jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Fiona Yu | Jorge L. Gálvez Vallejo | Giuseppe M. J. Barca
Source: Journal of Cheminformatics (article, 2024-08-19)
Field: Chemistry — Spectroscopy

Automatic molecular fragmentation by evolutionary optimisation Molecular fragmentation is an effective suite of approaches to reduce the formal computational complexity of quantum chemistry calculations while enhancing their algorithmic parallelisability. However, the practical applicability of fragmentation techniques remains hindered by a dearth of automation and effective metrics to assess the quality of a fragmentation scheme. In this article, we present the Quick Fragmentation via Automated Genetic Search (QFRAGS), a novel automated fragmentation algorithm that uses a genetic optimisation procedure to generate molecular fragments that yield low energy errors when adopted in Many Body Expansions (MBEs). Benchmark testing of QFRAGS on protein systems with less than 500 atoms, using two-body (MBE2) and three-body (MBE3) MBE calculations at the HF/6-31G* level, reveals mean absolute energy errors (MAEE) of 20.6 and 2.2 kJ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mtext>mol</mml:mtext> <mml:mrow><mml:mo>-</mml:mo> <mml:mn>1</mml:mn></mml:mrow> </mml:msup> </mml:math> , respectively. For larger protein systems exceeding 500 atoms, MAEEs are 181.5 kJ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mtext>mol</mml:mtext> <mml:mrow><mml:mo>-</mml:mo> <mml:mn>1</mml:mn></mml:mrow> </mml:msup> </mml:math> for MBE2 and 24.3 kJ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mtext>mol</mml:mtext> <mml:mrow><mml:mo>-</mml:mo> <mml:mn>1</mml:mn></mml:mrow> </mml:msup> </mml:math> for MBE3. Furthermore, when compared to three manual fragmentation schemes on a 40-protein dataset, using both MBE and Fragment Molecular Orbital techniques, QFRAGS achieves comparable or often lower MAEEs. When applied to a 10-lipoglycan/glycolipid dataset, MAEs of 7.9 and 0.3 kJ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mtext>mol</mml:mtext> <mml:mrow><mml:mo>-</mml:mo> <mml:mn>1</mml:mn></mml:mrow> </mml:msup> </mml:math> were observed at the MBE2 and MBE3 levels, respectively.Scientific Contribution This Article presents the Quick Fragmentation via Automated Genetic Search (QFRAGS), an innovative molecular fragmentation algorithm that significantly improves upon existing molecular fragmentation approaches by specifically addressing their lack of automation and effective fragmentation quality metrics. With an evolutionary optimisation strategy, QFRAGS actively pursues high quality fragments, generating fragmentation schemes that exhibit minimal energy errors on systems with hundreds to thousands of atoms. The advent of QFRAGS represents a significant advancement in molecular fragmentation, greatly improving the accessibility and computational feasibility of accurate quantum chemistry calculations. Fragmentation (computing) ; Computer science ; Data science ; Computational biology ; Biology Mass Spectrometry Techniques and Applications ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Ömer Dilek
Source: Bitlis Eren Üniversitesi Fen Bilimleri Dergisi (article, 2024-03-20)
Field: Chemistry — Organic Chemistry

