jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Hüseyin Yıldırım | Haydar Arslan
Source: Karaelmas Science and Engineering Journal (article, 2021-12-15)
Field: Materials Science — Materials Chemistry

38 Atomlu Ni-Pt-Cu Üçlü Nanoalaşımlarının Yapısal ve Dinamik Özellikleri Bu çalışmada, Ni6PtnCu32-n (n=0-32) üçlü nanoalaşımların global optimizasyonları atomlar arası etkileşmeler Gupta çok cisim potansiyeli ile modellenerek ve Basin-Hopping algoritması kullanılarak gerçekleştirilmiştir. Nanoalaşımların kararlılığı fazlalık enerji analizi ve bağ sayısı analizi ile incelenmiştir. Optimizasyon sonucunda elde edilen tüm kompozisyonların global minimum yapıları, Moleküler Dinamik (MD) simülasyonlarında başlangıç konfigürasyonları olarak alınmıştır. Ni6PtnCu32-n (n=0-32) üçlü nanoalaşımlarının erime sıcaklıkları Kanonik topluluk (NVT) koşullarında MD simülasyonları ile incelenmiştir. Erime geçişlerini belirlemek için kalorik eğri ve Lindemann kriteri kullanılmıştır. Ni6PtnCu32-n (n=0-32) üçlü nanoalaşımların MD simülasyonları sonucunda erime sıcaklıklarının kompozisyona bağlı olarak dalgalanmalar gösterdiği tespit edilmiştir. Ayrıca, erime sürecinde optimizasyon sonucunda elde edilen en kararlı kompozisyonların dinamik davranışları Bağ-Açı analizi (BAA) ve kare ortalama yer değiştirmelerin karekökü (RMSD) gibi farklı analiz yöntemleri ile incelenmiştir. Ternary operation ; Atom (system on chip) ; Materials science ; Ternary alloy ; Crystallography ; Chemistry ; Computer science ; Embedded system Catalytic Processes in Materials Science ; Laser-Ablation Synthesis of Nanoparticles
Authors: Matteo Cucchi | Anton Weissbach | Lukas M. Bongartz | Hsin Tseng | Hans Kleemann | Richard Kantelberg | Karl Leo
Source: Research Square (preprint, 2021-12-06)
Field: Materials Science — Polymers and Plastics

Thermodynamics of Organic Electrochemical Transistors Abstract Bioelectronics which bridge the gap between conventional electronics and biological systems are actively researched due to their fascinating perspectives in healthcare and other fields. A key element of future bioelectronics is the organic electrochemical transistor (OECT) that, by employing a mixed ion-electron conducting materials, can perform switching tasks in electrolytic environments and serve as sensoric or actoric element. OECTs differ substantially from their inorganic field-effect counterparts, mainly due to their electrochemical, rather than electrostatic, gate operation principle. However, the working mechanism of OECTs is modeled as the one of the field-effect transistor: this approach not only fails to give quantitative agreement with experimental observation but also ignores the material properties of the channel and the chemical dynamics that stem for the operation of the device. Here, we present a new comprehensive unified model that can explain the behavior of OECTs across a broad range of materials, designs, and operation regimes. We treat the polymeric channel as a thermodynamic binary system and show that the entropy of mixing is the major driving force behind the operation of the OECT. We are able to quantify the entropic and enthalpic interactions between charged species for a variety of materials and solvents and harness this knowledge to provide guidelines for material modeling and insights for device fine-tuning for targeted applications. Finally, our thermodynamic model provides a description of the intrinsic origin of the ubiquitous hysteretic behavior of OECTs. Electrochemistry ; Transistor ; Thermodynamics ; Materials science ; Environmental science ; Chemistry ; Physics ; Electrical engineering ; Engineering ; Electrode ; Physical chemistry ; Voltage Conducting polymers and applications ; Organic Electronics and Photovoltaics ; Advanced Memory and Neural Computing
Authors: Kyle Groden | Fernando D. Vila | Li Li | Simon R. Bare | Susannah L. Scott | Jean‐Sabin McEwen
Source:  (preprint, 2021-09-30)
Field: Materials Science — Surfaces, Coatings and Films

