jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Jeff Jones
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2020-02-07)
Field: Chemistry — Spectroscopy

A Pre-computed Probabilistic Molecular Search Engine for Tandem Mass Spectrometry Proteomics Abstract Mass spectrometry methods of peptide identification involve comparing observed tandem spectra with in-silico derived spectrum models. Presented here is a proteomics search engine that offers a new variation of the standard approach, with improved results. The proposed method employs information theory and probabilistic information retrieval on a pre-computed and indexed fragmentation database generating a peptide-to-spectrum match (PSM) score modeled on fragment ion frequency. As a result, the direct application of modern document mining, allows for treating the collection of peptides as a corpus and corresponding fragment ions as indexable words, leveraging ready-built search engines and common predefined ranking algorithms. Fast and accurate PSM matches are achieved yielding a 5-10% higher rate of peptide identities than current database mining methods. Immediate applications of this search engine are aimed at identifying peptides from large sequence databases consisting of homologous proteins with minor sequence variations, such as genetic variation expected in the human population. Database search engine ; Probabilistic logic ; Search engine ; Computer science ; Tandem mass spectrometry ; Ranking (information retrieval) ; In silico ; Fragment (logic) ; Fragmentation (computing) ; Data mining ; Proteomics ; Computational biology ; Mass spectrometry ; Artificial intelligence ; Information retrieval ; Chemistry ; Biology ; Algorithm ; Genetics ; Chromatography ; Gene Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Joseph E. Schneider | McKenna K. Goetz | John S. Anderson
Source: ChemRxiv (preprint, 2020-10-06)
Field: Chemistry — Inorganic Chemistry

Statistical Analysis of C–H Activation by Transition Metal Oxo Species Supports Thermodynamic Control Over Reactivity Transition metal oxo species are key intermediates for the activation of strong C‒H bonds. As such, there has been interest in understanding which structural or electronic parameters of metal oxo complexes determine their reactivity. Factors such as ground state thermodynamics, spin state, steric environment, oxygen radical character, and asynchronicity have all been cited as key contributors, yet there is no consensus on when each of these parameters is significant or the relative magnitude of their effects. Herein, we present a thorough statistical analysis of parameters that have been proposed to influence transition metal oxo mediated C‒H activation. We used density functional theory (DFT) to compute parameters for transition metal oxo complexes and analyzed their ability to explain and predict an extensive data set of experimentally determined reaction barriers. We found that, in general, only thermodynamic parameters related to the free energy of hydrogen atom, proton, and electron transfer play a statistically significant role. Steric effects ; Reactivity (psychology) ; Transition metal ; Chemistry ; Ground state ; Thermodynamics ; Hydrogen atom ; Metal ; Density functional theory ; Electron transfer ; Computational chemistry ; Chemical physics ; Physical chemistry ; Catalysis ; Stereochemistry ; Physics ; Atomic physics ; Organic chemistry Metal-Catalyzed Oxygenation Mechanisms ; Oxidative Organic Chemistry Reactions ; CO2 Reduction Techniques and Catalysts
Authors: Chunheng Jiang | Bolesław K. Szymański | Shlomo Havlin | Jianxi Gao
Source: Research Square (Research Square) (preprint, 2020-09-10)
Field: Chemistry — Physical and Theoretical Chemistry

Nuclear Reaction Network Unveils Novel Reaction Patterns and Nuclei Stability Abstract Despite the advances in discovering new nuclei, modeling microscopic nuclear structure, nuclear reactors, and stellar nucleosynthesis, we lack a systemic tool, in the form of a network framework, to understand the structure and dynamics of 70 thousands reactions discovered until now. We assemble here a nuclear reaction network in which a node represents a nuclide, and a link represents a direct reaction between nuclides. Interestingly, the degree distribution of nuclear network exhibits a bimodal distribution that significantly deviates from the power-law distribution of scale-free networks and Poisson distribution of random networks. The distribution is universal for reactions with a rate below the threshold, λ-T γ , where T is the temperature and γ≈1.05. We discovered three rules that govern the structure pattern of nuclear reaction network: (i) reaction-type is determined by linking choices, (ii) spatial distances between the reacting nuclides are short, and (iii) each node in- and out- degrees are close to each other. By incorporating these three rules, our model unveils the underlying nuclear reaction patterns hidden in a large and dense nuclear reaction network. It enables us to predict missing links that represent possible new nuclear reactions not yet discovered. Stability (learning theory) ; Nuclear reaction ; Chemistry ; Computer science ; Physics ; Nuclear physics History and advancements in chemistry ; Nuclear physics research studies ; Origins and Evolution of Life
Authors: Takehiro Fujita | Kei Terayama | Masato Sumita | Hironori Izawa | Koji Tsuda | Kenji Morihashi
Source: ChemRxiv (preprint, 2020-11-20)
Field: Chemistry — Organic Chemistry

