research ; Organic Chemistry Cycloaddition Reactions ; Structural and Chemical Analysis of Organic and Inorganic Compounds
Authors: M. Amir Bazrafshan | Farhad Khoeini | B. Szafran
Source: arXiv (Cornell University) (preprint, 2023-09-16)
Field: Materials Science — Materials Chemistry

Insights into electronic and transport properties of phosphorene nanorings in two perpendicular directions: Effects of circular and elliptical external potentials In this work, we study the electronic and transport properties of phosphorene nanorings in two perpendicular directions (zigzag and armchair directions) in the presence of zigzag metallic source and drain leads. Our results are based on the non-equilibrium Green's function (NEGF) method and a five-parameter tight-binding (TB) approach. We investigate how system parameters affect the electronic transport. These parameters include the radius of the rings, the width of the leads and the external potential. Our results show that for all configurations studied, a transport energy gap exists whose width can be tuned by the width of the leads and the radius of the nanoring. The transmission function of wider leads shows more sensitivity to the variation of the inner radius due to higher electronic states that can respond to smaller changes in the scattering region. In addition, the transport along the armchair direction is more susceptible to tuning than the transport along the zigzag direction. The effects of external potentials on the conductance are more pronounced than the geometrical parameters. In particular the circular potential of the amplitude of 0.1 eV can widen the transport gap by about ~0.35 eV. Zigzag ; Phosphorene ; Condensed matter physics ; RADIUS ; Conductance ; Perpendicular ; Tight binding ; Materials science ; Nanoring ; Electronic structure ; Physics ; Band gap ; Nanotechnology ; Geometry 2D Materials and Applications ; Molecular Junctions and Nanostructures ; Advanced Thermoelectric Materials and Devices
Source: Chemical Communications (article, 2023-01-01)
Field: Chemistry — Inorganic Chemistry

Contents list Permissions Request permissions Contents list Chem. Commun., 2023, 59, 6601 DOI: 10.1039/D3CC90184J This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given. Read more about how to correctly acknowledge RSC content. Acknowledgement ; Chromatin structure remodeling (RSC) complex ; Computer science ; Attribution ; World Wide Web ; Library science ; Chemistry ; Computer security ; Psychology Radioactive element chemistry and processing
Authors: Avinash Singh | Tripti Richhariya
Source: MIGRATION LETTERS (article, 2023-12-20)
Field: Chemistry — Analytical Chemistry

Sensing of Harmful Dyes in Food Particles Using Nanomaterial-Based Electrochemical Analysis Azo-dyes, including Allura Red, Sunset Yellow (SY), Brilliant Blue, and Tartrazine (Tz), are commonly utilized as food coloring additives because of their affordability and durability. The dyes SY and Tz are widely employed within this dye group because of their comparable hues and frequent co-application in food items. Despite their beneficial industrial applications, these substances include a toxicity profile that poses risks, including the potential for undesirable consequences such as allergies, asthma, cancer, DNA damage, cytotoxicity, and nervousness. In light of these factors, employing susceptible, cost-effective, straightforward, and expeditious sensors to examine azo-hazardous dyes is imperative. Electrochemical nanosensors (ENS), which integrate the distinctive characteristics of electrochemistry with nanotechnology, are very advantageous devices that find extensive application in analyzing azo dyes. In this paper, the exterior of a Glassy Carbon Electrode (GCE) has been subjected to modification by the incorporation of calixarene (Cx) and gold nanoparticles (AuNP) to facilitate the improvement and integration of electrochemistry with nanotechnology. The sensing capability of the Modified GCE (MGCE) nanosensor with Cx and AuNP has been evaluated by the utilization of Cyclic Voltammetry (CV) and Differential Pulse Voltammetry (DPV) techniques. The study aimed to examine the impact of various factors to determine the optimal circumstances for obtaining the most favorable reaction from the target analytical substances. The signals of the chosen food dyes have been significantly improved when using the MGCE nanocomposite, which is attributed to the synergistic interaction between Cx and AuNP compared to the unmodified GCE. The sensor platform that was built also showed notable performance characteristics when utilized to detect food colors in food samples. Furthermore, the observed high percentage of recovery, consistent repeatability, and durability indicate the potential use of the developed electrochemical platform to examine actual samples. Tartrazine ; Differential pulse voltammetry ; Nanosensor ; Nanomaterials ; Nanotechnology ; Cyclic voltammetry ; Electrochemistry ; Nanocomposite ; Materials science ; Chemistry ; Electrode ; Chromatography Dye analysis and toxicity ; Electrochemical sensors and biosensors ; Electrochemical Analysis and Applications
Authors: Danila A. Barskiy | John W. Blanchard | Dmitry Budker | Quentin Stern | James Eills | Stuart J. Elliott | Román Picazo‐Frutos | Antoine Garcon | Sami Jannin | Igor V. Koptyug
Source: arXiv (Cornell University) (preprint, 2023-07-13)
Field: Chemistry — Spectroscopy

