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Continuous time nonlinear dynamical system states variables estimated suboptimally from discrete noisy measurements with second order nonlinear filter, deriving dynamical equations
Information theoretic measures have helped to sharpen our understanding of many-body quantum states. As perhaps the most well-known example, the entanglement entropy (or more generally, the bipartite mutual information) has become a powerful tool for characterizing the dynamical growth of quantum correlations. By contrast, although computable, the bipartite mutual information (MI) is almost never explored in classical many particle systems; this owes in part to the fact that computing the MI requires keeping track of the evolution of the full probability distribution, a feat which is rarely done (or thought to be needed) in classical many-body simulations. Here, we utilize the MI to analyze the spreading of information in 1D elementary cellular automata (CA). Broadly speaking, we find that the behavior of the MI in these dynamical systems exhibits a few different types of scaling that roughly correspond to known CA universality classes. Of particular note is that we observe a set of automata for which the MI converges parametrically slowly to its thermodynamic value. We develop a microscopic understanding of this behavior by analyzing a two-species model of annihilating particles moving in opposite directions. Furthermore, our work suggests the possibility that information theoretic tools such as the MI might enable a more fine-grained characterization of classical many-body states and dynamics.
Abstract High‐efficiency separation of C 6 alkanes, particularly the mono‐ and dibranched isomers by using porous solids, is of paramount significance in the petrochemical industry and, remains a daunting challenge. In this work, we report the complete separation of linear/monobranched hexanes from their dibranched isomers through selective size‐exclusion by a microporous MOF, Zn‐tcpt (H 3 tcpt=2,4,6‐tris(4‐carboxyphenoxy)‐1,3,5‐triazine), with a two‐fold interpenetrated structure of hms nets. Importantly, its adsorption capacity and selectivity are notably higher than those of the previously reported adsorbents that can split mono‐ and dibranched alkane isomers. Dynamic breakthrough measurements verify the excellent separation of C 6 alkane isomers by Zn‐tcpt, and the size‐exclusion based separation mechanism has been confirmed by ab initio materials modeling. The high‐efficiency separation of alkane isomers by Zn‐tcpt can be attributed to its optimal pore dimensions as well as high porosity.
High-efficiency separation of C 6 alkanes, particularly the mono- and dibranched isomers by using porous solids, is of paramount significance in the petrochemical industry and, remains a daunting challenge. In this work, we report the complete separation of linear/monobranched hexanes from their dibranched isomers through selective size-exclusion by a microporous MOF, Zn-tcpt (H3tcpt=2,4,6-tris(4-carboxyphenoxy)-1,3,5-triazine), with a two-fold interpenetrated structure of hms nets. Importantly, its adsorption capacity and selectivity are notably higher than those of the previously reported adsorbents that can split mono- and dibranched alkane isomers. Dynamic breakthrough measurements verify the excellent separation of C 6 alkane isomers by Zn-tcpt, and the size-exclusion based separation mechanism has been confirmed by ab initio materials modeling. Furthermore, the high-efficiency separation of alkane isomers by Zn-tcpt can be attributed to its optimal pore dimensions as well as high porosity.
Abstract Understanding the interactive behavior of Janus particles (JPs) is a growing field of research. The enhancement in binding energy, in comparison to homogenous particles, and the dual characteristic of JPs open up new possibilities for novel applications. In many such applications, interfacial materials become subjected to flows that produce dilational and shear stresses. Therefore, it is important to understand the impact that the Janus character brings to interfaces. In this work, we study the microstructure of two-dimensional (2D) JP monolayers formed at the air–water interface and examine the shear viscoelasticity with an interface rheometer that was adapted for in situ surface pressure control via a Langmuir trough. We extend concepts from bulk rheology to data obtained from interfacial rheology as a tool to understand and predict the monolayer’s viscoelastic behavior. Finally, by calculating the time relaxation spectrum from the measured 2D dynamic moduli, we conclude that a phenomenon similar to glass transition is taking place by analogy.
Digital image correlation (DIC) is an established test technique in several fields including quasi-static displacement measurements. Recently there has been growing interest in using DIC to measure structural dynamic response and even extract modal parameters from that information. Although high-speed cameras have become more ubiquitous, there are no commercial end-to-end packages for modal analysis based on image data, particularly when combined with traditional data acquisition systems. As such, the practitioner is left to develop several key data processing capabilities, hardware interface equipment, and testing practices themselves. This work highlights several practical aspects that have been encountered while establishing DIC as a viable modal testing capability in a laboratory environment.