Machine Learning Analysis for Photo-Induced Phenomena of 1-Methyl-3-(N-(1,8- Naphthalimidyl)ethyl)imidazolium Salts 1-Methyl-3-(N-(1,8-naphthalimidyl)ethyl)imidazolium (MNEI) salts show various photochemical phenomena depending on the guest anion. We used machine learning techniques to extract decisive factors that dominate the fate of MNEI salts after UV irradiation and prepared a decision tree diagram to deduce their photochemical phenomena before experiments. Diagram ; Irradiation ; Ion ; Chemistry ; Decision tree ; Organic chemistry ; Computer science ; Machine learning ; Physics ; Nuclear physics Multicomponent Synthesis of Heterocycles ; Chemical Synthesis and Analysis ; Inorganic and Organometallic Chemistry
Authors: P. Srinivasan
Source: Research Repository (Delft University of Technology) (article, 2020-02-17)
Field: Materials Science — Materials Chemistry

Atomistic Simulations of Nickel-Titanium Shape-Memory Alloys Shape-memory Alloys (SMAs) exhibit tremendous mechanical properties owing to their reversible phase transformation between the austenitic and the martensitic phase. Out of these, equi-atomic nickel-titanium (NiTi) alloys are the most widely used SMAs for various applications since the transformation occurs close to room temperature. Advances in SMA engineering can be propelled by understanding the fundamental behavior of these materials. Atomistic scale computational techniques provide an efficient way of doing this. The accuracy of such techniques is based on the underlying model that is used in these simulations. With advancements in computational power, the scope for building more accurate material models and simulating bigger and more realistic systems have increased. This thesis is focused on understanding NiTi behavior at an atomistic scale using such accurate models. The work done as a part of this thesis is twofold. Firstly, previously existing interatomic potential models are used to perform molecular dynamics (MD) simulations to describe various phase transformation phenomena in NiTi SMAs including pseudo-elasticity and shape-memory effect, thereby comparing the performance of these existing models. Secondly, a new NiTi interatomic potential is developed, using a database generated by performing Density Functional Theory (DFT) calculations, the performance of which is better than existing models. Shape-memory alloy ; Nickel titanium ; Interatomic potential ; Austenite ; Molecular dynamics ; Transformation (genetics) ; Diffusionless transformation ; Materials science ; Martensite ; Statistical physics ; Work (physics) ; Computer science ; Mechanical engineering ; Metallurgy ; Microstructure ; Computational chemistry ; Chemistry ; Physics ; Engineering Shape Memory Alloy Transformations
Authors: Manuel Carrer | Tatjana Škrbić | Sigbjørn Løland Bore | Giuseppe Milano | Michele Cascella | Achille Giacometti
Source: ChemRxiv (preprint, 2020-06-02)
Field: Chemistry — Organic Chemistry

Can Polarity-Inverted Surfactants Self-Assemble in Nonpolar Solvents? We investigate the self-assembly process of a surfactant with inverted polarity in water and cyclohexane using both all-atom and coarse grained hybrid particle-field molecular&lt;br&gt;dynamics simulations. Unlike conventional surfactants, the molecule under study proposed in a recent experiment is&lt;br&gt;&lt;div&gt;formed by a rigid and compact hydrophobic adamantane moiety, and a long and floppy triethylene glycol tail. In water, we report the formation of stable inverted micelles with the adamantane heads grouping together into a hydrophobic core, and the tails forming hydrogen bonds with water. By contrast, multi-microsecond simulations do not provide evidence of stable micelle formation in cyclohexane. Validating the computational results by comparison with experimental diffusion constant and small-angle neutron scattering intensity, we show that at laboratory thermodynamic conditions the mixture resides in the supercritical region of the phase diagram, where aggregated and free surfactant states co-exist in solution. Our simulations also provide indications about how to escape this region, to produce thermodynamically stable micellar forms.&lt;/div&gt; Adamantane ; Micelle ; Cyclohexane ; Pulmonary surfactant ; Chemistry ; Molecular dynamics ; Chemical physics ; Supercritical fluid ; Hydrogen bond ; Hydrophobe ; Molecule ; Small-angle neutron scattering ; Phase (matter) ; Neutron scattering ; Chemical engineering ; Crystallography ; Materials science ; Physical chemistry ; Scattering ; Organic chemistry ; Aqueous solution ; Computational chemistry ; Physics Surfactants and Colloidal Systems ; Mesoporous Materials and Catalysis ; Pickering emulsions and particle stabilization
Authors: Dil K. Limbu | Stephen R. Elliott | Raymond Atta‐Fynn | Parthapratim Biswas
Source: Scientific Reports (preprint, 2020-05-08)
Field: Materials Science — Materials Chemistry

