jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Chiagoziem Wisdom Chidiebere | Chidi Edbert Duru | J. P. C. Mbagwu
Source: Journal of the Nigerian Society of Physical Sciences (review, 2021-11-29)
Field: Chemistry — Physical and Theoretical Chemistry

Application of computational chemistry in chemical reactivity: a review Molecular orbitals are vital to giving reasons several chemical reactions occur. Although, Fukui and coworkers were able to propose a postulate which shows that highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) is incredibly important in predicting chemical reactions. It should be kept in mind that this postulate could be a rigorous one therefore it requires an awfully serious attention in order to be understood. However, there has been an excellent breakthrough since the introduction of computational chemistry which is mostly used when a mathematical method is fully well built that it is automated for effectuation and intrinsically can predict chemical reactivity. At the cause of this review, we’ve reported on how HOMO and LUMO molecular orbitals may be employed in predicting a chemical change by the utilization of an automatic data processing (ADP) system through the utilization of quantum physics approximations. HOMO/LUMO ; Reactivity (psychology) ; Molecular orbital ; Atomic orbital ; Computational chemistry ; Chemistry ; Quantum chemistry ; Molecule ; Physics ; Quantum mechanics ; Organic chemistry Various Chemistry Research Topics ; Computational Drug Discovery Methods ; Free Radicals and Antioxidants
Authors: Karthik Pushpavanam | Jinrong Ma | Yifeng Cai | Nada Y. Naser | François Baneyx
Source: Annual Review of Chemical and Biomolecular Engineering (review, 2021-04-14)
Field: Materials Science — Biomaterials

Solid-Binding Proteins: Bridging Synthesis, Assembly, and Function in Hybrid and Hierarchical Materials Fabrication There is considerable interest in the development of hybrid organic-inorganic materials because of the potential for harvesting the unique capabilities that each system has to offer. Proteins are an especially attractive organic component owing to the high amount of chemical information encoded in their amino acid sequence, their amenability to molecular and computational (re)design, and the many structures and functions they specify. Genetic installation of solid-binding peptides (SBPs) within protein frameworks affords control over the position and orientation of adhesive and morphogenetic segments, and a path toward predictive synthesis and assembly of functional materials and devices, all while harnessing the built-in properties of the host scaffold. Here, we review the current understanding of the mechanisms through which SBPs bind to technologically relevant interfaces, with an emphasis on the variables that influence the process, and highlight the last decade of progress in the use of solid-binding proteins for hybrid and hierarchical materials synthesis. Bridging (networking) ; Nanotechnology ; Function (biology) ; Component (thermodynamics) ; Computer science ; Computational biology ; Biochemical engineering ; Materials science ; Biology ; Engineering ; Genetics Diatoms and Algae Research ; Supramolecular Self-Assembly in Materials ; Silk-based biomaterials and applications
Authors: Anil Kunwar | Ensieh Yousefi | Xiaojing Zuo | Youqing Sun | David Seveno | Muxing Guo | Nele Moelans
Source: International Journal of Mechanical Sciences (article, 2021-11-22)
Field: Materials Science — Materials Chemistry

Multi-phase field simulation of Al <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e1157" altimg="si16.svg"> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mn>3</mml:mn> </mml:mrow> </mml:msub> </mml:math> Ni <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e1165" altimg="si17.svg"> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mn>2</mml:mn> </mml:mrow> </mml:msub> </mml:math> intermetallic growth at liquid Al/solid Ni interface using MD computed interfacial energies Considering its application in developing Raney-type Ni catalysts and in metal surface coatings, the study on the growth behavior of Al3Ni2 intermetallic compound (IMC) at the Al/Ni material interface is of utmost importance. The present work integrates nanoscale molecular dynamics (MD) calculation with mesoscale phase field model for studying the interfacial phenomena associated with Al3Ni2 growth in Al/Ni interface at 1173.15 K. The interfacial energies computed from MD are in the range 0.9–1.2 J/m2 with FCC/IMC featuring as the interface with the largest value and IMC/LIQUID as the one with the lowest value. Phase field model parameters characterizing a varying interface energy formulation are established to simulate the 2D growth of interfacial IMC grains. With the help of an atomistically informed phase field model, it has been revealed that the phase areas and morphology are obviously sensitive to the interfacial properties. The methodologies and results of these multiscale simulations for IMC interfaced between Al and Ni microstructures offer the complementary and accelerated design route of in-silico studies for materials systems experimented at high temperature. Intermetallic ; Phase (matter) ; Materials science ; Field (mathematics) ; Interface (matter) ; Molecular dynamics ; Microstructure ; Thermodynamics ; Physics ; Chemistry ; Metallurgy ; Alloy ; Composite material ; Mathematics ; Computational chemistry Solidification and crystal growth phenomena ; Aluminum Alloy Microstructure Properties ; nanoparticles nucleation surface interactions
Authors: Stefanie A. Meißner | Theresa Eder | Tristan J. Keller | David Ari Hofmeister | Sebastian Spicher | Stefan‐S. Jester | Jan Vogelsang | Stefan Grimme | John M. Lupton | Sigurd Höger
Source: Nature Communications (article, 2021-11-16)
Field: Materials Science — Materials Chemistry

