jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Gabriele Losi | Omar Chehaimi | Maria Clelia Righi
Source: arXiv (Cornell University) (preprint, 2023-04-27)
Field: Materials Science — Materials Chemistry

TribChem: a Software for the First-principles, High-Throughput Study of Solid Interfaces and their Tribological properties High throughput first-principles calculations, based on solving the quantum mechanical many-body problem for hundreds of materials in parallel, have been successfully applied to advance many materials-based technologies, from batteries to hydrogen storage. However, this approach has not yet been adopted to systematically study solid-solid interfaces and their tribological properties. To this aim, we developed TribChem, an advanced software based on the FireWorks platform, which is here presented. TribChem is constructed in a modular way, allowing for the separate calculation of bulk, surface, and interface properties. At present the calculated interfacial properties include adhesion, shear strength, and charge redistribution. Further properties can be easily added due to the general structure of the main workflow. Tribology ; Materials science ; Workflow ; Modular design ; Throughput ; Software ; Nanotechnology ; Computer science ; Interface (matter) ; Computational science ; Mechanical engineering ; Composite material ; Engineering ; Database Diamond and Carbon-based Materials Research ; Force Microscopy Techniques and Applications ; Electron and X-Ray Spectroscopy Techniques
Authors: Sócrates Pedro Muñoz Pérez | María Magaly Morante-Santamaría | Helmer Félix Huamán-Manayay
Source: Revista UIS Ingenierías (article, 2023-03-21)
Field: Materials Science — Polymers and Plastics

Revisión sistemática del comportamiento convencional y reológico del biocompuesto asfalto-biomasas producidas La ingeniería de pavimentos, busca con ahínco materiales no petrolíficos como sustituyentes/mejoradores del asfalto. La producción de bioasfalto con biomasa es la técnica más usual con beneficios económicos, sociales y medioambientales. Este documento tiene como objetivo realizar una revisión literaria del mejoramiento del asfalto con biomasa en subproductos de biocarbón o bioaceite. Se efectuó una revisión de 80 artículos científicos, los cuales estudiaron las propiedades convencionales y reológicas del asfalto con porcentajes óptimos de adición de biomodificadores, considerándolos como nuevas tecnologías en las construcciones viales. Los resultados muestran que la dosis y tipo del biomaterial influye mucho como modificador, dado que el rendimiento del bioasfalto a base de biomasa garantiza reacciones positivas con una mínina adición de 1% de aceite de palma hasta 100% de ceniza de madera como máximo. En conclusión, a mayor dosis de biomodificador a altas temperaturas mayor es la mejora en la viscosidad, estabilidad, grado de penetración, punto de reblandecimiento, resistencia a la tracción indirecta, módulo de resistencia, resistencia a la deformación, resistencia a la fatiga, resistencia al deslizamiento y resistencia a la humedad del asfalto, además de tener mejores condiciones de envejecimiento oxidativo, pues generalmente el ligante asfáltico es compatible con la mayoría de los biomateriales, siendo viable como fuente de energía renovable, sostenible y de calidad. Humanities ; Art ; Physics ; Philosophy Natural Fiber Reinforced Composites
Authors: Handong Li | Jianwei Wang | Chanchan Qin | Tao Lei | Fushan Lu | Qi Li
Source: Journal of Physics D Applied Physics (article, 2023-10-26)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Inverse design of electromagnetically induced transparency metamaterials based on generative adversarial networks Abstract The traditional metamaterial design process usually relies on some knowledge experience and simulation tools to continuously optimize by trial and error, until the simulation results meet the requirements. But this trial-and-error approach could be more unstable and time-consuming, especially when there are too many material parameters or the optimization interval is too large. This paper proposes a multi-prediction model for metamaterials, Improved-StarGan based on StarGan with semi-supervised learning, and use an EIT structure as a validation object. The generator can output various material structures according to the input spectrum extremes, and the discriminator can forward predict the spectrum extremes based on the input material structure parameters. Spectral normalization, gradient penalty, and hidden space distance regularization are also used to increase the diversity of its output data at the expense of sacrificing a part of the accuracy of the generator. During model training, the loss values of the training and validation sets converge normally and end up in a small range. Finally, the data was extracted from the test set for model prediction and simulation comparison. Meanwhile, a sample of one of the predicted structures is tested. All the results show that the model predictions have low error and high confidence. the results demonstrate that the method is effective in both inverse multiple structure and forward prediction of metamaterials, which provides a new design idea for the structural design of metamaterials. Discriminator ; Computer science ; Metamaterial ; Regularization (linguistics) ; Inverse ; Normalization (sociology) ; Algorithm ; Generator (circuit theory) ; Artificial intelligence ; Mathematics ; Physics ; Optics ; Detector Metamaterials and Metasurfaces Applications ; Animal Vocal Communication and Behavior ; Photonic Crystals and Applications
Authors: Öznur Özaltın
Source:  (article, 2023-01-01)
Field: Chemistry — Analytical Chemistry