The deacetylation process is a key step in the lignocellulosic biomass pretreatment process that currently is done in batch reactors. A flow-through diffuser type reactor is a promising approach to make the process more efficient and economically favorable. A washing step before deacetylation can further reduce chemical usage and increase the process efficiency. However, the highly compacted biomass particles can cause significant pressure-drop for fluid flow through the bed, which in the worst case can cause self-enhancing pressure-drop leading to reactor blocking. Detailed understanding of the fundamentals of flow through a compressible packed bed is necessary to scale up the washing and deacetylation process. This work closely examines the classical Kozeny Carman equation and proposes modifications to accurately predict the pressure-drop at different compaction states. Here, a compressible packed bed model is further developed based on the interaction between solid mechanics and fluid dynamics. Experimental measurements of water flow through a packed bed of corn stover show good agreement with the developed model. Corn stover washing process scale up simulations show that smaller reactor diameter, higher friction lining material, lower process throughput, and higher process temperature is favorable in stabilizing the bed from extensive compression when the bed height is fixed.
The neutron radio frequency (RF) spin flipper is one of the key components to implement neutron resonance spin echo (NRSE) for high resolution measurements of dynamics in materials. Various types of RF flippers have been built and implemented including adiabatic and non-adiabatic RF flippers. For a pulsed neutron source, adiabatic RF flipper is more favorable due to its wide operation bandwidth. However, the optimization criteria of an adiabatic RF flipper is still lacking. Also they are difficult to be operated in bootstrap mode, which can be use to minimize the phase aberration and increase the achievable resolution. In the report by Dadisman et al. (2019), an adiabatic RF flipper has been built for the first time with superconducting technologies, which allows bootstrap mode. Here in this article, the method of optimizing the device and the detailed design will be discussed for each component of the device.
This paper describes force and stability prediction for inserted end and face mills using a reverse engineering approach. Structured light scanning is used to identify the spatial coordinates of the points that define the multiple insert cutting edges. These points are used to extract the cutting edge radius and angle and are then incorporated in a time domain simulation that predicts cutting force and tool/workpiece deflection for user-selected operating parameters. Good agreement between predicted and measured cutting forces is demonstrated. The process stability is then predicted using the validated force model and measured structural dynamics.
Here, this paper presents an approach for inserted end/face mill force and stability predictions using a reverse engineering approach. Structured light scanning is implemented to identify the spatial coordinates of the points that define the multiple insert cutting edges. These points are analyzed to extract the cutting edge radius and angle values, which are then incorporated in a time domain simulation that predicts cutting force and tool/workpiece deflection for user-selected operating parameters. Good agreement between predicted and measured cutting forces is first demonstrated. The process stability is then predicted using the validated force model and measured structural dynamics. Observations about the stability dependence on insert geometry are finally presented for a selected end mill.
OsO 4 and RuO 4 are molecular oxides with unique tetrameric structures and rare +8 oxidation states. Accurately modeling their properties remains challenging for density functional theory (DFT) due to weak intertetramer interactions, which standard functionals fail to capture. Here, in this work, we show that the van der Waals (vdW)-corrected density functional (vdW-DF-optB86b) provides structural parameters that are much closer to experimental values than the standard generalized gradient approximation, with volume predictions that fall within the experimentally observed range. Phonon band structure analysis shows that the inclusion of vdW interactions stabilizes soft phonon modes, highlighting the importance of dispersion corrections for accurate predictions of lattice dynamics. Experimental measurements of the phonon density of states for OsO 4 , obtained via inelastic neutron scattering, demonstrate good agreement with our vdW-DF-optB86b calculations. These results validate OsO 4 and RuO 4 as valuable benchmarks for structural and vibrational calculations via vdW-corrected DFT methods and offer insights for studying the broader class of sparse molecular materials.
The particle-like magnetic skyrmion or skyrmion lattice (SkX) formation has promoted strong application and fundamental science interests. Despite extensive research, the kinetic of the SkX development is much less understood because of the ultrafast spin rotation and high sensitivity to external perturbations. In this work, using in situ Lorentz transmission electron microscopy, we successfully measured the dynamics of SkX formation from the conical phase with precise control of both the temperature and the magnetic field. We discovered that the Avrami equation can accurately describe the transition process with an initial Avrami constant around 1, suggesting that the rate-limiting step for the quasiparticle lattice formation is one-dimensional heterogeneous nucleation of individual skyrmions. A modified Arrhenius rate law is established, with an energy barrier that has a square-root dependence on temperature and a quadratic dependence on the magnetic field. This study paves the way toward precise and predictable manipulation of topological spin structures.