Nanoscale π-conjugated ladders It is challenging to increase the rigidity of a macromolecule while maintaining solubility. Established strategies rely on templating by dendrons, or by encapsulation in macrocycles, and exploit supramolecular arrangements with limited robustness. Covalently bonded structures have entailed intramolecular coupling of units to resemble the structure of an alternating tread ladder with rungs composed of a covalent bond. We introduce a versatile concept of rigidification in which two rigid-rod polymer chains are repeatedly covalently associated along their contour by stiff molecular connectors. This approach yields almost perfect ladder structures with two well-defined π-conjugated rails and discretely spaced nanoscale rungs, easily visualized by scanning tunnelling microscopy. The enhancement of molecular rigidity is confirmed by the fluorescence depolarization dynamics and complemented by molecular-dynamics simulations. The covalent templating of the rods leads to self-rigidification that gives rise to intramolecular electronic coupling, enhancing excitonic coherence. The molecules are characterized by unprecedented excitonic mobility, giving rise to excitonic interactions on length scales exceeding 100 nm. Such interactions lead to deterministic single-photon emission from these giant rigid macromolecules, with potential implications for energy conversion in optoelectronic devices. Intramolecular force ; Covalent bond ; Macromolecule ; Supramolecular chemistry ; Chemical physics ; Materials science ; Structural rigidity ; Conjugated system ; Nanoscopic scale ; Nanotechnology ; Molecule ; Molecular dynamics ; Polymer ; Exciton ; Fluorescence ; Chemistry ; Computational chemistry ; Physics ; Optics ; Stereochemistry Luminescence and Fluorescent Materials ; Supramolecular Self-Assembly in Materials ; Supramolecular Chemistry and Complexes
Authors: Ziyue Zou | Sun-Ting Tsai | Pratyush Tiwary
Source: The Journal of Physical Chemistry B (article, 2021-11-17)
Field: Materials Science — Materials Chemistry

Toward Automated Sampling of Polymorph Nucleation and Free Energies with the SGOOP and Metadynamics Understanding the driving forces behind the nucleation of different polymorphs is of great importance for material sciences and the pharmaceutical industry. This includes understanding the reaction coordinate that governs the nucleation process and correctly calculating the relative free energies of different polymorphs. Here, we demonstrate, for the prototypical case of urea nucleation from the melt, how one can learn such a one-dimensional reaction coordinate as a function of prespecified order parameters and use it to perform efficient biased all-atom molecular dynamics simulations. The reaction coordinate is learnt as a function of the generic thermodynamic and structural order parameters using the "spectral gap optimization of order parameters (SGOOP)" approach [Tiwary, P. and Berne, B. J. <i>Proc. Natl. Acad. Sci. U.S.A.</i> (2016)] and is biased using well-tempered metadynamics simulations. The reaction coordinate gives insights into the role played by different structural and thermodynamics order parameters, and the biased simulations obtain accurate relative free energies for different polymorphs. This includes an accurate prediction of the approximate pressure at which urea undergoes a phase transition and one of the metastable polymorphs becomes the most stable conformation. We believe the ideas demonstrated in this work will facilitate efficient sampling of nucleation in complex, generic systems. Metadynamics ; Reaction coordinate ; Nucleation ; Metastability ; Molecular dynamics ; Thermodynamics ; Chemistry ; Work (physics) ; Statistical physics ; Umbrella sampling ; Phase transition ; Chemical physics ; Physical chemistry ; Computational chemistry ; Materials science ; Physics Crystallization and Solubility Studies ; Crystallography and molecular interactions ; Protein Structure and Dynamics
Authors: Jong Hun Kang | Lynne B. McCusker | Michael W. Deem | Christian Baerlocher | Mark E. Davis
Source: Chemistry of Materials (article, 2021-02-24)
Field: Chemistry — Inorganic Chemistry