First Principles Approach to Extracting Chemical Information from X-Ray Absorption Near-Edge Spectra of Ga-Containing Materials The X-ray absorption near edge structure (XANES) can provide uniquely detailed information on the coordination environments of important Ga-containing materials with unknown structures, including catalytically-active materials. In this study, the Ga K-edge XANES was simulated using first principles-based methods for seven molecular Ga complexes, as well b-Ga2O3, in order to explore the chemical origins of the experimentally observed features. The theoretical spectra were computed using FEFF, CASTEP and StoBE, in order to assess the sensitivity of the results to the computational approach. While the XANES features depend on the Ga coordination environment, they are also sensitive to the electronegativity of the ligands and the symmetry at Ga. The white line position responds to changes in both the core state (due to differential screening) and the valence “p” states (arising from differences in ligand coordination). XANES ; Valence (chemistry) ; CASTEP ; Electronegativity ; Spectral line ; Materials science ; K-edge ; Absorption spectroscopy ; Coordination number ; Crystallography ; Molecular physics ; Chemistry ; Electronic structure ; Physics ; Computational chemistry ; Optics ; Ion Electron and X-Ray Spectroscopy Techniques ; X-ray Spectroscopy and Fluorescence Analysis ; X-ray Diffraction in Crystallography
Authors: Jessica Wahlers | Jèssica Margalef | Eric Hansen | Armita Bayesteh | Paul Helquist | Montserrat Diéguez | Òscar Pàmies | Olaf Wiest | Per‐Ola Norrby
Source: Research Square (preprint, 2021-06-04)
Field: Chemistry — Inorganic Chemistry

Proofreading Experimentally Assigned Stereochemistry Through Q2MM Predictions in Pd-Catalyzed Allylic Aminations Abstract The palladium-catalyzed enantioselective allylic substitution by carbon or nitrogen nucleophiles is a key transformation that is particularly useful for the synthesis of bioactive compounds. Unfortunately, the selection of a suitable ligand/substrate combination often requires significant screening effort. Here, we show that a transition state force field (TSFF) derived by the quantum-guided molecular mechanics (Q2MM) method can be used to rapidly screen ligand/substrate combinations. Testing of this method on 77 literature reactions revealed several cases where the computationally predicted major enantiomer differed from the one reported. Interestingly, experimental follow-up led to a reassignment of the experimentally observed configuration. This result demonstrates the power of mechanistically based methods to predict and, where necessary, correct the stereochemical outcome. Proofreading ; Allylic rearrangement ; Catalysis ; Chemistry ; Stereochemistry ; Combinatorial chemistry ; Organic chemistry Asymmetric Hydrogenation and Catalysis ; Asymmetric Synthesis and Catalysis ; Chemical Synthesis and Analysis
Authors: Hao Zhou | Shihuan Ren | Yuanming Zhang | and Hai-Guang Zhao
Source: General Chemistry (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Synthesis of Colloidal Carbon Quantum Dots Carbon quantum dots (C-dots) are emerging semiconductor nanomaterials consisting of earth-abundant C, O, and N elements. C-dots have many advantages such as high quantum yield, good photoand chemical-stability, low-cost, low-toxicity and easy synthesis with earth-abundant precursors. In this minireview, we summarized and updated the most recent research works for the synthesis of the fluorescent and phosphorescent C-dots. In the end, we also give our owner views for the challenges and research directions for C-dots. Carbon quantum dots ; Quantum dot ; Carbon fibers ; Nanotechnology ; Colloid ; Materials science ; Chemical engineering ; Engineering ; Composite material ; Composite number Carbon Nanotubes in Composites ; Laser-Ablation Synthesis of Nanoparticles ; Graphene and Nanomaterials Applications
Authors: Emily A. Eikey | Alex M. Maldonado | Charles D. Griego | Guido Falk von Rudorff | John A. Keith
Source: ChemRxiv (preprint, 2021-11-22)
Field: Materials Science — Materials Chemistry