Possible Applications of Dissolution Dynamic Nuclear Polarization in Conjunction with Zero- to Ultralow-Field Nuclear Magnetic Resonance The combination of a powerful and broadly applicable nuclear hyperpolarization technique with emerging (near-)zero-field modalities offer novel opportunities in a broad range of nuclear magnetic resonance spectroscopy and imaging applications, including biomedical diagnostics, monitoring catalytic reactions within metal reactors and many others. These are discussed along with a roadmap for future developments. Hyperpolarization (physics) ; Polarization (electrochemistry) ; Nuclear magnetic resonance ; Spectroscopy ; Nuclear magnetic resonance spectroscopy ; Nuclear engineering ; Physics ; Materials science ; Engineering ; Chemistry Advanced NMR Techniques and Applications ; Solid-state spectroscopy and crystallography ; Electron Spin Resonance Studies
Authors: Enésio Marinho | Cesar E. P. Villegas | Pedro Venezuela | Alexandre Reily Rocha
Source: arXiv (Cornell University) (preprint, 2023-12-16)
Field: Materials Science — Materials Chemistry

Photovoltaic efficiency of transition metal dichalcogenides thin films by ab initio excited-state methods Transition metal dichalcogenides (TMDCs) have garnered significant interest in optoelectronics, owing to their scalability and thickness-dependent electrical and optical properties. In particular, thin films of TMDCs could be used in photovoltaic devices. In this work, we employ $ab$ $initio$ many-body perturbation theory within $G_0W_0$-BSE approach to accurately compute the optoelectronic properties of thin films of 2H-TMDCs composed of Mo, W, S, and Se. Subsequently, we evaluate their photovoltaic performance including exciton recombination effects, and show this is a key ingredient. We obtain efficiencies of up to 29\% for a 200-nm thick film of \ce{WSe2}, thus providing an upper limit. We also include other \textcolor{black}{phenomenological} recombination mechanisms that could be present in current samples. This slightly reduces efficiencies, indicating that even with current synthesis technologies, there is still potential for further enhancement of TMDCs' performance in photovoltaic applications. Photovoltaic system ; Materials science ; Ab initio ; Thin film ; Optoelectronics ; Transition metal ; Exciton ; Ab initio quantum chemistry methods ; Excited state ; Condensed matter physics ; Nanotechnology ; Chemistry ; Atomic physics ; Catalysis ; Electrical engineering ; Physics 2D Materials and Applications ; Advanced Chemical Physics Studies ; Machine Learning in Materials Science
Authors: Hassan El‐Sayed | El‑Sheikh, M. N. | Rohim, M. Nafea M.
Source: Journal of the Egyptian Society of Tribology /Journal of the Egyptian Society of Tribology (article, 2023-07-01)
Field: Materials Science — General Materials Science