Comparison of Support Vector Machines and ShuffleNet for Detection of Rice Species The objective of the current investigation is to identify the optimal approach for the automated identification of rice species based on images. Two types of datasets have been utilized. The initial dataset comprises a total of 75,000 images, including five different rice species, namely Arborio, Basmati, Ipsala, Jasmine, and Karacadag. The dataset is a balanced set comprising 15,000 images for each type. During this dataset's analysis phase, ShuffleNet, one of the pre-trained architectures in Convolutional Neural Networks (CNNs), was used. The second dataset was created by extracting features from the same rice images. 106 distinct features were acquired, which include morphological, shape, and color features as the main features. The previously extracted features have been analyzed for the classification of rice species using Support Vector Machines (SVM), which have a quadratic kernel function. Moreover, the two datasets have been obtained from the URL https://www.muratkoklu.com/datasets/. Additionally, 5- fold cross-validation has been applied for both ShuffleNet and SVM to avoid overfitting. Based on the empirical findings, ShuffleNet has achieved an accuracy rate of 99.8%, while SVM has acquired an accuracy rate of 99.9%. While the results exhibit minimal differences, the optimal algorithm choice may be contingent upon the researcher's level of proficiency in the field. Overfitting ; Support vector machine ; Computer science ; Pattern recognition (psychology) ; Artificial intelligence ; Kernel (algebra) ; Identification (biology) ; Set (abstract data type) ; Artificial neural network ; Mathematics ; Biology ; Ecology Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Identification and Quantification in Food
Authors: Aimee Sheehan | Tatsiana Mikulchyk | Catherine S. P. De Castro | Safakath Karuthedath | Wejdan Althobaiti | Metodej Dvoracek | Gul Sabad-e- | Hugh J. Byrne | Frédéric Laquai | Izabela Naydenova | Mikhail A. Filatov
Source: ChemRxiv (preprint, 2023-07-26)
Field: Materials Science — Materials Chemistry