Imidazole Based Novel Schiff Base: Synthesis, Characterization, Quantum Chemical Calculations, In Silico Investigation of ADMEt Properties and Molecular Docking Simulations against VEGFR2 Protein The potential drug candidate novel Schiff base, 2-(((3-(4-methyl-1H-imidazol-1-yl)-5-(trifluoromethyl)phenyl)imino)methyl)phenol (MITPIM) was synthesized by the reaction of salicylaldehyde and 3-(4-methyl-1H-imidazol-1-yl)-5-(trifluoromethyl)aniline which is the precursor of the nilotinib molecule used in the cancer treatment. It was characterizated by using spectroscopic techniques such as 1H-NMR, 13C-NMR, 19F-NMR, FT-IR and UV-Vis. DFT computational technique was used for further investigation. DFT/B3LYP method and the 6-311G(d,p) basis set were used to determine optimized geometry. Then by using optimized geometry and DFT approach three-dimensional molecular electrostatic potential (MEP), vibration frequencies, NMR chemical shift values, HOMOs-LUMOs and molecular orbital energies were calculated. It was observed that the experimental and theoretical datas were in good agreement. The ADME and toxicity properties were investigated by using online servers. According to the results, it was concluded that the MITPIM has low toxicity and high oral bioavailability. Molecular docking simulations of the MITPIM with VEGFR2 protein (PDB ID: 2XIR) were investigated. According to molecular docking studies, the binding energy of the complex formed by the MITPIM with VEGFR2 protein (PDB ID: 2XIR) was −9.34 kcal/mol and the value was close to nilotinib’s binding score which was -9.69 kcal/mol. Molecular docking and ADMEt results shown that the newly synthesized MITPIM has the potential to be drug. Chemistry ; Schiff base ; Docking (animal) ; Computational chemistry ; Carbon-13 NMR ; Proton NMR ; Basis set ; Imidazole ; ADME ; Stereochemistry ; Density functional theory Synthesis and biological activity ; Synthesis and Characterization of Heterocyclic Compounds ; Metal complexes synthesis and properties
Authors: Shuyun Yao | Feike Zhang | Shiyu Wang | Yuanming Liu | Weijie Fu | Yingjie Ji | Kang Ji | H. J. Yang | Ruilong Liu | Xiaoke Li | Zhiyu Yang | Yi‐Ming Yan
Source: Chemistry - A European Journal (article, 2024-11-14)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Spin‐Electrochemistry of Transition Metal Oxides for Energy Storage: Concepts, Advances and Perspectives Developing high-capacity and cyclically stable transition metal (TM)-based electrode materials for energy storage devices, such as aqueous ion energy storage systems, is crucial for addressing the growing issue of energy scarcity. The spin state, or spin configuration of the d-electrons, plays a vital role in the electrochemical energy storage performance of these materials. However, there has been a lack of systematic descriptions regarding the role of spin configurations in electrochemical energy storage to date. This review aims to elucidate the advantages of controlling the spin states of metal centers to enhance energy storage performance and highlights recent progress in employing spin state regulation in electrochemical energy storage. Additionally, it covers the various characterization techniques used to determine spin states. Finally, we discuss the future prospects and challenges within this emerging field, with the aim of accelerating the development of spin-based electrochemical energy storage technologies. This review also seeks to provide clear and reliable directions for the design and preparation of novel energy storage materials. Energy storage ; Electrochemical energy storage ; Nanotechnology ; Electrochemistry ; Spin (aerodynamics) ; Materials science ; Electrochemical energy conversion ; Spin transition ; Engineering physics ; Electrode ; Chemistry ; Supercapacitor ; Physics ; Mechanical engineering ; Engineering ; Condensed matter physics ; Power (physics) Supercapacitor Materials and Fabrication ; Advanced battery technologies research ; Electrocatalysts for Energy Conversion
Authors: Monika Dubey | Jyoti Sharma | Richa Krishna | Vipin Chawla | Subhasha Nigam | Monika Joshi
Source: 3 Biotech (article, 2024-11-29)
Field: Materials Science — Materials Chemistry

Algae-synthesized cerium oxide nanoparticles for antibiotic degradation in water and subsequent bioenergy production Chlorella sorokiniana ; Photocatalysis ; Biomass (ecology) ; Degradation (telecommunications) ; Cerium oxide ; Bioenergy ; Algae ; Chemistry ; Chlorella ; Nanoparticle ; Raw material ; Biofuel ; Nuclear chemistry ; Pulp and paper industry ; Food science ; Catalysis ; Botany ; Materials science ; Agronomy ; Biology ; Nanotechnology ; Biotechnology ; Organic chemistry Advanced Nanomaterials in Catalysis ; Advanced Photocatalysis Techniques ; Nanomaterials for catalytic reactions
Authors: Ashah M. Gould | Danielle Schalk | Molly E. Fleagle | Kraig A. Wheeler
Source: Crystal Growth & Design (article, 2024-04-15)
Field: Chemistry — Physical and Theoretical Chemistry