Disorder by design: A data-driven approach to amorphous semiconductors without total-energy functionals X-ray diffraction, Amorphous silicon, Multi-objective optimization, Monte Carlo methods. This paper addresses a difficult inverse problem that involves the reconstruction of a three-dimensional model of tetrahedral amorphous semiconductors via inversion of diffraction data. By posing the material-structure determination as a multiobjective optimization program, it has been shown that the problem can be solved accurately using a few structural constraints, but no total-energy functionals/forces, which describe the local chemistry of amorphous networks. The approach yields highly realistic models of amorphous silicon, with no or only a few coordination defects (≤1%), a narrow bond-angle distribution of width 9-11.5°, and an electronic gap of 0.8-1.4 eV. These data-driven information-based models have been found to produce electronic and vibrational properties of a-Si that match accurately with experimental data and rival that of the Wooten-Winer-Weaire models. The study confirms the effectiveness of a multiobjective optimization approach to the structural determination of complex materials, and resolves a long-standing dispute concerning the uniqueness of a model of tetrahedral amorphous semiconductors obtained via inversion of diffraction data. Amorphous semiconductors ; Tetrahedron ; Amorphous solid ; Amorphous silicon ; Semiconductor ; Uniqueness ; Inversion (geology) ; Materials science ; Diffraction ; Inverse ; Inverse problem ; Silicon ; Statistical physics ; Physics ; Crystallography ; Mathematics ; Chemistry ; Optics ; Mathematical analysis ; Geometry ; Optoelectronics ; Crystalline silicon ; Geology Phase-change materials and chalcogenides ; Thin-Film Transistor Technologies ; Nonlinear Optical Materials Studies
Authors: Ke Huang
Source: UNM’s Digital Repository (University of New Mexico) (article, 2020-01-01)
Field: Materials Science — General Materials Science

INTERACTION OF OPTOMECHANICAL CAVITIES WITH ACOUSTIC WAVES AND OSCILLATORS Resonators and oscillators are key elements in a wide variety of natural and manmade systems. As such understanding and exploiting their dynamics both as isolated devices and members of coupled systems has been the subject of intensive investigation for more than a century. The advent of optomechanical resonators (OMRs) that support strong coupling between optical and mechanical modes resulting in self-sustained optomechanical oscillations, has created new opportunities for device development and implementation of coupled oscillatory systems. One aspect of this thesis is focused on exploring some of the unique features of OMRs and optomechanical oscillators (OMOs) that can be exploited for efficient acousto-optical transduction and signal processing in the context of underwater communication and sensing. Another aspect is related to interaction of OMOs with other types of oscillators and the behavior of the resulting oscillatory systems as well as closely related heterogenous oscillatory systems. Notable achievements and results discussed in this dissertation include: 1) Demonstrating a new and practical method for stabilizing an OMO; 2) First demonstration of injection locking of an OMO via acoustic waves; 3) Studying the performance of optomechanical resonator as an acousto-optical receiver with optomechanical gain; 4) First demonstration of OMO functioning as a local oscillator and mixer in an acousto-optical underwater communication link; 5) Theoretical and experimental study of cluster synchronization in a multilayer network of Colpitts oscillators; 6) Theoretical study of the dynamics of a heterogeneous coupled oscillatory system comprising an optoelectronic oscillator and an OMO; 7) Experimental observations of synchronization between an optoelectronic and a Colpitts oscillator both in periodical oscillatory and chaotic regimes; 8) Application of homogeneous and heterogeneous oscillatory systems in sensing and detection. Physics ; Acoustics ; Optics Material Properties and Applications ; Elasticity and Wave Propagation ; Engineering Diagnostics and Reliability
Authors: Shusuke Kasamatsu | Osamu Sugino | T. Ogawa | Akihide Kuwabara
Source: ChemRxiv (preprint, 2020-02-03)
Field: Materials Science — Materials Chemistry

