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Solution‐Phase Dynamic Assembly of Permanently Interlocked Aryleneethynylene Cages through Alkyne Metathesis
Abstract Highly stable permanently interlocked aryleneethynylene molecular cages were synthesized from simple triyne monomers using dynamic alkyne metathesis. The interlocked complexes are predominantly formed in the reaction solution in the absence of any recognition motif and were isolated in a pure form using column chromatography. This study is the first example of the thermodynamically controlled solution‐phase synthesis of interlocked organic cages with high stability.
A Dynamically Stabilized Single‐Nickel Electrocatalyst for Selective Reduction of Oxygen to Hydrogen Peroxide
Abstract On‐location electrochemical generation of H 2 O 2 is of great current interest. Herein, selective two‐electron reduction of O 2 to H 2 O 2 by a single [Ni II (H 2 O) 6 ] 2+ cation that is dynamically associated with a negatively charged metal–organic layer (MOL) by hydrogen bonding and coulombic interactions is reported. In contrast, Ni II centers covalently immobilized on the MOL reduce O 2 to H 2 O in a four‐ electron process. Oxygen adsorption by [Ni II (H 2 O) 6 ] 2+ followed by two‐electron reduction generates neutral [Ni II (H 2 O) 4 (OH)(OOH)] 0 , which momentarily disconnects from the negatively charged MOL to avoid the injection of additional electrons. Release of H 2 O 2 from [Ni II (H 2 O) 4 (OH)(OOH)] 0 regenerates [Ni II (H 2 O) 6 ] 2+ , which regains affinity to the MOL. Such dynamically associated Ni II single‐metal electrocatalysts ensure high selectivity and represent a new strategy for generating selective catalysts for electrochemical production of important chemicals.
In situ monitoring of H and O stable isotopes in soil water reveals ecohydrologic dynamics in managed soil systems [Urban ecohydrologic dynamics revealed by in situ monitoring of H and O stable isotopes in soil water]
The water cycle in urban and hydrologically managed settings is subject to perturbations that are dynamic on small spatial and temporal scales; the effects of which may be especially profound in soils. We deploy a membrane inlet-based laser spectroscopy system in conjunction with soil moisture and temperature sensors to monitor soil water dynamics and H and O stable isotope ratios (δ 2 H and δ 18 O values) in a seasonally irrigated urban-landscaped garden soil over the course of 9 months between the cessation of irrigation in the autumn and the onset of irrigation through the summer. Here, we find that soil water δ 2 H and δ 18 O values predominately reflect seasonal precipitation and irrigation inputs. A comparison of total soil water by cryogenic extraction and mobile soil water measured by in situ water vapor probes reveals that initial infiltration events after long periods of soil drying (the autumn season in this case) emplace water into the soil matrix that is not easily replaced by, or mixed with, successive pulses of infiltrating soil water. Tree stem xylem water H and O stable isotope composition did not match that of available water sources. Our findings suggest that partitioning of soil water into mobile and immobile “pools” and resulting ecohydrologic separation may occur in engineered and hydrologically managed soils and not be limited to natural settings. Furthermore, the laser spectroscopy method detailed here has potential to yield insights in a variety of critical zone and vadose zone studies, potential that is heightened by the simplicity and portability of the system.
Cytosolic expression, solution structures, and molecular dynamics simulation of genetically encodable disulfide‐rich de novo designed peptides
Abstract Disulfide‐rich peptides represent an important protein family with broad pharmacological potential. Recent advances in computational methods have made it possible to design new peptides which adopt a stable conformation de novo. Here, we describe a system to produce disulfide‐rich de novo peptides using Escherichia coli as the expression host. The advantage of this system is that it enables production of uniformly 13 C‐ and 15 N‐labeled peptides for solution nuclear magnetic resonance (NMR) studies. This expression system was used to isotopically label two previously reported de novo designed peptides, and to determine their solution structures using NMR. The ensemble of NMR structures calculated for both peptides agreed well with the design models, further confirming the accuracy of the design protocol. Collection of NMR data on the peptides under reducing conditions revealed a dependency on disulfide bonds to maintain stability. Furthermore, we performed long‐time molecular dynamics (MD) simulations with tempering to assess the stability of two families of de novo designed peptides. Initial designs which exhibited a stable structure during simulations were more likely to adopt a stable structure in vitro , but attempts to utilize this method to redesign unstable peptides to fold into a stable state were unsuccessful. Further work is therefore needed to assess the utility of MD simulation techniques for de novo protein design.
From ground to excited electronic state dynamics of electron and ion irradiated graphene nanomaterials
Microscopes utilizing convergent electron and ion beams are emerging as powerful tools for both imaging and manipulating two-dimensional materials with atomic resolution, allowing the ultimate limits of nanofabrication to be realized. In this chapter, we detail the use of time-dependent electronic structure theory to determine the excited state properties and reactivity of functionalized graphene nanostructures. A time-dependent density functional theory treatment of electronic excitations of materials is presented, with specific emphasis on predicting the position-dependent electronic response of two-dimensional nanomaterials to electron beams. The method is demonstrated in a study highlighting the important role that electronic excitation can play in opening reaction pathways relevant to atomically precise defect manipulation in graphene. Finally, we provide some perspective on future development directions for methods of simulating nonequilibrium electronic and vibrational dynamics induced by electron/ion beams.
Anomalous chiral transport in heavy ion collisions from Anomalous-Viscous Fluid Dynamics
Chiral anomaly is a fundamental aspect of quantum theories with chiral fermions. How such microscopic anomaly manifests itself in a macroscopic many-body system with chiral fermions, is a highly nontrivial question that has recently attracted significant interest. As it turns out, unusual transport currents can be induced by chiral anomaly under suitable conditions in such systems, with the notable example of the Chiral Magnetic Effect (CME) where a vector current (e.g. electric current) is generated along an external magnetic field. A lot of efforts have been made to search for CME in heavy ion collisions, by measuring the charge separation effect induced by the CME transport. A crucial challenge in such effort, is the quantitative prediction for the CME signal. In this paper, we develop the Anomalous-Viscous Fluid Dynamics (AVFD) framework, which implements the anomalous fluid dynamics to describe the evolution of fermion currents in QGP, on top of the neutral bulk background described by the VISH2+1 hydrodynamic simulations for heavy ion collisions. With this new tool, we quantitatively and systematically investigate the dependence of the CME signal to a series of theoretical inputs and associated uncertainties. With realistic estimates of initial conditions and magnetic field lifetime, the predicted CME signal is quantitatively consistent with measured change separation data in 200GeV Au–Au collisions. Based on analysis of Au–Au collisions, we further make predictions for the CME observable to be measured in the planned isobaric (Ru–Ru v.s. Zr–Zr) collision experiment, which could provide a most decisive test of the CME in heavy ion collisions.
Interaction-induced transition in the quantum chaotic dynamics of a disordered metal
We demonstrate that a weakly disordered metal with short-range interactions exhibits a transition in the quantum chaotic dynamics when changing the temperature or the interaction strength. For weak interactions, the system displays exponential growth of the out-of-time-ordered correlator (OTOC) of the current operator. The Lyapunov exponent of this growth is temperature-independent in the limit of vanishing interaction. With increasing the temperature or the interaction strength, the system undergoes a transition to a non-chaotic behaviour, for which the exponential growth of the OTOC is absent. We conjecture that the transition manifests itself in the quasiparticle energy-level statistics and also discuss ways of its explicit observation in cold-atom setups.
Comparison of Surface Tension Generation Methods in Smoothed Particle Hydrodynamics for Dynamic Systems
Developing robust numerical models of dynamic surface tension dominated multiphase systems is an ongoing challenge, especially in scenarios with large density and viscosity ratios. This is critical to the design and understanding of various physical and engineering systems, such as fluidized beds, fuel injectors, and drug delivery schemes. Much of the computational work in surface tension dominated multiphase flows has employed the continuum surface force method (CSF) of Brackbill et al. [1], which recasts surface tension from a surface force to a volumetric force that can be imposed in the vicinity of an interface. The CSF method produces accurate results across a variety of systems, however it relies on the identication of surface normals, which can be unreliable under certain conditions. Alternative methods of simulating surface tension have been proposed. Here the advantages and disadvantages of the CSF method in comparison to a pairwise forces (PF) method proposed by Tartakovsky and Panchenko [2] are explored. The CSF and PF methods are used in a smoothed particle hydrodynamics (SPH) framework to model dynamic systems. Results are compared to existing test cases from the literature and to analytic solutions derived from fundamental normal mode behavior of bubbles and droplets. A physical system for which the PF method is more stable and physically appropriate than the CSF method is identied.
Temporal dynamics of CO 2 and CH 4 loss potentials in response to rapid hydrological shifts in tidal freshwater wetland soils
Earth System Models predict climate extremes that will impact regional and global hydrology. Aquatic-terrestrial transition zones like wetlands are subjected to the immediate consequence of climate change with shifts in the magnitude and dynamics of hydrologic flow. Such fluctuating hydrology can alter the nature and rate of biogeochemical transformations and significantly impact the carbon balance of the ecosystem. We tested the impacts of fluctuating hydrology and, specifically, the role of antecedent moisture conditions in determining the dominant carbon loss mechanisms in soils sampled from a tidal freshwater wetland system in the lower Columbia River, WA, USA. Our objective was to understand shifts in biogeochemical processes in response to changing soil moisture, based on soil respiration and methane production rates, and to elucidate such responses based on the observed electron acceptor and metabolite profiles under laboratory conditions. Metabolomics and biogeochemical process rates provided evidence that soil redox was the principal factor driving metabolic function. Fluctuating redox conditions altered terminal electron acceptor and donor availability and recovery strengths of their concentrations in soil such that a disproportionate release of carbon dioxide stemmed from alternative anaerobic degradation processes like sulfate and iron reduction compared to carbon loss due to methano genesis. Our results show that extended and short-term saturation created conditions conducive to increasing metabolite availability for anaerobic decomposition processes, with a significant lag in methanogenesis. In contrast,extended drying caused a cellular-level stress response and rapid recycling of alternate electron acceptors.