Benzoyl Valine Quasiracemates: Pairing CF<sub>3</sub> Quasienantiomers with H to <i>t</i>-Butyl Understanding the interplay of structural features responsible for molecular assembly is essential for molecular crystal engineering. When assembling molecules with encoded motifs, <i>first choice</i> supramolecular strategies almost always include robust directional nonbonded contacts. Quasiracemic materials, considered near racemates since cocrystallization occurs with chemically unique components, lack a molecular framework or functional group restrictions, highlighting the importance of molecular shape to molecular assembly. Recently, our group reported quasiracemates derived from benzoyl leucine/phenylalanine derivatives with two points of chemical difference. In this study, we modified the chemical framework with valine and increased the scope of the work by imposing a larger variance in the side chain substituents. Pairing a CF<sub>3</sub> component with quasienantiomers that differ iteratively from hydrogen to <i>t</i>-butyl offers an important view into the supramolecular landscape of these materials. Single-crystal X-ray crystallography and lattice energy assessments, coupled with conformational and crystal structure similarity searches, show an elevated degree of isomorphism for many of the targeted 17 racemates and quasiracemates. These benzoyl amino acid molecular architectures create extended hydrogen-bond patterns in the crystal that provide enhanced opportunities to study the shape space and molecular recognition profiles for a diverse family of quasienantiomeric components. Pairing ; Valine ; Chemistry ; Stereochemistry ; Crystallography ; Medicinal chemistry ; Physics ; Amino acid ; Condensed matter physics Crystallography and molecular interactions ; Fluorine in Organic Chemistry ; Molecular Sensors and Ion Detection
Authors: Bharath Sampath Kumar
Source: ChemRxiv (preprint, 2024-01-28)
Field: Chemistry — Spectroscopy

Recent advancement and applications of mass spectrometry imaging Analysis concerning the spatial distribution of biomolecules in complex surfaces can be accomplished with mass spectrometry imaging [MSI]. The in situ direct determination of the abundance of lipids, peptides, proteins, and metabolites in segments of tissues enables MSI to be an effective technique. Molecule-specific visualization can be accomplished utilizing a variety of ionization techniques, each of which generates data with great spatial and mass accuracy and is suitable for a particular application. A chemical microscope that may be utilized for straightforward biomolecular assessment of histopathological tissue surfaces is generated through the integration of molecular classification with regional assessment. MSI effectively enables label-free identification and mapping of a variety of biological compounds, the presence or absence of which may be an obvious indication of disease pathogenesis. The MSI protocol's several phases must be carefully adhered to if one wants to detect the target analytes with the necessary spatial resolution. When combined with other imaging modalities, MSI can be used to ascertain the connection between changes in the spatial distribution of essential chemicals and other differences in the properties of the tissue. The findings of the examined empirical research illustrate how MSI represents a viable experimental approach with an assortment of applications. The paper will concentrate on technical developments, applications, challenges, and MSI's prospects moving forward. Mass spectrometry imaging ; Mass spectrometry ; Chemistry ; Computer science ; Chromatography Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Pesticide Residue Analysis and Safety
Authors: Marija M. Vuksanović | Ivana O. Mladenović | Stevan Stupar | Аleksandar Marinković | Radmila Jančić Heinemann
Source: Polymers and Polymer Composites (article, 2024-01-01)
Field: Materials Science — Polymers and Plastics

Microhardness measurement optimization in green derived silica/polyester composites using response surface methodology Polymer composites based on unsaturated polyester resin (UPR) and reinforced with particles based on unmodified/modified plant provenance biosilica particles were synthesized and characterized. An unsaturated polyester resin was obtained from waste poly (ethylene terephthalate (PET). Biosilaca particles are made from rice husk biomass. The surface of the produced silica particles was modified using three different silanes: 3-trimethoxysilylpropyl methacrylate (MEMO), trimethoxyvinylsilane (TMEVS), and 3-aminopropyltrimethoxysilane (APTMS). The microhardness test method was used to investigate the mechanical properties of synthesized composite material with variations in dwell times and applied loads. Optimization of composite microhardness value prediction in function of synthesized parameters (type of modification of silica particles) and measurement parameters (applied loads and dwell times) was done using the method of response surface methodology (RSM) regression analysis. The maximal microhardness values (0.459 GPa) were obtained of type modification of silica particles with vinyl with 80% confidence for 120 experimental variables. This method can be used to choose the optimal dwell time and load for comparison of measurements between different composite materials and to enable the choice of the material in terms of optimization of the quality of reinforcement and quality of interphase determined by surface modification. Materials science ; Composite material ; Response surface methodology ; Indentation hardness ; Dwell time ; Polyester ; Composite number ; Central composite design ; Surface modification ; Polyester resin ; Chemical engineering ; Mathematics ; Microstructure Polymer Nanocomposites and Properties ; Natural Fiber Reinforced Composites ; Tribology and Wear Analysis
Authors: Ryo Hamano | Naoki Tanaka | Tsuyohiko Fujigaya
Source: Materials Advances (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Size exclusion chromatography-based length sorting of single-walled carbon nanotubes stably coated with cross-linked polymers The remarkable stability of gel-coated SWCNT dispersions enables length sorting using size exclusion chromatography. Length-sorted, gel-coated SWCNTs show photoluminescence in near IR and are ready to use for various applications including near IR imaging. Size-exclusion chromatography ; Carbon nanotube ; Polymer ; Sorting ; Materials science ; Gel permeation chromatography ; Nanotechnology ; Photoluminescence ; Chemistry ; Organic chemistry ; Optoelectronics ; Composite material ; Computer science Carbon Nanotubes in Composites ; Mechanical and Optical Resonators ; Graphene research and applications
Authors: L. Askew | Aimee Sweeney | David Cox | Maxim Shkunov
Source: Advanced Materials Interfaces (article, 2024-07-01)
Field: Materials Science — Polymers and Plastics