Further Investigations of Racemic and Chiral Molecular Sieves of the STW Topology Large single crystals of pure-silica STW-type molecular sieves are prepared using 1,2,3,4,5-pentamethylimidazolium (12345PMI) and 2-ethyl-1,3,4-trimethylimidazolium (2E134TMI) as organic structure-directing agents (OSDAs) and α-amino acid additives. The effects of the amount and type of amino acid on the crystallization of pure-silica STW materials are investigated. Room-temperature single-crystal X-ray diffractometry shows that 12345PMI better fits the STW cage than 2E134TMI and is fully consistent with computed simulations. The synthesis of an enantioenriched R-STW-type molecular sieve having a Si/Ge ratio of 2.2 is achieved using a chiral, dicationic OSDA that contains two stereocenters. The conformation of the chiral OSDA in the chiral framework has been obtained from a Rietveld refinement using synchrotron powder diffraction data and is the first structure refinement of an enantioenriched, inorganic molecular sieve prepared from a pure, asymmetric OSDA. Molecular sieve ; Materials science ; Crystallization ; Rietveld refinement ; Synchrotron ; Crystallography ; Stereocenter ; Topology (electrical circuits) ; Crystal structure ; Powder diffraction ; Chemical engineering ; Catalysis ; Organic chemistry ; Enantioselective synthesis ; Chemistry ; Optics ; Physics Zeolite Catalysis and Synthesis ; Mesoporous Materials and Catalysis ; Chemical Synthesis and Characterization
Authors: Zachary H. Aitken | V. Sorkin | Zhi Gen Yu | Shuai Chen | Zhaoxuan Wu | Yong‐Wei Zhang
Source: Physical review. B./Physical review. B (article, 2021-03-29)
Field: Materials Science — Materials Chemistry

Modified embedded-atom method potentials for the plasticity and fracture behaviors of unary fcc metals The predictability of molecular dynamics simulations on the plasticity and fracture behaviors of metals is critically dependent on the accuracy of the employed interatomic potential. Here we present an approach to fitting modified embedded-atom method (MEAM) interatomic potentials to several key properties obtained from first-principles calculations and literature data that govern the continuous mechanistic processes in pure unary fcc Ni, Al, and Cu metals. Along with the commonly used lattice and elastic properties, our MEAM potentials are fitted to the cohesive energy curve, the decohesive energy curve, and the generalized stacking fault energy curve, which are the key properties governing the lattice response to volumetric, fracture, and shear deformations. We further demonstrate that these potentials are able to accurately predict the experimental values for a range of other mechanically relevant properties. Importantly, the potentials presented here outperform all existing EAM/MEAM interatomic potentials readily available from the literature and thus enable more accurate simulations of plasticity and fracture behavior of unary fcc metals. Stacking-fault energy ; Interatomic potential ; Materials science ; Molecular dynamics ; Embedded atom model ; Plasticity ; Unary operation ; Atom (system on chip) ; Lattice (music) ; Multiscale modeling ; Thermodynamics ; Condensed matter physics ; Dislocation ; Computational chemistry ; Physics ; Composite material ; Chemistry ; Computer science Machine Learning in Materials Science ; Metal and Thin Film Mechanics ; Nuclear Materials and Properties
Authors: Ulschan Bathe | Bryan J. Leong | Donald R. McCarty | Christopher S. Henry | Paul E. Abraham | Mark A. Wilson | Andrew D. Hanson
Source: Biochemistry (article, 2021-11-03)
Field: Materials Science — Materials Chemistry

