jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Davide Materia | Leonardo Ratini | Celestino Angeli | Leonardo Guidoni
Source: arXiv (Cornell University) (preprint, 2024-04-22)
Field: Chemistry — Physical and Theoretical Chemistry

Quantum Information reveals that orbital-wise correlation is essentially classical in Natural Orbitals The intersection of Quantum Chemistry and Quantum Computing has led to significant advancements in understanding the potential of using quantum devices for the efficient calculation of molecular energies. Simultaneously, this intersection is enhancing the comprehension of quantum chemical properties through the use of quantum computing and quantum information tools. This paper tackles a key question in this relationship: Is the nature of the orbital-wise electron correlations in wavefunctions of realistic prototypical cases classical or quantum? We delve into this inquiry with a comprehensive examination of molecular wavefunctions using Shannon and von Neumann entropies, alongside classical and quantum information theory. Our analysis reveals a notable distinction between classical and quantum mutual information in molecular systems when analyzed with Hartree-Fock canonical orbitals. However, this difference decreases dramatically, by approximately 100-fold, when Natural Orbitals are used as reference. This finding suggests that wavefunction correlations, when viewed through the appropriate orbital basis, are predominantly classical. This insight indicates that computational tasks in quantum chemistry could be significantly simplified by employing Natural Orbitals. Consequently, our study underscores the importance of using Natural Orbitals to accurately assess molecular wavefunction correlations and to avoid their overestimation. In summary, our results suggest a promising path for computational simplification in quantum chemistry, advocating for the wider adoption of Natural Orbitals and raising questions about the actual computational complexity of the multi-body problem in quantum chemistry. Natural bond orbital ; Atomic orbital ; Physics ; Quantum mechanics ; Density functional theory ; Electron History and advancements in chemistry ; Molecular spectroscopy and chirality
Authors: Ruoling Deng | Long Qi | Jing Zhang | Ningxia Yin | Mingxin Hou | Xiaoming Xu
Source: Research Square (preprint, 2024-03-13)
Field: Chemistry — Analytical Chemistry

Non-destructive measurement of rice grain size based on panicle structure using deep learning method Panicle ; Artificial intelligence ; Agricultural engineering ; Statistics ; Mathematics ; Computer science ; Agronomy ; Biology ; Engineering Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Leaf Properties and Growth Measurement
Authors: Xiang Cheng | Lawrence Carin | Suvrit Sra
Source: arXiv (Cornell University) (preprint, 2024-10-22)
Field: Materials Science — Materials Chemistry

Graph Transformers Dream of Electric Flow We show theoretically and empirically that the linear Transformer, when applied to graph data, can implement algorithms that solve canonical problems such as electric flow and eigenvector decomposition. The Transformer has access to information on the input graph only via the graph's incidence matrix. We present explicit weight configurations for implementing each algorithm, and we bound the constructed Transformers' errors by the errors of the underlying algorithms. Our theoretical findings are corroborated by experiments on synthetic data. Additionally, on a real-world molecular regression task, we observe that the linear Transformer is capable of learning a more effective positional encoding than the default one based on Laplacian eigenvectors. Our work is an initial step towards elucidating the inner-workings of the Transformer for graph data. Code is available at https://github.com/chengxiang/LinearGraphTransformer Transformer ; Dream ; Graph ; Electrical engineering ; Computer science ; Mathematics ; Discrete mathematics ; Voltage ; Engineering ; Psychology Machine Learning in Materials Science ; Graph Theory and Algorithms ; Neural Networks and Applications
Authors: Л. В. Степанова | K. A. Mushankova
Source: Problems of Strength and Plasticity (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