Toward Full‐Color Vision Restoration: Conjugated Polymers as Key Functional Materials in Artificial Retinal Prosthetics Abstract For the prosthetic retina, a device replacing dysfunctional cones and rods, with the ability to mimic the spectral response properties of these photoreceptors and provide electrical stimulation signals to activate residual visual pathways, can relay sufficient data to the brain for interpretation as color vision. Organic semiconductors including conjugated polymers with four different bandgaps providing wavelength‐specific electrical responses are ideal candidates for potential full‐color vision restoration. Here, conjugated polymer photocapacitor devices immersed in electrolyte are demonstrated to elicit a photovoltage measured by a Ag/AgCl electrode 100 microns from the device of ≈−40 mV for 15–39 µW mm −2 of incident light power density at three wavelengths: 405 nm for blue photoreceptor candidate material, 534 nm for green, 634 nm for red. Photoresponse is substantially improved by introducing polymer donor/acceptor molecules bulk heterojunctions. Devices with bulk heterojunction configurations achieved at least −70 mV for green candidates with the highest at −200 mV for red cone candidates. These findings highlight the potential for organic materials to bridge the gap toward natural vision restoration for retinal dystrophic conditions such as age‐related macular degeneration, Stargardt disease, or retinitis pigmentosa and contribute to the ongoing advancements in visual prosthetic devices. Materials science ; Optoelectronics ; Visual prosthesis ; Retinitis pigmentosa ; Retinal implant ; Polymer ; Conjugated system ; Optics ; Nanotechnology ; Retina ; Composite material Conducting polymers and applications ; Neuroscience and Neural Engineering ; Advanced Memory and Neural Computing
Authors: Tsung‐Shine Ko | H. H. Hsieh | Chi Lee | Szu-Hung Chen | Wei‐Chun Chen | Wei–Lin Wang | Yang‐Wei Lin | Sean Wu
Source: Nanomaterials (article, 2024-11-20)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Electric Field-Enhanced SERS Detection Using MoS2-Coated Patterned Si Substrate with Micro-Pyramid Pits This study utilized semiconductor processing techniques to fabricate patterned silicon (Si) substrates with arrays of inverted pyramid-shaped micro-pits by etching. Molybdenum trioxide (MoO<sub>3</sub>) was then deposited on these patterned Si substrates using a thermal evaporation system, followed by two-stage sulfurization in a high-temperature furnace to grow MoS<sub>2</sub> thin films consisting of only a few atomic layers. During the dropwise titration of Rhodamine 6G (R6G) solution, a longitudinal electric field was applied using a Keithley 2400 (Cleveland, OH, USA) source meter. Raman mapping revealed that under a 100 mV condition, the analyte R6G molecules were effectively confined within the pits. Due to its two-dimensional structure, MoS<sub>2</sub> provides a high surface area and supports a surface-enhanced Raman scattering (SERS) charge transfer mechanism. The SERS results demonstrated that the intensity in the pits of the few-layer MoS<sub>2</sub>/patterned Si SERS substrate was approximately 274 times greater compared to planar Si, with a limit of detection reaching 10<sup>-5</sup> M. The experimental results confirm that this method effectively resolves the issue of random distribution of analyte molecules during droplet evaporation, thereby enhancing detection sensitivity and stability. Substrate (aquarium) ; Materials science ; Pyramid (geometry) ; Electric field ; Nanotechnology ; Optoelectronics ; Optics Gold and Silver Nanoparticles Synthesis and Applications ; Advanced biosensing and bioanalysis techniques ; Quantum Dots Synthesis And Properties
Authors: Andres Correa Hernandez | Claire Gmachl
Source: APL Machine Learning (article, 2024-09-01)
Field: Chemistry — Spectroscopy