Evaluating quantum alchemy of atoms with thermodynamic cycles: Beyond ground electronic states Due to the sheer size of chemical and materials space, high throughput computational screening thereof will require the development of new computational methods that are accurate, efficient, and transferable. These methods need to be applicable to electron configurations beyond ground states. To this end, we have systematically studied the applicability of quantum alchemy predictions using a Taylor series expansion on quantum mechanics (QM) calculations for single atoms with different electronic structures arising from different net charges and electron spin multiplicities. We first compare QM method accuracy to experimental quantities including first and second ionization energies, electron affinities, and multiplet spin energy gaps for a baseline understanding of QM reference data. We then investigate the intrinsic accuracy of an approach we call "manual" quantum alchemy schemes compared to the same QM reference data, which employ QM calculations where the basis set of a different element is used for an atom as the limit case of quantum alchemy. We then discuss the reliability of quantum alchemy based on Taylor series approximations at different orders of truncation. Overall, we find that the errors from finite basis set treatments in quantum alchemy are significantly reduced when thermodynamic cycles are employed, which points out a route to improve quantum alchemy in explorations of chemical space. This work establishes important technical aspects that impact the accuracy of quantum alchemy predictions using a Taylor series and provides a foundation for further quantum alchemy studies. Alchemy ; Quantum ; Theoretical physics ; Quantum mechanics ; Statistical physics ; Physics ; Chemistry Machine Learning in Materials Science ; Spectroscopy and Quantum Chemical Studies ; Various Chemistry Research Topics
Authors: Ayşegül Beşir | Fehmi Yazıcı | Mehmet Serhat Odabaş
Source: Brazilian Archives of Biology and Technology (article, 2021-01-01)
Field: Chemistry — Spectroscopy

Estimating Hydroxymethyfurfural (HMF) Concentration Via Modified Seliwanoff Test Using Artificial Neural Network (ANN) HIGHLIGHTS A linear relationship was revealed between HMF concentration and red color resulting from the modified Seliwanoff test. Artificial intelligence interpretation of the concentration-color relationship were evaluated. The modified Seliwanoff test has been shown to be used for HMF determination. Artificial neural network ; Artificial intelligence ; Biological system ; Pattern recognition (psychology) ; Mathematics ; Computer science ; Biology Analytical Chemistry and Chromatography ; Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis
Authors: Ravi Shankar | Sofia Marchesini | Erich A. Müller | Camille Petit
Source: ChemRxiv (preprint, 2021-05-27)
Field: Materials Science — Materials Chemistry

Gas Adsorption in Amorphous Porous Boron Oxynitride: Grand Canonical Monte Carlo Simulations and Experimental Determination Amorphous boron nitride doped with oxygen, boron oxynitride, BNO, is a porous material stable at high pressures and elevated temperatures with potential uses in adsorption-based separation processes at the industrial scale. We present here a molecular model capable of accurately predicting gas sorption in porous BNO solely from the knowledge of the basic experimental characteristics, i.e. overall chemical composition and porosity. With this information, the adsorbent is described atomistically by a complex 3-D pore network built by random packing of nanoflakes. The adsorption may then be evaluated by employing Grand Canonical Monte Carlo with classical forcefields. We report sorption isotherms for CO2, N2 and CH4 on BNO at low (< 1 bar) and high (0 -20 bar) pressures, across a range of temperatures (283 -313 K), which are well predicted by the molecular model. While the experimental measurement of multi-component isotherms under such conditions is a challenging task, molecular simulations provide predictions without the need of additional information. As an example, CO2/N2 and CO2/CH4 binary mixture isotherms, at conditions relevant to post combustion CO2 capture and natural gas sweetening, are computed. Overall, the model provides fundamental insight, which is useful in the design and optimization of porous BNObased adsorbents for molecular separations. Monte Carlo method ; Adsorption ; Boron ; Porosity ; Amorphous solid ; Statistical physics ; Computer science ; Materials science ; Chemistry ; Physics ; Mathematics ; Physical chemistry ; Statistics ; Crystallography ; Composite material ; Organic chemistry Boron and Carbon Nanomaterials Research ; Graphene research and applications ; Thermal properties of materials
Authors: Ravikiran Mahadasa
Source: Engineering International (article, 2021-12-31)
Field: Materials Science — Polymers and Plastics

Hierarchical Structuring of Fibrous Materials: Toward Tailored Properties for High-Performance Textile Products This study aims to determine whether fiber materials with hierarchical organization can improve the qualities of textile goods for high-performance uses. The primary goals are to examine functionalization strategies, identify future possibilities in textile engineering, investigate hierarchical structuring methodologies, and analyze hierarchically structured textiles' mechanical and thermal properties. An extensive examination of extant literature and secondary data sources is carried out to examine the approaches, uses, and difficulties related to hierarchical organization. Important discoveries emphasize how hierarchically organized fabrics have improved mechanical strength, thermal behavior, and functional qualities. The discussion of policy implications follows, focusing on the role of industry cooperation, workforce development, sustainability programs, research funding, and industrial collaboration in improving hierarchically structured textiles. The study's findings highlight the revolutionary potential of fibrous materials' hierarchical organization for promoting sustainability and innovation in the textile sector. Structuring ; Textile ; Materials science ; Business ; Composite material Textile materials and evaluations ; Additive Manufacturing and 3D Printing Technologies ; 3D Shape Modeling and Analysis
Authors: K Bachelord Egree | ; Yoto University | Y Wakiya | H Kamakura | K Shibahara | A Ogasawara | R Saeki | A Nishikubo | H Inokuchi | D Yoshikawa | Tanaka
Source: Angewandte Chemie (article, 2021-10-01)
Field: Materials Science — Materials Chemistry