ATOMISTIC AND CONTINUAL DETERMINATION OF STRESS FIELDS AT A CRACK TIP IN ANISOTROPIC ENVIRONMENT WITH CUBIC SYSTEM The article presents a comparative analysis of stresses associated with a crack tip in an anisotropic medium with cubic symmetry of elastic properties under mixed mode loading conditions, using two different approaches: atomistic and continuum approaches. The atomistic approach is based on the use of the molecular dynamics method implemented in the open source Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). The continuum approach is based on the classical theory of elasticity of anisotropic media, in which the mechanical fields associated with the crack tip are represented using series that generalize the well-known representation of M. Williams to the case of anisotropic media. Using the method of molecular dynamics, a large series of calculations of loading of single-crystal copper and aluminum plates with a face-centered crystal lattice, weakened by a central crack, was carried out using the embedded atom potential (EAM). Molecular dynamics modeling is aimed at determining atomistic stresses and strains near the crack tip. The calculated atomistic stresses were compared with the stress field determined by the continuum theory of elasticity of anisotropic media for crystal lattices with cubic symmetry of elastic properties. A comparative analysis was carried out for the angular dependences of the stress and strain tensor components at different distances from the crack tip for the entire range of mixed strain modes: from perfect normal tension to loadings close to perfect transverse shear. It is established that the fields found on the basis of two fundamentally different approaches (discrete and continuum) are fully consistent with each other. It is demonstrated that the mathematical methods of continuum fracture mechanics can be used to describe stress, strain, and displacement fields at the atomistic level. Anisotropy ; Materials science ; Stress (linguistics) ; Stress field ; Composite material ; Structural engineering ; Engineering ; Physics ; Optics ; Finite element method Material Properties and Failure Mechanisms ; Metallurgy and Material Forming ; Engineering Diagnostics and Reliability
Authors: D. Widdowson | Vitaliy Kurlin
Source: Acta Crystallographica Section A Foundations and Advances (article, 2024-08-26)
Field: Materials Science — Materials Chemistry

The crystal isometry principle has made transparent the black boxes of structural databases Isometry (Riemannian geometry) ; Database ; Crystal (programming language) ; Computer science ; Crystallography ; Mathematics ; Pure mathematics ; Programming language ; Chemistry X-ray Diffraction in Crystallography
Authors: Shuang Peng | Songze Chen | Hong Liang | Chuang Zhang
Source: arXiv (Cornell University) (preprint, 2024-11-04)
Field: Materials Science — Materials Chemistry

Semi-implicit Lax-Wendroff kinetic scheme for multi-scale phonon transport Fast and accurate predictions of the spatiotemporal distributions of temperature are crucial to the multi-scale thermal management and safe operation of microelectronic devices. To realize it, an efficient semi-implicit Lax-Wendroff kinetic scheme is developed for numerically solving the transient phonon Boltzmann transport equation (BTE) from the ballistic to diffusive regime. The phonon BTE at the cell center is discretized under the framework of finite volume method, where the trapezoidal and midpoint rules are used to deal with the temporal integration of phonon scattering and convection terms, respectively. For the reconstruction of the interfacial distribution function, the phonon BTE at the cell interface is discretized in the form of finite difference method and solved numerically, where second-order upwind and central scheme are used to deal with the spatial interpolation and gradient of interfacial distribution function, respectively. The macroscopic governing equations are invoked for the evolution of macroscopic fields at both the cell center and interface, where the macroscopic flux is obtained by taking the moment of the interfacial distribution function. Numerical results show that the present scheme could accurately predict the steady/unsteady heat conduction in solid materials from the ballistic to diffusive regime, and its time and cell size are not limited by the relaxation time and phonon mean free path. The present work could provide a useful tool for the efficient predictions of the macroscopic spatiotemporal distributions in the multi-scale thermal engineering. Phonon ; Scale (ratio) ; Kinetic energy ; Scheme (mathematics) ; Physics ; Classical mechanics ; Mathematics ; Condensed matter physics ; Mathematical analysis ; Quantum mechanics Thermal properties of materials ; Spectral Theory in Mathematical Physics ; Numerical methods in inverse problems
Authors: David F. Anderson | Badal Joshi
Source: arXiv (Cornell University) (preprint, 2024-04-05)
Field: Chemistry — Physical and Theoretical Chemistry