Insights Into Defect Arrangements in Y-Doped BaZrO3 From Large-Scale First-Principles Thermodynamic Sampling: Association, Repulsion, Percolation, and Trapping &lt;div&gt;Y-doped BaZrO&lt;sub&gt;3&lt;/sub&gt; is an ion conductor under intense research for application in medium temperature solid oxide fuel cells. The conductivity is maximized at ~20% doping, and the decrease with further doping has often been attributed to the association effect, or the trapping of ionic charge carriers by the dopant. This seems like a reasonable conjecture since the dopant and carrier are charged in opposite polarities&lt;/div&gt;&lt;div&gt;and should attract each other. However, at such high doping concentrations, many-body interactions between nearby dopants and carriers are likely to modify such a simple two-body attraction picture. Thus, in this work, we employ a large-scale first-principles thermodynamic sampling scheme to directly examine the configuration of dopants and charge-compensating defects at realistic doping concentrations under processing conditions. We find that although there is, indeed, a clear Y&lt;sub&gt;Zr&lt;/sub&gt; – V&lt;sub&gt;O &lt;/sub&gt;association effect at all doping concentrations examined, the magnitude of the effect actually decreases with increasing dopant concentration. We also find that Y&lt;sub&gt;Zr&lt;/sub&gt;–Y&lt;sub&gt;Zr &lt;/sub&gt;and V&lt;sub&gt;O&lt;/sub&gt; –V&lt;sub&gt;O &lt;/sub&gt;interactions cannot simply be understood in terms of two-body Coulomb attraction and repulsion, highlighting the importance of many-body effects in understanding the defect chemistry&lt;/div&gt;&lt;div&gt;in heavily doped oxides. Finally, we examine the dopant configurations and successfully explain the conductivity maximum based on a percolation vs. trapping picture that has gained attention recently.&lt;/div&gt; Dopant ; Doping ; Ionic bonding ; Materials science ; Trapping ; Chemistry ; Analytical Chemistry (journal) ; Ion ; Condensed matter physics ; Physics Advancements in Solid Oxide Fuel Cells ; Ionic liquids properties and applications ; Magnetic and transport properties of perovskites and related materials
Authors: Sameer Aryal
Source: MOspace Institutional Repository (University of Missouri) (article, 2020-01-01)
Field: Chemistry — Analytical Chemistry

Mobile hyperspectral imaging for structural damage detection Hyperspectral imaging ; Remote sensing ; Computer vision ; Computer science ; Artificial intelligence ; Environmental science ; Geology Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Advanced Measurement and Detection Methods
Authors: Farzana Siddique | Muhammad Arshad | Wardah Hassan | Zakir Hussain Shah | Usman Akhtar
Source: International Journal of Biosciences (IJB) (article, 2020-04-01)
Field: Materials Science — Biomaterials

A review on Chitosan: As a potent fish preservative Due to rising awareness regarding side effects of chemical preservative of food stuff scientist are looking for innovative method of preservation of sea food that can enhance the shelf life, also improve the integrity and quality of food stuff. To address this situation, natural coatings have gained more attention. Among all-natural preservative agents, chitosan is preferable choice due to its non-toxic, biodegradable nature and excellent film forming properties. In current review, the functional antimicrobial and antioxidant properties of chitosan are highlighted with reference to extension of shelf life of sea food. Preservative ; Shelf life ; Food preservation ; Fish <Actinopterygii> ; Antimicrobial ; Food Preservatives ; Natural food ; Chitosan Nanocomposite Films for Food Packaging ; Seaweed-derived Bioactive Compounds ; Collagen: Extraction and Characterization
Authors: Ryan Lacdao Arevalo
Source: KIMIKA (article, 2020-06-25)
Field: Materials Science — Materials Chemistry

Quantum and Atomic Scale Materials Modeling in the Philippines: Status, Challenges, and Recommendations The computational materials modeling and simulation research landscape in the Philippines is explored to identify the problem areas and challenges faced by the experts in this field, thereby gaining insights for policy recommendations towards advancing this field in the country. The identified problem areas based on a survey administered to sixteen expert-respondents include the inadequate computational infrastructure, issues on funding, problems with students, administrative and teaching assignments, and lack of collaborations with the industry. Based on these results, policy recommendations were formulated, which include a proposed framework for an integrated computational and experimental approach in the national research and development agenda, enhancement of the national computing facility, amendment of the procurement law, dedicated funding for computational science, establishment of a junior research fellowship and an organized materials modeling community, and development of regional niches for computational materials science. Procurement ; Computational model ; Scale (ratio) ; Field (mathematics) ; Management science ; Computer science ; Engineering ethics ; Political science ; Engineering management ; Business ; Engineering ; Simulation ; Physics Machine Learning in Materials Science ; Nanotechnology research and applications
Authors: Tanja B Vojinovic | Ljiljana Kašćelan | Zorica Potpara | Natasa Radonjic | Zorka Kascelan
Source:  (preprint, 2020-07-06)
Field: Chemistry — Analytical Chemistry