Daisuke Tanaka Ia mw aiting for the day when someone will discover how to solve the COVID-19 problem. Focus (optics) ; Physics ; Optics X-ray Diffraction in Crystallography ; Enzyme Structure and Function ; Crystal Structures and Properties
Authors: Qianqi Lin | Shu Hu | Tamás Földes | Junyang Huang | Demelza Wright | Jack Griffiths | Bart de Nijs | Edina Rosta | Jeremy J. Baumberg
Source:  (article, 2021-06-21)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Optical Suppression of Energy Barriers in Single Molecule-Metal Binding Understanding the interactions between molecules and metal surfaces is of widespread importance in electrochemistry, sensing, medical imaging/targeting, molecular electronics and spintronics. Although many techniques have characterized the molecule-metal transient bonds, conflicting conclusions arise from their buried location and heterogeneity, while single-molecule probes are scarce. Confinement of optical fields to picometre length-scales around adatoms (termed picocavities [1] , Fig. 1a ) has enabled tip-enhanced and surface-enhanced Raman spectroscopies (TERS and SERS, Fig. 1e ) of single-molecules. However how adatoms change with molecule-metal interactions, with light (both key ingredients in photocatalysis), and how they link to picocavity formation in metal nanogaps is not understood. Molecule ; Spintronics ; Molecular electronics ; Nanotechnology ; Materials science ; Metal ; Chemical physics ; Chemistry ; Condensed matter physics ; Physics Gold and Silver Nanoparticles Synthesis and Applications ; Molecular Junctions and Nanostructures ; Advanced biosensing and bioanalysis techniques
Authors: Duvalier Madrid-Úsuga | Ana G. Mora-León | Andrea Cabrera-Espinosa | Braulio Insuasty | Alejandro Ortíz
Source: Computational and Theoretical Chemistry (preprint, 2021-01-21)
Field: Materials Science — Polymers and Plastics

Theoretical characterization of photoactive molecular systems based on BODIPY-derivatives for the design of organic solar cells HOMO/LUMO ; Density functional theory ; Exciton ; Triphenylamine ; BODIPY ; Organic solar cell ; Absorption spectroscopy ; Materials science ; Molecular orbital ; Absorption (acoustics) ; Dissociation (chemistry) ; Molecule ; Chemistry ; Computational chemistry ; Physical chemistry ; Optoelectronics ; Physics ; Optics ; Fluorescence ; Organic chemistry ; Condensed matter physics ; Polymer Conducting polymers and applications ; Organic Electronics and Photovoltaics ; Perovskite Materials and Applications
Authors: Amin Alibakhshi | Bernd Hartke
Source: ChemRxiv (preprint, 2021-02-09)
Field: Chemistry — Organic Chemistry

Evaluation of the Temperature Dependence of Vaporization Enthalpy and its Correlation with Surface Tension by Machine Learning and Predictive Correlations Temperature dependence of vaporization enthalpy is one of the most important thermophysical properties of compounds. In the present study, we theoretically developed relationships applicable to evaluation of vaporization enthalpy of compounds from diverse chemical families for a wide temperature range from melting point to the critical temperature. One outcome of the proposed approach is a relationship describing the correlation between the surface tension and vaporization enthalpy which outperforms the extensively applied Kabo method proposed for the same purpose.&lt;br&gt; Enthalpy of vaporization ; Vaporization ; Enthalpy ; Thermodynamics ; Surface tension ; Atmospheric temperature range ; Melting point ; Melting temperature ; Chemistry ; Correlation ; Materials science ; Physics ; Organic chemistry ; Mathematics Chemical Thermodynamics and Molecular Structure ; Machine Learning in Materials Science ; Phase Equilibria and Thermodynamics
Authors: Orion Dollar | Nisarg Joshi | David A. C. Beck | Jim Pfaendtner
Source: ChemRxiv (preprint, 2021-02-08)
Field: Materials Science — Materials Chemistry