Chemical mass-action systems as analog computers: implementing arithmetic computations at specified speed Recent technological advances allow us to view chemical mass-action systems as analog computers. In this context, the inputs to a computation are encoded as initial values of certain chemical species while the outputs are the limiting values of other chemical species. In this paper, we design chemical systems that carry out the elementary arithmetic computations of: identification, inversion, $m$th roots (for $m \ge 2$), addition, multiplication, absolute difference, rectified subtraction over non-negative real numbers, and partial real inversion over real numbers. We prove that these ``elementary modules'' have a speed of computation that is independent of the inputs to the computation. Moreover, we prove that finite sequences of such elementary modules, running in parallel, can carry out composite arithmetic over real numbers, also at a rate that is independent of inputs. Furthermore, we show that the speed of a composite computation is precisely the speed of the slowest elementary step. Specifically, the scale of the composite computation, i.e. the number of elementary steps involved in the composite, does not affect the overall asymptotic speed -- a feature of the parallel computing nature of our algorithm. Our proofs require the careful mathematical analysis of certain non-autonomous systems, and we believe this analysis will be useful in different areas of applied mathematics, dynamical systems, and the theory of computation. We close with a discussion on future research directions, including numerous important open theoretical questions pertaining to the field of computation with reaction networks. Arithmetic ; Computation ; Analog computer ; Action (physics) ; Computer science ; Parallel computing ; Mathematics ; Algorithm ; Engineering ; Electrical engineering ; Physics Various Chemistry Research Topics
Authors: Hanur Meku Yesuf | Syed Rashedul Islam | Xueping Zhang | Xiaohong Qin
Source: Environmental Engineering Research (article, 2024-10-01)
Field: Chemistry — Spectroscopy

Super-hydrophobic blended needle-punched nonwovens integrated with silica-aerogels for PM2.5 filtration This study investigated the hydrophobic and PM2.5 filtration properties of blended needle-punched nonwovens with the treatment of silica-aerogel. The treatment was done by padding. The BET, SEM and FTIR studies were used to investigate the influence of silica-aerogel on needle-punched nonwovens such as surface properties and molecular interaction. All the treated samples showed super-hydrophobic properties with water contact angle (WCA) of around 154.2 - 154.79o, filtration efficiency of 99.07 - 99.21%, pressure drop of 72.83 - 79.71 Pa and dust-holding capacity of 3,459,520 - 3,472,060 particles/cm2. The findings demonstrated that silica-aerogel played a vital role in enhancing the hydrophobicity, filtration efficiency, dust-holding capacity and fabric density of blended needle-punched nonwovens with statistically significant performance (p&lt;0.05). There was no statistically significant difference in pressure drop, air permeability, porosity, and fabric thickness, which indicated that the treated samples could perform without structure loss as compared to the untreated. Filtration (mathematics) ; Materials science ; Air filtration ; Composite material ; Chemical engineering ; Chemistry ; Particulates ; Organic chemistry ; Engineering ; Mathematics Aerogels and thermal insulation ; Electrospun Nanofibers in Biomedical Applications ; Aerosol Filtration and Electrostatic Precipitation
Authors: Louise Marie Buur | Arthur Declercq | Marina Strobl | Robbin Bouwmeester | Sven Degroeve | Lennart Martens | Viktoria Dorfer | Ralf Gabriels
Source: ChemRxiv (preprint, 2024-01-28)
Field: Chemistry — Spectroscopy

MS²Rescore 3.0 is a modular, flexible, anduser-friendly platform to boost peptideidentifications, as showcased with MS Amanda 3.0 Rescoring of peptide-spectrum matches (PSMs) has emerged as a standard procedure for the analysis of tandem mass spectrometry data. This emphasizes the need for software maintenance and continuous improvement for such algorithms. We here introduce MS²Rescore 3.0, a versatile, modular, and user-friendly platform designed to increase peptide identifications. Researchers can install MS²Rescore across various platforms with minimal effort and benefit from a graphical user interface, a modular Python API, and extensive documentation. To showcase this new version, we connected MS²Rescore 3.0 with MS Amanda 3.0, a new release of the well-established search engine, addressing previous limitations on automatic rescoring. Among new features, MS Amanda now contains additional output columns that can be used for rescoring. The full potential of rescoring is best revealed when applied on challenging data sets. We therefore evaluated the performance of these two tools on publicly available single-cell data sets, where the number of PSMs was substantially increased, thereby demonstrating that MS²Rescore offers a powerful solution to boost peptide identifications. MS²Rescore's modular design and user-friendly interface make data-driven rescoring easily accessible, even for inexperienced users. We therefore expect MS²Rescore to be a valuable tool for the wider proteomics community. MS²Rescore is available at https://github.com/compomics/ms2rescore. Modular design ; Python (programming language) ; Computer science ; Documentation ; User Friendly ; Graphical user interface ; Interface (matter) ; Software ; User interface ; Human–computer interaction ; Operating system ; Software engineering Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Advanced biosensing and bioanalysis techniques
Authors: Hui Sun | Hao Luo | Feifei Wang | Qingjiu CHEN | Meng Chen | X. L. Wang | Haibo Yu | Guanglie Zhang | Lianqing Liu | Jianping Wang | Dapeng Wu | Wen J. Li
Source: Research Square (preprint, 2024-07-11)
Field: Materials Science — Surfaces, Coatings and Films