The Moderately (D)efficient Enzyme: Catalysis-Related Damage <i>In Vivo</i> and Its Repair Enzymes have <i>in vivo</i> life spans. Analysis of life spans, i.e., lifetime totals of catalytic turnovers, suggests that nonsurvivable collateral chemical damage from the very reactions that enzymes catalyze is a common but underdiagnosed cause of enzyme death. Analysis also implies that many enzymes are moderately deficient in that their active-site regions are not naturally as hardened against such collateral damage as they could be, leaving room for improvement by rational design or directed evolution. Enzyme life span might also be improved by engineering systems that repair otherwise fatal active-site damage, of which a handful are known and more are inferred to exist. Unfortunately, the data needed to design and execute such improvements are lacking: there are too few measurements of <i>in vivo</i> life span, and existing information about the extent, nature, and mechanisms of active-site damage and repair during normal enzyme operation is too scarce, anecdotal, and speculative to act on. Fortunately, advances in proteomics, metabolomics, cheminformatics, comparative genomics, and structural biochemistry now empower a systematic, data-driven approach for identifying, predicting, and validating instances of active-site damage and its repair. These capabilities would be practically useful in enzyme redesign and improvement of in-use stability and could change our thinking about which enzymes die young <i>in vivo</i>, and why. Collateral damage ; In vivo ; Enzyme ; Cheminformatics ; Life span ; Active site ; Protein engineering ; Computational biology ; Chemistry ; Biochemistry ; Biology ; Bioinformatics ; Biotechnology ; Evolutionary biology Enzyme Structure and Function ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: John R. Helliwell
Source: Acta Crystallographica Section A Foundations and Advances (article, 2021-05-01)
Field: Materials Science — Materials Chemistry

Combining X-rays, neutrons and electrons, and NMR, for precision and accuracy in structure–function studies The distinctive features of the physics-based probes used in understanding the structure of matter focusing on biological sciences, but not exclusively, are described in the modern context. This is set in a wider scope of holistic biology and the scepticism about `reductionism', what is called the `molecular level', and how to respond constructively. These topics will be set alongside the principles of accuracy and precision, and their boundaries. The combination of probes and their application together is the usual way of realizing accuracy. The distinction between precision and accuracy can be blurred by the predictive force of a precise structure, thereby lending confidence in its potential accuracy. These descriptions will be applied to the comparison of cryo and room-temperature protein crystal structures as well as the solid state of a crystal and the same molecules studied by small-angle X-ray scattering in solution and by electron microscopy on a sample grid. Examples will include: time-resolved X-ray Laue crystallography of an enzyme Michaelis complex formed directly in a crystal equivalent to in vivo; a new iodoplatin for radiation therapy predicted from studies of platin crystal structures; and the field of colouration of carotenoids, as an effective assay of function, i.e. their colouration, when unbound and bound to a protein. The complementarity of probes, as well as their combinatory use, is then at the foundation of real (biologically relevant), probe-artefacts-free, structure-function studies. The foundations of our methodologies are being transformed by colossal improvements in technologies of X-ray and neutron sources and their beamline instruments, as well as improved electron microscopes and NMR spectrometers. The success of protein structure prediction from gene sequence recently reported by CASP14 also opens new doors to change and extend the foundations of the structural sciences. Context (archaeology) ; Physics ; Theoretical physics ; Chemistry ; Biology Enzyme Structure and Function ; Protein Structure and Dynamics ; Advanced Electron Microscopy Techniques and Applications
Authors: Muhammad Ashraf Sabri | Ziad Sara | Mohammad H. Al‐Sayah | Taleb Ibrahim | Mustafa Khamis | Oussama M. El‐Kadri
Source: Sustainability (article, 2021-01-18)
Field: Materials Science — Materials Chemistry