Diethoxycarbonyl-BODIPYs as heavy-atom-free photosensitizers for holographic recording in cellulose acetate photopolymer A series of new heavy-atom-free photosensitizers using 2,6-diethoxycarbonyl-BODIPY was designed and synthesized. Photoinduced electron transfer between the BODIPY and meso-aryl subunits followed by the formation of BODIPY triplet excited states via spin-orbit charge transfer intersystem crossing (SOCT-ISC) was studied by steady-state and ultrafast pump-probe transient optical spectroscopy. Highly efficient photosensitization was observed for dyads bearing pyrene and anthracene substituents, which exhibited singlet oxygen generation with quantum yield of up to 94%. Notably, charge transfer and ISC were observed in non-polar solvent (toluene) due to the increased electron accepting ability of the diethoxycarbonyl-BODIPY as compared to alkyl-substituted BODIPY scaffold. Studied dyads were used as photosensitizers for creation of volume phase transmission gratings in a photopolymerizable material based on cellulose acetate - polyethylene glycol (CA-PEG) matrix. In combination with N-phenylglycin (NPG) as a co-initiator, new BODIPYs showed the ability to initiate a free-radical polymerization of acrylamide monomers under 532 nm irradiation. This allowed for holographic recording of diffractive structures with diffraction efficiency of up to 56% obtained for CA-PEG layers with BODIPY-pyrene dyad as compared to a reference heavy-atom-containing diiodo-BODIPY dye (27%). The materials sensitized with diethoxycarbonyl-BODIPYs showed refractive index modulation of up to 2.3 × 10-3 during holographic recording at the spatial frequency of 800 lines/mm which demonstrate the potential of SOCT-ISC photosensitizers in photopolymerization and holographic recording applications. BODIPY ; Photochemistry ; Triphenylamine ; Chemistry ; Photopolymer ; Atom-transfer radical-polymerization ; Materials science ; Photosensitizer ; Monomer ; Fluorescence ; Polymer ; Organic chemistry ; Optics Porphyrin and Phthalocyanine Chemistry ; Liquid Crystal Research Advancements ; Luminescence and Fluorescent Materials
Authors: Dabin Lee | H. G. Yoon | S. M. Park | Jun Woo Choi | G. Chen | Hee Young Kwon | C. Won
Source: Scientific Reports (article, 2023-07-17)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Super-resolution of magnetic systems using deep learning We construct a deep neural network to enhance the resolution of spin structure images formed by spontaneous symmetry breaking in the magnetic systems. Through the deep neural network, an image is expanded to a super-resolution image and reduced to the original image size to be fitted with the input feed image. The network does not require ground truth images in the training process. Therefore, it can be applied when low-resolution images are provided as training datasets, while high-resolution images are not obtainable due to the intrinsic limitation of microscope techniques. To show the usefulness of the network, we train the network with two types of simulated magnetic structure images; one is from self-organized maze patterns made of chiral magnetic structures, and the other is from magnetic domains separated by walls that are topological defects of the system. The network successfully generates high-resolution images highly correlated with the exact solutions in both cases. To investigate the effectiveness and the differences between datasets, we study the network's noise tolerance and compare the networks' reliabilities. The network is applied with experimental data obtained by magneto-optical Kerr effect microscopy and spin-polarized low-energy electron microscopy. Computer science ; Artificial intelligence ; Data science Magnetic Properties and Applications ; Characterization and Applications of Magnetic Nanoparticles ; Non-Destructive Testing Techniques
Authors: Sascha Jähnigen
Source: Angewandte Chemie (article, 2023-04-18)
Field: Chemistry — Spectroscopy

Vibrational Circular Dichroism Spectroscopy of Chiral Molecular Crystals: Insights from Theory Abstract Chirality is a curious phenomenon that appears in various forms. While the concept of molecular (RS‐)chirality is ubiquitous in chemistry, there are also more intricate forms of structural chirality. One of them is the enantiomorphism of crystals, especially molecular crystals, that describes the lack of mirror symmetry in the unit cell. Its relation to molecular chirality is not obvious, but still an open question, which can be addressed with chiroptical tools. Vibrational circular dichroism (VCD) denotes chiral infrared (IR) spectroscopy that is susceptible to both, the molecular as well as the intermolecular space by means of vibrational transitions. When carried out in the solid state, VCD delivers a very rich set of non‐local contributions that are determined by crystal packing and collective motion. Since its discovery in the 1970s, VCD has become the method of choice for the determination of absolute configurations, but its applicability reaches beyond towards the study of different crystal forms and polymorphism. This brief review summarises the theoretical concepts of crystal chirality and how computations of solid‐state VCD can shed light into the intimate connection of chiral structure and vibrational optical activity. Chirality (physics) ; Vibrational circular dichroism ; Chemistry ; Circular dichroism ; Chemical physics ; Intermolecular force ; Spectroscopy ; Infrared spectroscopy ; Crystal (programming language) ; Absolute configuration ; Axial chirality ; Crystallography ; Molecule ; Computational chemistry ; Physics ; Stereochemistry ; Enantioselective synthesis ; Symmetry breaking ; Chiral symmetry breaking ; Quantum mechanics ; Organic chemistry Molecular spectroscopy and chirality ; Spectroscopy and Quantum Chemical Studies ; Axial and Atropisomeric Chirality Synthesis
Authors: Abhijit Biswas | Rui Xu | Gustavo A. Alvarez | Jin Zhang | Joyce Christiansen‐Salameh | Anand B. Puthirath | Kory Burns | Jordan A. Hachtel | Tao Li | Sathvik Ajay Iyengar | Tia Gray | Chenxi Li | Xiang Zhang | Harikishan Kannan | Jacob Elkins | Tymofii S. Pieshkov | Róbert Vajtai | A. Glen Birdwell | Mahesh R. Neupane | Elias Garratt | Tony Ivanov | Bradford B. Pate | Yuji Zhao | Hanyu Zhu | Zhiting Tian | Ángel Rubio | Pulickel M. Ajayan
Source: arXiv (Cornell University) (preprint, 2023-04-24)
Field: Materials Science — Materials Chemistry