Deep Learning-Enabled Transformation of Scanning Superlens Microscopy Images into Scanning Electron Microscopy-like Large Depth-of-Field Images Dark field microscopy ; Microscopy ; Scanning confocal electron microscopy ; Scanning electron microscope ; Transformation (genetics) ; Materials science ; Electron microscope ; Depth of field ; Optics ; Scanning ion-conductance microscopy ; Artificial intelligence ; Computer science ; Chemistry ; Physics Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications ; Advanced Fluorescence Microscopy Techniques
Authors: S. Nithya priya | L. Ramesh
Source: International Research Journal on Advanced Engineering and Management (IRJAEM) (review, 2024-10-18)
Field: Chemistry — Inorganic Chemistry

Need of Feature Extraction in Coconut Tree Disease Detection: A Review Agriculture has served as the primary means of sustenance for mankind for thousands of years. Even in the present day, it continues to support approximately 50% of the global population. Plant diseases pose a significant threat to crop production, resulting in substantial losses each year on a global scale. To mitigate the financial impact of these diseases, it is crucial to maintain the health of plants throughout their growth and development. The symptoms of infections are predominantly visible on plant leaves, making them a common indicator for disease detection and identification. However, visually observing and identifying diseases is a challenging task that requires extensive human expertise. To provide farmers with improved assistance in disease detection, image processing techniques combined with computational intelligence or soft computing techniques can be employed. These methods offer a more effective approach to disease detection. By extracting features from the symptoms of a disease, it becomes possible to identify and detect the presence of a disease in plants. Therefore, feature extraction techniques play a vital role in such systems. This paper focuses on reviewing the feature extraction methods, highlighting their advantages and disadvantages. It provides a comprehensive discussion on various image features, including color, texture, and shape, for different types of disorders found in diverse agricultural practices. Tree (set theory) ; Computer science ; Extraction (chemistry) ; Feature (linguistics) ; Pattern recognition (psychology) ; Artificial intelligence ; Mathematics ; Chromatography ; Chemistry ; Combinatorics ; Linguistics Coconut Research and Applications ; Date Palm Research Studies ; Plant Pathogens and Fungal Diseases
Authors: Kallil M. Zielinski | Leonardo Scabini | Lucas C. Ribas | Núbia R. da Silva | Hans Beeckman | Jan Verwaeren | Odemir Martinez Bruno | Bernard De Baets
Source: arXiv (Cornell University) (preprint, 2024-04-12)
Field: Chemistry — Organic Chemistry