A machine learning framework for quantum cascade laser design A multi-layer perceptron neural network was used to predict the laser transition figure of merit, a measure of the laser threshold gain, of over 900 × 106 Quantum Cascade (QC) laser designs using only layer thicknesses and the applied electric field as inputs. Designs were generated by randomly altering the layer thicknesses of an initial 10-layer design. Validating the predictions with our 1D Schrödinger solver, the predicted values show 5%–15% error for the laser structures, well within QC laser design variations. The algorithm (i) allowed for the identification of high figure of merit structures, (ii) recognized which layers should be altered to maximize the figure of merit at a given electric field, and (iii) increased the original design figure of merit of 94.7–141.2 eV ps Å2, a 1.5-fold improvement and significant for QC lasers. The computational time for laser design data collection is greatly reduced from 32 h for 27 000 designs using our 1D Schrödinger solver on a virtual machine, to 8 h for 907 × 106 designs using the machine learning algorithm on a laptop computer. Cascade ; Quantum cascade laser ; Quantum ; Laser ; Computer science ; Artificial intelligence ; Physics ; Engineering ; Optics ; Quantum mechanics ; Chemical engineering Spectroscopy and Laser Applications ; Laser Design and Applications ; Semiconductor Lasers and Optical Devices
Authors: Jack Thomas | William J. Baldwin | Gábor Csányi | Christoph Ortner
Source: arXiv (Cornell University) (preprint, 2024-06-16)
Field: Materials Science — Materials Chemistry

Self-consistent Coulomb interactions for machine learning interatomic potentials A ubiquitous approach to obtain transferable machine learning-based models of potential energy surfaces for atomistic systems is to decompose the total energy into a sum of local atom-centred contributions. However, in many systems non-negligible long-range electrostatic effects must be taken into account as well. We introduce a general mathematical framework to study how such long-range effects can be included in a way that (i) allows charge equilibration and (ii) retains the locality of the learnable atom-centred contributions to ensure transferability. Our results give partial explanations for the success of existing machine learned potentials that include equilibriation and provide perspectives how to design such schemes in a systematic way. To complement the rigorous theoretical results, we describe a practical scheme for fitting the energy and electron density of water clusters. Coulomb ; Physics ; Statistical physics ; Quantum mechanics ; Electron Machine Learning in Materials Science
Authors: Yili Wang | Kaixiong Zhou | Ninghao Liu | Ying Wang | Xin Wang
Source: arXiv (Cornell University) (preprint, 2024-06-19)
Field: Materials Science — Materials Chemistry

Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models Sharpness-aware minimization (SAM) has received increasing attention in computer vision since it can effectively eliminate the sharp local minima from the training trajectory and mitigate generalization degradation. However, SAM requires two sequential gradient computations during the optimization of each step: one to obtain the perturbation gradient and the other to obtain the updating gradient. Compared with the base optimizer (e.g., Adam), SAM doubles the time overhead due to the additional perturbation gradient. By dissecting the theory of SAM and observing the training gradient of the molecular graph transformer, we propose a new algorithm named GraphSAM, which reduces the training cost of SAM and improves the generalization performance of graph transformer models. There are two key factors that contribute to this result: (i) \textit{gradient approximation}: we use the updating gradient of the previous step to approximate the perturbation gradient at the intermediate steps smoothly (\textbf{increases efficiency}); (ii) \textit{loss landscape approximation}: we theoretically prove that the loss landscape of GraphSAM is limited to a small range centered on the expected loss of SAM (\textbf{guarantees generalization performance}). The extensive experiments on six datasets with different tasks demonstrate the superiority of GraphSAM, especially in optimizing the model update process. The code is in:https://github.com/YL-wang/GraphSAM/tree/graphsam Transformer ; Minification ; Computer science ; Graph ; Algorithm ; Mathematical optimization ; Theoretical computer science ; Mathematics ; Electrical engineering ; Voltage ; Engineering Machine Learning in Materials Science ; Molecular Junctions and Nanostructures ; CO2 Reduction Techniques and Catalysts