Non-linear optics at twist interfaces in h-BN/SiC heterostructures Understanding the emergent electronic structure in twisted atomically thin layers has led to the exciting field of twistronics. However, practical applications of such systems are challenging since the specific angular correlations between the layers must be precisely controlled and the layers have to be single crystalline with uniform atomic ordering. Here, we suggest an alternative, simple and scalable approach where nanocrystalline two-dimensional (2D) film on three-dimensional (3D) substrates yield twisted-interface-dependent properties. Ultrawide-bandgap hexagonal boron nitride (h-BN) thin films are directly grown on high in-plane lattice mismatched wide-bandgap silicon carbide (4H-SiC) substrates to explore the twist-dependent structure-property correlations. Concurrently, nanocrystalline h-BN thin film shows strong non-linear second-harmonic generation and ultra-low cross-plane thermal conductivity at room temperature, which are attributed to the twisted domain edges between van der Waals stacked nanocrystals with random in-plane orientations. First-principles calculations based on time-dependent density functional theory manifest strong even-order optical nonlinearity in twisted h-BN layers. Our work unveils that directly deposited 2D nanocrystalline thin film on 3D substrates could provide easily accessible twist-interfaces, therefore enabling a simple and scalable approach to utilize the 2D-twistronics integrated in 3D material devices for next-generation nanotechnology. Materials science ; Nanocrystalline material ; Heterojunction ; Thin film ; van der Waals force ; Optoelectronics ; Band gap ; Nanotechnology ; Silicon carbide ; Condensed matter physics ; Composite material ; Physics Thermal properties of materials ; Graphene research and applications ; Boron and Carbon Nanomaterials Research
Authors: Stephanie Thibert | Deseree Reid | Jesse Wilson | Rohith Varikoti | Natalia Maltseva | Katherine Schultz | Agustin Kruel | G. Babnigg | A. Joachimiak | Neeraj Kumar | Mowei Zhou
Source: ChemRxiv (preprint, 2023-09-04)
Field: Chemistry — Spectroscopy

Native Mass Spectrometry Dissects the Structural Dynamics of an Allosteric Heterodimer of SARS-CoV-2 Nonstructural Proteins Structure-based drug design, which relies on precise understanding of the target protein and its interaction with the drug candidate, is dramatically expedited by advances in computational methods for candidate prediction. Yet, the accuracy needs to be improved with more structural data from high throughput experiments, which are challenging to generate, especially for dynamic and weak associations. Herein, we applied native mass spectrometry (native MS) to rapidly characterize ligand binding of an allosteric heterodimeric complex of SARS-CoV-2 two nonstructural proteins (nsp) nsp10 and nsp16 (nsp10/16). Native MS showed that the dimer is in equilibrium with monomeric states in solution. Consistent with literature, well characterized small co-substrate, RNA substrate and product bind with high specificity and affinity to the dimer but not the free monomers. Unsuccessfully designed ligands bind indiscriminately to all forms. Using neutral gas collision, the nsp16 monomer with bound co-substrate can be released from the holo dimer complex, confirming the binding to nsp16 as revealed by the crystal structure. However, an unusual migration of the endogenous zinc ions bound to nsp10 to nsp16 after collisional dissociation was observed, and can be suppressed using an alternative surface collision method at reduced precursor charge states. This highlighted the importance of careful optimization of experimental techniques. Overall, with minimal sample input (~µg), native MS can rapidly detect ligand binding affinities and locations in dynamic multi-subunit protein complexes, demonstrating the potential of an “all-in-one” native MS assay for rapid structural profiling of protein-to-AI-based compound systems to expedite drug discovery. Allosteric regulation ; Dimer ; Chemistry ; Protein subunit ; Ligand (biochemistry) ; Monomer ; Drug discovery ; Ion-mobility spectrometry ; Molecular dynamics ; Binding site ; Mass spectrometry ; Biophysics ; Stereochemistry ; Biochemistry ; Biology ; Computational chemistry ; Enzyme ; Chromatography Mass Spectrometry Techniques and Applications ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Mohammed Amine Belyamna | A. Guedri | Abdelhalim Aiiaoui | Chouaib Zeghida
Source: Acta Mechanica Slovaca (article, 2023-12-16)
Field: Materials Science — Metals and Alloys