Dynamic assessment of urban economy-environment-energy system using system dynamics model: A case study in Beijing
Highlights: • We combine System Dynamics model and Geographic Information System to analyze the energy-environment-economy (3E) system both temporally and spatially, which explicitly explore the interaction of economics, energy, and environment and effects of the key influencing factors. • Beijing is selected as a case study. • Alternative scenarios, e.g., current, technology, energy and environment scenarios are explored and compared. • Simulation results shows that, current scenario is not sustainable; technology scenario is applicable to economic growth; environment scenario maintains a balanced path of development for long term stability. Economic development, accompanying with environmental damage and energy depletion, becomes essential nowadays. There is a complicated and comprehensive interaction between economics, environment and energy. Understanding the operating mechanism of Energy-Environment-Economy model (3E) and its key factors is the inherent part in dealing with the issue. In this paper, we combine System Dynamics model and Geographic Information System to analyze the energy-environment-economy (3E) system both temporally and spatially, which explicitly explore the interaction of economics, energy, and environment and effects of the key influencing factors. Beijing is selected as a case study to verify our SD-GIS model. Alternative scenarios, e.g., current, technology, energy and environment scenarios are explored and compared. Simulation results shows that, current scenario is not sustainable; technology scenario is applicable to economic growth; environment scenario maintains a balanced path of development for long term stability. Policy-making insights are given based on our results and analysis.
Computationally-efficient stochastic cluster dynamics method for modeling damage accumulation in irradiated materials
An improved version of a recently developed stochastic cluster dynamics (SCD) method (Marian and Bulatov, 2012) [6] is introduced as an alternative to rate theory (RT) methods for solving coupled ordinary differential equation (ODE) systems for irradiation damage simulations. SCD circumvents by design the curse of dimensionality of the variable space that renders traditional ODE-based RT approaches inefficient when handling complex defect population comprised of multiple (more than two) defect species. Several improvements introduced here enable efficient and accurate simulations of irradiated materials up to realistic (high) damage doses characteristic of next-generation nuclear systems. The first improvement is a procedure for efficiently updating the defect reaction-network and event selection in the context of a dynamically expanding reaction-network. Next is a novel implementation of the τ-leaping method that speeds up SCD simulations by advancing the state of the reaction network in large time increments when appropriate. Lastly, a volume rescaling procedure is introduced to control the computational complexity of the expanding reaction-network through occasional reductions of the defect population while maintaining accurate statistics. The enhanced SCD method is then applied to model defect cluster accumulation in iron thin films subjected to triple ion-beam (Fe{sup 3+}, He{sup +} and H{sup +}) irradiations, for which standard RT or spatially-resolved kinetic Monte Carlo simulations are prohibitively expensive.
A dissipative particle dynamics method for arbitrarily complex geometries
Not Available
Defect cluster and nonequilibrium gas bubble associated growth in irradiated UMo fuels – a cluster dynamics and phase field model
Irradiation examination shows that gas bubble swelling kinetics is much faster after irradiation-induced recrystallization than that prior recrystallization in UMo fuels. It implies that gas bubbles in coarse grains and small recrystallized grains have different growth behavior. In this work, a phase-field model of gas bubble evolution integrating microstructure dependent cluster dynamics has been developed, for the first time, to study the gas bubble swelling behavior in the recrystallization zone of UMo fuels. Generation, diffusion, reaction, sink, emission and clustering of vacancies and interstitials are described by the cluster dynamics model while a phase-field model is used to describe the evolution of non-equilibrium gas bubbles including nucleation and growth. With the coupled model, the effect of defect generation rate, clustering rate, interstitial emission and sink rates on grain boundaries on the gas bubble evolution are systematically simulated. A set of model parameters (defect generation rate, clustering rate, interstitial emission and sink rates) is determined by comparing measured and simulated gas bubble swelling kinetics. The results demonstrate that interstitial clustering is one of the important physical mechanisms which results in a fast gas bubble swelling kinetics in the recrystallization zone. The developed model can also be extended to study the associated growth of defect and second phase precipitates often observed in irradiated materials.