Simultaneous Adsorption and Reduction of Cr(VI) to Cr(III) in Aqueous Solution Using Nitrogen-Rich Aminal Linked Porous Organic Polymers Two novel nitrogen-rich aminal linked porous organic polymers, NRAPOP-O and NRAPOP-S, have been prepared using a single step-one pot Schiff-base condensation reaction of 9,10-bis-(4,6-diamino-S-triazin-2-yl)benzene and 2-furaldehyde or 2-thiophenecarboxaldehyde, respectively. The two polymers show excellent thermal and physiochemical stabilities and possess high porosity with Brunauer–Emmett–Teller (BET) surface areas of 692 and 803 m2 g−1 for NRAPOP-O and NRAPOP-S, respectively. Because of such porosity, attractive chemical and physical properties, and the availability of redox-active sites and physical environment, the NRAPOPs were able to effectively remove Cr(VI) from solution, reduce it to Cr(III), and simultaneously release it into the solution. The efficiency of the adsorption process was assessed under various influencing factors such as pH, contact time, polymer dosage, and initial concentration of Cr(VI). At the optimum conditions, 100% removal of Cr(VI) was achieved, with simultaneous reduction and release of Cr(III) by NRAPOP-O with 80% efficiency. Moreover, the polymers can be easily regenerated by the addition of reducing agents such as hydrazine without significant loss in the detoxication of Cr(VI). Aminal ; Adsorption ; Polymer ; Chemistry ; Aqueous solution ; Porosity ; Hydrazine (antidepressant) ; Nitrogen ; Redox ; Inorganic chemistry ; Benzene ; Condensation reaction ; Nuclear chemistry ; Chemical engineering ; Organic chemistry ; Chromatography ; Catalysis Covalent Organic Framework Applications ; Metal-Organic Frameworks: Synthesis and Applications ; Radioactive element chemistry and processing
Authors: Bingyin Hu | Anqi Lin | L. Catherine Brinson
Source: Journal of Cheminformatics (article, 2021-03-12)
Field: Materials Science — Materials Chemistry

ChemProps: A RESTful API enabled database for composite polymer name standardization The inconsistency of polymer indexing caused by the lack of uniformity in expression of polymer names is a major challenge for widespread use of polymer related data resources and limits broad application of materials informatics for innovation in broad classes of polymer science and polymeric based materials. The current solution of using a variety of different chemical identifiers has proven insufficient to address the challenge and is not intuitive for researchers. This work proposes a multi-algorithm-based mapping methodology entitled ChemProps that is optimized to solve the polymer indexing issue with easy-to-update design both in depth and in width. RESTful API is enabled for lightweight data exchange and easy integration across data systems. A weight factor is assigned to each algorithm to generate scores for candidate chemical names and optimized to maximize the minimum value of the score difference between the ground truth chemical name and the other candidate chemical names. Ten-fold validation is utilized on the 160 training data points to prevent overfitting issues. The obtained set of weight factors achieves a 100% test accuracy on the 54 test data points. The weight factors will evolve as ChemProps grows. With ChemProps, other polymer databases can remove duplicate entries and enable a more accurate "search by SMILES" function by using ChemProps as a common name-to-SMILES translator through API calls. ChemProps is also an excellent tool for auto-populating polymer properties thanks to its easy-to-update design. Computer science ; Overfitting ; Standardization ; Materials informatics ; Identifier ; Data mining ; Information retrieval ; Search engine indexing ; Database ; Set (abstract data type) ; Artificial intelligence ; Health informatics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Metabolomics and Mass Spectrometry Studies
Authors: Juan Wu | Simon X. Yang
Source: IEEE Access (article, 2021-01-01)
Field: Chemistry — Analytical Chemistry

Modeling of the Bulk Tobacco Flue-Curing Process Using a Deep Learning-Based Method The research of the bulk tobacco flue-curing process is helpful to model the intelligent bulk curing system, which is designed to implement the curing procedure without manual operation. An intelligent bulk curing method based on the convolutional neural network (CNN) named TobaccoNet was proposed, which could set the target dry-bulb temperature (TD) and the target wet-bulb temperature (TW) of the bulk curing barn according to the tobacco leaves image. The performance of the TobaccoNet is compared with the traditional manual image feature extraction method, the stacked-sparse-autoencoder (SSAE)-based deep learning method, and the other two methods applied in related references. The test results show that TobaccoNet outperforms the comparison methods in predicting TD and TW. Specifically, the correlation coefficient reaches 0.9965 and 0.9683, the mean relative error is 1.62% and 1.77%, and the root mean squared error achieves 1.061 °C and 0.8581 °C respectively. The promising results demonstrate that the TobaccoNet is effective and reliable for modeling the intelligent bulk tobacco flue-curing process. The influence of different CNN structures on the prediction accuracy of TD and TW was analyzed. From the perspective of the computational complexity and the prediction performance, the proposed sequential CNN structure is more suitable for analyzing bulk tobacco curing in this study. Curing (chemistry) ; Autoencoder ; Convolutional neural network ; Computer science ; Deep learning ; Mean squared error ; Artificial intelligence ; Artificial neural network ; Curing of tobacco ; Feature extraction ; Pattern recognition (psychology) ; Materials science ; Mathematics ; Composite material ; Statistics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Industrial Vision Systems and Defect Detection