Enhancing Piping System Reliability Through Material Upgrades and ANN-Based Damage Parameter Estimation The objective of this study is to enhance the longevity of damaged or defective components through necessary repairs. In corrosive environments, stainless steels, such as 304 and 316NG austenitic stainless steel (SS), are preferred due to their chemical composition. Notably, 316SS contains a higher molybdenum content, resulting in improved resistance to pitting and crevice corrosion. The simulation of intergranular stress corrosion cracking (IGSCC) in SS piping relies on factors like applied and residual stresses, environmental conditions, and sensitization degree. To understand crack growth rates and times-to-initiation for each material, "damage parameters (DPs)" are utilized. These DPs consolidate the individual influences of various parameters. To estimate the DPs an artificial neuronal network (ANN) is proposed in this work. The ANN serves as a tool for predicting the DPs based on the given inputs. The obtained results are then utilized in numerical simulations to assess crack growth rates, times-to-initiation, and reliability for damaged 304SS and 316SS. Finally, this paper investigates the impact of replacing old 304 material with new 316NG material on piping reliability. By examining the effects of this replacement, the study aims to provide insights into how the reliability of the piping can be improved through material upgrades. Piping ; Reliability (semiconductor) ; Reliability engineering ; Estimation ; Estimation theory ; Environmental science ; Computer science ; Engineering ; Forensic engineering ; Systems engineering ; Environmental engineering ; Physics ; Algorithm Hydrogen embrittlement and corrosion behaviors in metals ; Non-Destructive Testing Techniques ; Fatigue and fracture mechanics
Authors: Francesca Venturini | Silvan Fluri | Manas Mejari | Michael Baumgartner | Dario Piga | Umberto Michelucci
Source: arXiv (Cornell University) (preprint, 2023-09-21)
Field: Chemistry — Organic Chemistry

Shedding Light on the Ageing of Extra Virgin Olive Oil: Probing the Impact of Temperature with Fluorescence Spectroscopy and Machine Learning Techniques This work systematically investigates the oxidation of extra virgin olive oil (EVOO) under accelerated storage conditions with UV absorption and total fluorescence spectroscopy. With the large amount of data collected, it proposes a method to monitor the oil's quality based on machine learning applied to highly-aggregated data. EVOO is a high-quality vegetable oil that has earned worldwide reputation for its numerous health benefits and excellent taste. Despite its outstanding quality, EVOO degrades over time owing to oxidation, which can affect both its health qualities and flavour. Therefore, it is highly relevant to quantify the effects of oxidation on EVOO and develop methods to assess it that can be easily implemented under field conditions, rather than in specialized laboratories. The following study demonstrates that fluorescence spectroscopy has the capability to monitor the effect of oxidation and assess the quality of EVOO, even when the data are highly aggregated. It shows that complex laboratory equipment is not necessary to exploit fluorescence spectroscopy using the proposed method and that cost-effective solutions, which can be used in-field by non-scientists, could provide an easily-accessible assessment of the quality of EVOO. Fluorescence spectroscopy ; Olive oil ; Spectroscopy ; Process engineering ; Quality (philosophy) ; Fluorescence ; Computer science ; Exploit ; Environmental science ; Health benefits ; Biochemical engineering ; Biological system ; Chemistry ; Engineering ; Food science ; Physics ; Biology Edible Oils Quality and Analysis ; Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies