Dynamic Phase Diagram of Catalytic Surface of Hexagonal Boron Nitride under Conditions of Oxidative Dehydrogenation of Propane.

Partially oxidized surfaces of hexagonal boron nitride (hBN) and several metal borides are unexpectedly excellent catalysts for oxidative dehydrogenation of alkanes to olefins, but the nature of the active site(s) on these B-containing interfaces remains elusive. We characterize the surface of the partially oxidized B-rich hBN surface under reaction conditions from first principles. The interface has thermal access to multiple different stoichiometries and multiple structures of each stoichiometry. The size of the thermal ensemble is composition-dependent. The phase diagram of the interface constructed on the basis of the statistical ensembles of many accessible states is very different from the one based on global minima. Phase boundaries shift and blur, and phases consist of several stoichiometries and structures. The BO layer transiently exposes the reactive -B═O motifs in the metastable states. The fluxionality and structural diversity emerging under reaction conditions must be taken into account in theoretically descriptions of the catalytic interface

Divergent evolution of protein conformational dynamics in dihydrofolate reductase.

Molecular evolution is driven by mutations, which may affect the fitness of an organism and are then subject to natural selection or genetic drift. Analysis of primary protein sequences and tertiary structures has yielded valuable insights into the evolution of protein function, but little is known about the evolution of functional mechanisms, protein dynamics and conformational plasticity essential for activity. We characterized the atomic-level motions across divergent members of the dihydrofolate reductase (DHFR) family. Despite structural similarity, Escherichia coli and human DHFRs use different dynamic mechanisms to perform the same function, and human DHFR cannot complement DHFR-deficient E. coli cells. Identification of the primary-sequence determinants of flexibility in DHFRs from several species allowed us to propose a likely scenario for the evolution of functionally important DHFR dynamics following a pattern of divergent evolution that is tuned by cellular environment

On the Dynamical Ferromagnetic, Quantum Hall, and Relativistic Effects on the Carbon Nanotubes Nucleation and Growth Mechanism

The mechanism of carbon nanotube (CNT) nucleation and growth has been a mystery for over 15 years. Prior models have attempted the extension of older classical transport mechanisms. In July 2000, a more detailed and accurate nonclassical, relativistic mechanism was formulated considering the detailed dynamics of the electronics of spin and orbital rehybridization between the carbon and catalyst via novel mesoscopic phenomena and quantum dynamics. Ferromagnetic carbon was demonstrated. Here, quantum (Hall) effects and relativistic effects of intense many body spin-orbital interactions for novel orbital rehybridization dynamics (Little Effect) are proposed in this new dynamical magnetic mechanism. This dynamic ferromagnetic mechanism is proven by imposing dynamic and static magnetic fields during CNT syntheses and observing the different influence of these external magnetic environments on the catalyzing spin currents and spin waves and the resulting CNT formation

Meta-heuristic algorithms in car engine design: a literature survey

Meta-heuristic algorithms are often inspired by natural phenomena, including the evolution of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of some birds, and annealing in metallurgy. Due to their great potential in solving difficult optimization problems, meta-heuristic algorithms have found their way into automobile engine design. There are different optimization problems arising in different areas of car engine management including calibration, control system, fault diagnosis, and modeling. In this paper we review the state-of-the-art applications of different meta-heuristic algorithms in engine management systems. The review covers a wide range of research, including the application of meta-heuristic algorithms in engine calibration, optimizing engine control systems, engine fault diagnosis, and optimizing different parts of engines and modeling. The meta-heuristic algorithms reviewed in this paper include evolutionary algorithms, evolution strategy, evolutionary programming, genetic programming, differential evolution, estimation of distribution algorithm, ant colony optimization, particle swarm optimization, memetic algorithms, and artificial immune system

The Dimerization Domain in DapE Enzymes Is Required for Catalysis

The emergence of antibiotic-resistant bacterial strains underscores the importance of identifying new drug targets and developing new antimicrobial compounds. Lysine and meso-diaminopimelic acid are essential for protein production and bacterial peptidoglycan cell wall remodeling and are synthesized in bacteria by enzymes encoded within dap operon. Therefore dap enzymes may serve as excellent targets for developing a new class of antimicrobial agents. The dapE-encoded N-succinyl-L,L-diaminopimelic acid desuccinylase (DapE) converts N-succinyl-L,L-diaminopimelic acid to L,Ldiaminopimelic acid and succinate. The enzyme is composed of catalytic and dimerization domains, and belongs to the M20 peptidase family. To understand the specific role of each domain of the enzyme we engineered dimerization domain deletion mutants of DapEs from Haemophilus influenzae and Vibrio cholerae, and characterized these proteins structurally and biochemically. No activity was observed for all deletion mutants. Structural comparisons of wild-type, inactive monomeric DapE enzymes with other M20 peptidases suggest that the dimerization domain is essential for DapE enzymatic activity. Structural analysis and molecular dynamics simulations indicate that removal of the dimerization domain increased the flexibility of a conserved active site loop that may provide critical interactions with the substrate