Giving Attention to Generative VAE Models for De Novo Molecular Design &lt;div&gt; &lt;div&gt; &lt;div&gt; &lt;p&gt;We explore the impact of adding attention to generative VAE models for molecular design. Four model types are compared: a simple recurrent VAE (RNN), a recurrent VAE with an added attention layer (RNNAttn), a transformer VAE (TransVAE) and the previous state-of-the-art (MosesVAE). The models are assessed based on their effect on the organization of the latent space (i.e. latent memory) and their ability to generate samples that are valid and novel. Additionally, the Shannon information entropy is used to measure the complexity of the latent memory in an information bottleneck theoretical framework and we define a novel metric to assess the extent to which models explore chemical phase space. All three models are trained on millions of molecules from either the ZINC or PubChem datasets. We find that both RNNAttn and TransVAE models perform substantially better when tasked with accurately reconstructing input SMILES strings than the MosesVAE or RNN models, particularly for larger molecules up to ~700 Da. The TransVAE learns a complex “molecular grammar” that includes detailed molecular substructures and high-level structural and atomic relationships. The RNNAttn models learn the most efficient compression of the input data while still maintaining good performance. The complexity of the compressed representation learned by each model type increases in the order of MosesVAE &lt; RNNAttn &lt; RNN &lt; TransVAE. We find that there is an unavoidable tradeoff between model exploration and validity that is a function of the complexity of the latent memory. However, novel sampling schemes may be used that optimize this tradeoff and allow us to utilize the information-dense representations learned by the transformer in spite of their complexity. &lt;/p&gt; &lt;/div&gt; &lt;/div&gt; &lt;/div&gt; Computer science ; Information bottleneck method ; Generative model ; Artificial intelligence ; Generative grammar ; Machine learning ; Mutual information Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Kolja Klett | Andrey G. Cherstvy | Jaeoh Shin | Igor M. Sokolov | Ralf Metzler
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-09-06)
Field: Materials Science — Materials Chemistry

Non-Gaussian, transiently anomalous and ergodic self-diffusion of flexible dumbbells in crowded two-dimensional environments: coupled translational and rotational motions We employ Langevin-dynamics simulations to unveil non-Brownian and non-Gaussian center-of-mass self-diffusion of massive flexible dumbbell-shaped particles in crowded two-dimensional solutions. We also study the intra-dumbbell dynamics due to the relative motion of the two constituent elastically-coupled disks. Our main focus is on effects of the crowding fraction ϕ and the particle structure on the diffusion characteristics. We evaluate the time-averaged mean-squared displacement (TAMSD), the displacement probability-density function (PDF) and the displacement autocorrelation function (ACF) of the dimers. For the TAMSD at highly crowded conditions of dumbbells, e.g., we observe a transition from the short-time ballistic behavior, via an intermediate subdiffusive regime, to long-time Brownian-like spreading dynamics. The crowded system of dimers exhibits two distinct diffusion regimes distinguished by the scaling exponent of the TAMSD, the dependence of the diffusivity on ϕ , and the features of the displacement-ACF. We attribute these regimes to a crowding-induced transition from a viscous to a viscoelastic diffusion medium upon growing ϕ . We also analyze the relative motion in the dimers, finding that larger ϕ suppress their vibrations and yield strongly non-Gaussian PDFs of rotational displacements. For the diffusion coefficients D ( ϕ ) of translational and rotational motion of the dumbbells an exponential decay with ϕ for weak and a power-law D ( ϕ ) ∝ ( ϕ – ϕ ⋆) 2.4 for strong crowding is found. A comparison of simulation results with theoretical predictions for D ( ϕ ) is discussed and some relevant experimental systems are overviewed. Dumbbell ; Mean squared displacement ; Physics ; Microrheology ; Rotational diffusion ; Brownian motion ; Anomalous diffusion ; Diffusion ; Center of mass (relativistic) ; Displacement (psychology) ; Brownian dynamics ; Statistical physics ; Scaling ; Autocorrelation ; Gaussian ; Exponent ; Langevin equation ; Viscoelasticity ; Classical mechanics ; Molecular dynamics ; Quantum mechanics ; Thermodynamics ; Mathematics ; Anisotropy Material Dynamics and Properties ; Granular flow and fluidized beds ; Ecosystem dynamics and resilience