Improving Structure Based Models for Predicting Chemical Functions and Weight Fractions in Cosmetic Products using Ensemble Support Vector Machine <title>Abstract</title> Through usage of a large number of cosmetic products, consumers are very often exposed to toxic chemicals. This paper is aimed at proposing a model for the prediction of chemical functions and weight fractions in these products based on the structural and physical-chemical properties of the chemicals. Due to the imbalance of classes we used Support Vector Machine (SVM) method, which can complement a smaller class with the examples that are most similar to it and identify the examples that are most different. The generality of the SVM method was additionally enhanced by combining it with ensemble Bootstrap Aggregation (Bagging). The research results show that the proposed bagging SVM method can overcome the disadvantages of previously applied methods. Further, it can help address the lack of information needed to assess exposure to risk from the use of cosmetic products containing toxic chemicals in their composition. The proposed models can be applied to predict whether a certain chemical may be a substitute for a function performed by another possibly toxic chemical in a cosmetic product, as well as well as to determine the quantity proportion of a certain dangerous chemical on the basis of its chemical structure and physical-chemical properties. Support vector machine ; Computer science ; Machine learning ; Artificial intelligence ; Pattern recognition (psychology) Spectroscopy and Chemometric Analyses ; Dye analysis and toxicity ; Advanced Chemical Sensor Technologies
Authors: Nihal Kuş | Saliha Ilıcan
Source: Bitlis Eren Üniversitesi Fen Bilimleri Dergisi (article, 2020-03-13)
Field: Chemistry — Organic Chemistry

Cis ve Trans Formundaki 5-Floropirimidin-2-Karboksilik Asit Molekülünün DFT/TD-DFT ve NBO Analizleri 5-Floropirimidin-2-karboksilik asit molekülünün kararlı durumları, baz setlerine difüz fonksiyonları eklenerek, DFT/B3LYP fonksiyonu ile hesaplandı. C-C-O-H dihedral açısına bağlı olarak molekülün minimum düzeyde cis ve trans olarak iki konformasyona sahip olduğu bulundu. Her iki konformasyon için infrared (IR) spektrum analizi yapılmıştır. Zamana bağlı yoğunluk fonksiyonel teorisi hesaplarından (TD-DFT) uyarılmış enerji düzeylerinin singlet ve triplet enerjileri belirlenmiştir. Fock matrisinin ikinci dereceden pertürbasyon teorisi ile yapılan doğal bağ orbital analizleri (NBO) ile stabilizasyon enerjileri, ve HOMO-LUMO alt ve üst aralıklarına bağlı enerjileri hesaplanmıştır. Ayrıca moleküle ait C-C ve C-N bağ uzunlukları kullanılarak halkaya ait HOMA (Harmonik osilatörde aromatikliğin ölçüsü) dizini bulunmuştur. Natural bond orbital ; Dihedral angle ; Physics ; Crystallography ; Density functional theory ; HOMO/LUMO ; Chemistry ; Molecule ; Computational chemistry ; Hydrogen bond Synthesis and biological activity ; Structural and Chemical Analysis of Organic and Inorganic Compounds ; Organic Chemistry Cycloaddition Reactions
Authors: Guillaume Dugast
Source: theses.fr (ABES) (article, 2020-09-04)
Field: Materials Science — Materials Chemistry

Morphological evolution of thermal protection system Les matériaux composites sont désormais incontournables en aéronautique et certaines applications (rentrée atmosphérique, vol supersonique) exigent des performances toujours plus grandes, principalement thermiques. Afin de répondre aux nouvelles exigences, les industriels cherchent à disposer des outils leurs permettant de faire les choix technologiques et de design qui s’imposent. Cela nécessite de transposer dans le domaine industriel les connaissances scientifiques développées depuis 15 ans en laboratoire et en attente de simplification pour une intégration dans les outils fiables d’ingénierie courante. Work (physics) ; Statistical analysis ; Thermal protection Thermal properties of materials ; Material Selection and Properties ; Rocket and propulsion systems research