Environmental boundary conditions for the origin of life converge to an organo-sulfur metabolism

Published in final edited form as: Nat Ecol Evol. 2019 December ; 3(12): 1715–1724. doi:10.1038/s41559-019-1018-8.It has been suggested that a deep memory of early life is hidden in the architecture of metabolic networks, whose reactions could have been catalyzed by small molecules or minerals before genetically encoded enzymes. A major challenge in unravelling these early steps is assessing the plausibility of a connected, thermodynamically consistent proto-metabolism under different geochemical conditions, which are still surrounded by high uncertainty. Here we combine network-based algorithms with physico-chemical constraints on chemical reaction networks to systematically show how different combinations of parameters (temperature, pH, redox potential and availability of molecular precursors) could have affected the evolution of a proto-metabolism. Our analysis of possible trajectories indicates that a subset of boundary conditions converges to an organo-sulfur-based proto-metabolic network fuelled by a thioester- and redox-driven variant of the reductive tricarboxylic acid cycle that is capable of producing lipids and keto acids. Surprisingly, environmental sources of fixed nitrogen and low-potential electron donors are not necessary for the earliest phases of biochemical evolution. We use one of these networks to build a steady-state dynamical metabolic model of a protocell, and find that different combinations of carbon sources and electron donors can support the continuous production of a minimal ancient 'biomass' composed of putative early biopolymers and fatty acids.80NSSC17K0295 - Intramural NASA; 80NSSC17K0296 - Intramural NASA; T32 GM100842 - NIGMS NIH HHSAccepted manuscrip

The NASA SBIR product catalog

The purpose of this catalog is to assist small business firms in making the community aware of products emerging from their efforts in the Small Business Innovation Research (SBIR) program. It contains descriptions of some products that have advanced into Phase 3 and others that are identified as prospective products. Both lists of products in this catalog are based on information supplied by NASA SBIR contractors in responding to an invitation to be represented in this document. Generally, all products suggested by the small firms were included in order to meet the goals of information exchange for SBIR results. Of the 444 SBIR contractors NASA queried, 137 provided information on 219 products. The catalog presents the product information in the technology areas listed in the table of contents. Within each area, the products are listed in alphabetical order by product name and are given identifying numbers. Also included is an alphabetical listing of the companies that have products described. This listing cross-references the product list and provides information on the business activity of each firm. In addition, there are three indexes: one a list of firms by states, one that lists the products according to NASA Centers that managed the SBIR projects, and one that lists the products by the relevant Technical Topics utilized in NASA's annual program solicitation under which each SBIR project was selected

Ab initio atomistic thermodynamics and statistical mechanics of surface properties and functions

Previous and present "academic" research aiming at atomic scale understanding is mainly concerned with the study of individual molecular processes possibly underlying materials science applications. Appealing properties of an individual process are then frequently discussed in terms of their direct importance for the envisioned material function, or reciprocally, the function of materials is somehow believed to be understandable by essentially one prominent elementary process only. What is often overlooked in this approach is that in macroscopic systems of technological relevance typically a large number of distinct atomic scale processes take place. Which of them are decisive for observable system properties and functions is then not only determined by the detailed individual properties of each process alone, but in many, if not most cases also the interplay of all processes, i.e. how they act together, plays a crucial role. For a "predictive materials science modeling with microscopic understanding", a description that treats the statistical interplay of a large number of microscopically well-described elementary processes must therefore be applied. Modern electronic structure theory methods such as DFT have become a standard tool for the accurate description of individual molecular processes. Here, we discuss the present status of emerging methodologies which attempt to achieve a (hopefully seamless) match of DFT with concepts from statistical mechanics or thermodynamics, in order to also address the interplay of the various molecular processes. The new quality of, and the novel insights that can be gained by, such techniques is illustrated by how they allow the description of crystal surfaces in contact with realistic gas-phase environments.Comment: 24 pages including 17 figures, related publications can be found at http://www.fhi-berlin.mpg.de/th/paper.htm