There is broad interest in layered, two-dimensional (2D) semiconductors owing to their high optical absorption and ability to heterogeneously integrate with various substrates. In such layered semiconductors, mesoscopic imperfections, such as surface step edges, may affect charge carrier kinetics and device performance, but studying their effects on carrier transport with sufficient spatial and temporal resolution is a challenge. Using scanning ultrafast electron microscopy, we image the near-surface charge carrier kinetics with μm/ps spatiotemporal resolution in single-crystal MoS 2 samples with surface steps tens of nanometers in height. We find an approximately 3-fold increase in surface trap density near such surface steps compared to the uniform, flat surface regions. Despite the difference in trap state density, filling of the traps occurs over the same time scale (∼100 ps), but carrier recovery is much slower near the step compared to the uniform regions of the material. Furthermore, these results provide an approach to measure ultrafast dynamics and determine the required uniformity of layered materials depending on the speed limit constraints for specific applications.
Electrochemical CO 2 reduction on Cu is a promising approach to produce value-added chemicals using renewable feedstocks, yet various Cu preparations have led to differences in activity and selectivity toward single and multicarbon products. Here, we find, surprisingly, that the effective catalytic activity toward ethylene improves when there is a larger fraction of less active sites acting as reservoirs of *CO on the surface of Cu nanoparticle electrocatalysts. In an adaptation of chemical transient kinetics to electrocatalysis, we measure the dynamic response of a gas diffusion electrode (GDE) cell when the feed gas is abruptly switched between Ar (inert) and CO. When switching from Ar to CO, CO reduction (COR) begins promptly, but when switching from CO to Ar, COR can be maintained for several seconds (delay time) despite the absence of the CO reactant in the gas phase. A three-site microkinetic model captures the observed dynamic behavior and shows that Cu catalysts exhibiting delay times have a less active *CO reservoir that exhibits fast diffusion to active sites. The observed delay times and the estimated *CO reservoir sizes are affected by catalyst preparation, applied potential, and microenvironment (electrolyte cation identity, electrolyte pH, and CO partial pressure). Notably, we estimate that the *CO reservoir surface coverage can be as high as 88 ± 7% on oxide-derived Cu (OD-Cu) at high overpotentials (–1.52 V vs SHE) and this increases in reservoir coverage coincide with increased turnover frequencies to ethylene. We also estimate that *CO can travel substantial distances (up to 10s of nm) prior to desorption or reaction. It appears that active C–C coupling sites by themselves do not control selectivity to C 2+ products in electrochemical COR; the supply of CO to those sites is also a crucial factor. More generally, the overall activity of Cu electrocatalysts cannot be approximated from linear combinations of individual site activities. Future designs must consider the diversity of the catalyst network and account for intersite transportation pathways.
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Sorbents for direct air capture (DAC) of CO 2 typically employ a chemisorbing material that requires regeneration at elevated temperatures, which is an energy-intensive step. Here, we developed composites of metal organic framework (MOF) with a functional ionic liquid (IL) at 5, 20, and 35 wt % loading, capable of CO 2 chemisorption and regeneration by moisture-swing coupled microwave (MW) irradiation. In dynamic breakthrough measurements, CO 2 from synthetic air (500 ppm of CO 2 ) was selectively absorbed (0.5 mmol/g at 30 °C) and then rapidly released (2–4 min) by dielectric heating at 60 °C. The developed IL/MOF composites demonstrate (1) targeted energy transfer to the IL domains where CO 2 is released due to dielectric heating upon MW irradiation and (2) a fast desorption rate due to large surface area offered by the MOF architecture. Furthermore, this study establishes carbon capture through surface enhancement of a porous substrate with ILs for future DAC processes that can be powered by sustainable energy sources.
We demonstrate a strategy that allows for the spontaneous reconfiguration of self-assembled DNA polymers exploiting RNA as chemical fuel. To do this, we have rationally designed orthogonally addressable DNA building blocks that can be transiently deactivated by RNA fuels and subtracted temporarily from participation in the self-assembly process. Through a fine modulation of the rate at which the building blocks are reactivated we can carefully control the final composition of the polymer and convert a disordered polymer in a higher order polymer, which is disfavored from a thermodynamic point of view. We measure the dynamic reconfiguration via fluorescent signals and confocal microscopy, and we derive a kinetic model that captures the experimental results. Our approach suggests a novel route toward the development of biomolecular materials in which engineered chemical reactions support the autonomous spatial reorganization of multiple components.