INVESTIGATION OF MECHANICAL AND TRIBOLOGICAL PROPERTIES OF THE PTFE/PA12 POLYMERIC DUAL-MATRIX REINFORCED WITH ZnO NPs FOR PROSTHETICS APPLICATIONS. The current study aims to introduce novel nanocomposites consisted of polymeric dual-matrix, polytetrafluorethylene/polyamide12 (PTFE/PA12), reinforced with zinc oxide nanoparticles (ZnO NPs) for prosthetics applications. PA12 content to polymeric dual-matrix was 5, 10, 15, and 20 weight fraction (wt. %). Also, ZnO NPs, which were characterized by transmission electron microscope (TEM), were filled into the dual-matrix of PTFE/PA12 by 0.25, 0.5, 1, and 1.5 wt. %. All the present nanocomposites were fabricated by a hot-pressing technique. Compression, microhardness, wear, and friction tests were performed to study the mechanical and tribological properties of all the fabricated nanocomposites. After the wear test, worn surfaces were examined by scanning electron microscope (SEM) to emphasize the occurred wear mechanism. Experimental results revealed that the optimum content of PA12 and ZnO NPs into proposed nanocomposites were 15 and 1 wt. %, respectively. Consequently, elastic modulus, compressive yield strength, Vickers hardness number (VHN), wear rate and friction coefficient of PTFE/15 wt. % PA12, as a dual-matrix, were enhanced by 125.48, 70.88, 81.68, 57.27, and 54.16 %, respectively compared to pure PTFE. Also, elastic modulus, compression yield strength, VHN, wear rate, and friction coefficient of the proposed PTFE/15 wt. %/1 wt. % ZnO NPs composite showed significant improvements by 51.58, 58.59, 50.86, 73.91, and 44.63%, respectively compared to the pure dual-matrix. Worn surfaces of the proposed composites proved that a significant enhancement was observed compared to the other worn surfaces. According to that, the proposed nanocomposites of PTFE/15 wt. % PA12/1 wt. % ZnO NPs are considered as a suitable choice for prosthetic applications. Tribology ; Materials science ; Composite material ; Matrix (chemical analysis) ; Polytetrafluoroethylene ; Dual (grammatical number) Material Properties and Applications ; Polymer Science and Applications
Authors: Tomasz Szołdra | Marcelo F. Ciappina | Nicholas Werby | P. H. Bucksbaum | Maciej Lewenstein | Jakub Zakrzewski | Andrew Maxwell
Source: New Journal of Physics (article, 2023-08-01)
Field: Chemistry — Spectroscopy

Femtosecond pulse parameter estimation from photoelectron momenta using machine learning Abstract Deep learning models have provided huge interpretation power for image-like data. Specifically, convolutional neural networks (CNNs) have demonstrated incredible acuity for tasks such as feature extraction or parameter estimation. Here we test CNNs on strong-field ionization photoelectron spectra, training on theoretical data sets to ‘invert’ experimental data. Pulse characterization is used as a ‘testing ground’, specifically we retrieve the laser intensity, where ‘traditional’ measurements typically lead to 20% uncertainty. We report on crucial data augmentation techniques required to successfully train on theoretical data and return consistent results from experiments, including accounting for detector saturation. The same procedure can be repeated to apply CNNs in a range of scenarios for strong-field ionization. Using a predictive uncertainty estimation, reliable laser intensity uncertainties of a few percent can be extracted, which are consistently lower than those given by traditional techniques. Using interpretability methods can reveal parts of the distribution that are most sensitive to laser intensity, which can be directly associated with holographic interferences. The CNNs employed provide an accurate and convenient ways to extract parameters, and represent a novel interpretational tool for strong-field ionization spectra. Physics ; Femtosecond ; Pulse (music) ; X-ray photoelectron spectroscopy ; Computational physics ; Statistical physics ; Optics ; Nuclear magnetic resonance ; Laser Mass Spectrometry Techniques and Applications ; Laser-Matter Interactions and Applications ; Advanced Chemical Physics Studies
Authors: Thomas D. Swinburne
Source: arXiv (Cornell University) (preprint, 2023-09-05)
Field: Materials Science — Materials Chemistry

Compressing and forecasting atomic material simulations with descriptors Atomic simulations of material microstructure require significant resources to generate, store and analyze. Here, atomic descriptor functions are proposed as a general latent space to compress atomic microstructure, ideal for use in large-scale simulations. Descriptors can regress a broad range of properties, including character-dependent dislocation densities, stress states or radial distribution functions. A vector autoregressive model can generate trajectories over yield points, resample from new initial conditions and forecast trajectory futures. A forecast confidence, essential for practical application, is derived by propagating forecasts through the Mahalanobis outlier distance, providing a powerful tool to assess coarse-grained models. Application to nanoparticles and yielding of dislocation networks confirms low uncertainty forecasts are accurate and resampling allows for the propagation of smooth microstructure distributions. Yielding is associated with a collapse in the intrinsic dimension of the descriptor manifold, which is discussed in relation to the yield surface. Resampling ; Mahalanobis distance ; Computer science ; Statistical physics ; Range (aeronautics) ; Algorithm ; Mathematics ; Artificial intelligence ; Physics ; Materials science Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Theoretical and Computational Physics