Advanced wood species identification based on multiple anatomical sections and using deep feature transfer and fusion In recent years, we have seen many advancements in wood species identification. Methods like DNA analysis, Near Infrared (NIR) spectroscopy, and Direct Analysis in Real Time (DART) mass spectrometry complement the long-established wood anatomical assessment of cell and tissue morphology. However, most of these methods have some limitations such as high costs, the need for skilled experts for data interpretation, and the lack of good datasets for professional reference. Therefore, most of these methods, and certainly the wood anatomical assessment, may benefit from tools based on Artificial Intelligence. In this paper, we apply two transfer learning techniques with Convolutional Neural Networks (CNNs) to a multi-view Congolese wood species dataset including sections from different orientations and viewed at different microscopic magnifications. We explore two feature extraction methods in detail, namely Global Average Pooling (GAP) and Random Encoding of Aggregated Deep Activation Maps (RADAM), for efficient and accurate wood species identification. Our results indicate superior accuracy on diverse datasets and anatomical sections, surpassing the results of other methods. Our proposal represents a significant advancement in wood species identification, offering a robust tool to support the conservation of forest ecosystems and promote sustainable forestry practices. Pooling ; Random forest ; Identification (biology) ; Computer science ; Artificial intelligence ; Convolutional neural network ; Transfer of learning ; Pattern recognition (psychology) ; Feature (linguistics) ; Feature extraction ; Machine learning ; Ecology ; Biology Wood and Agarwood Research ; Remote Sensing and LiDAR Applications ; Identification and Quantification in Food
Authors: Sang‐Jun Han | Hong Jin Kong | Junho Choi | Won Chegal | Min Seok Jang
Source: arXiv (Cornell University) (preprint, 2024-09-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Single-gate electro-optic beam switching metasurfaces Electro-optic active metasurfaces have attracted attention due to their ability to electronically control optical wavefront with unprecedented spatiotemporal resolutions. In most studies, such devices require gate arrays composed of a large number of independently-controllable local gate electrodes that address local scattering response of individual metaatoms. Although this approach in principle enables arbitrary wavefront control, the complicated driving mechanism and low optical efficiency have been hindering its practical applications. In this work, we demonstrate an active beam switching device that provides high directivity, uniform efficiency across diffraction orders, and a wide field of view while operating with only a single-gate bias. Experimentally, the metasurface achieves 57° of active beam switching from the 0th to the -1st order diffraction, with efficiencies of 0.084 and 0.078 and directivities of 0.765 and 0.836, respectively. Furthermore, an analytical framework using nonlocal quasinormal mode expansion provides deeper insight into the operating mechanism of active beam switching. Finally, we discuss the performance limitations of this design platform and provide insights into potential improvements. Beam (structure) ; Optoelectronics ; Optics ; Optical switch ; Materials science ; Physics Metamaterials and Metasurfaces Applications ; Photonic and Optical Devices ; Quantum optics and atomic interactions
Authors: Hyun‐Jae Lee | Kyoung‐June Go | Pawan Kumar | Chang‐Hoon Kim | Yungyeom Kim | Kyoungjun Lee | Takao Shimizu | Seung Chul Chae | Hosub Jin | Minseong Lee | Umesh V. Waghmare | Si‐Young Choi | Jun Hee Lee
Source: arXiv (Cornell University) (preprint, 2024-03-03)
Field: Materials Science — Materials Chemistry

Phonon-pair-driven Ferroelectricity Causes Costless Domain-walls and Bulk-boundary Duality Ferroelectric domain walls, recognized as distinct from the bulk in terms of symmetry, structure, and electronic properties, host exotic phenomena including conductive walls, ferroelectric vortices, novel topologies, and negative capacitance. Contrary to conventional understanding, our study reveals that the structure of domain walls in HfO2 closely resembles its bulk. First, our first-principles simulations unveil that the robust ferroelectricity is supported by bosonic pairing of all the anionic phonons in bulk HfO2. Strikingly, the paired phonons strongly bond with each other and successfully reach the center of the domain wall without losing their integrity and produce bulk-like domain walls. We then confirmed preservation of the bulk phonon displacements and consequently full revival of the bulk structure at domain walls via aberration-corrected STEM. The newly found duality between the bulk and the domain wall sheds light on previously enigmatic properties such as zero-energy domain walls, perfect Ising-type polar ordering, and exceptionally robust ferroelectricity at the sub-nm scales. The phonon-pairing discovered here is robust against physical boundaries such as domain walls and enables zero momentum and zero-energy cost local ferroelectric switching. This phenomenon demonstrated in Si-compatible ferroelectrics provides a novel technological platform where data storage on domain walls is as feasible as that within the domains, thereby expanding the potential for high-density data storage and advanced ferroelectric applications. Phonon ; Duality (order theory) ; Ferroelectricity ; Boundary (topology) ; Condensed matter physics ; Domain (mathematical analysis) ; Materials science ; Physics ; Mathematics ; Quantum mechanics ; Pure mathematics ; Mathematical analysis ; Dielectric Ferroelectric and Piezoelectric Materials ; Acoustic Wave Resonator Technologies ; Smart Materials for Construction