The ideal adsorbed solution (IAS) theory is the benchmark for the prediction of mixed-gas adsorption equilibria from pure-component isotherms. In this work, we use atomistic grand canonical Monte Carlo simulations to test the effects of molecular siting and adsorbent energetic heterogeneity on the applicability of the IAS theory. Pure-component isotherms generated by atomistic simulation are used to predict binary isobaric isotherms using the IAS theory. These predicted isotherms are compared with those obtained by a full atomistic simulation of the binary mixture. Binary mixtures of argon, methane, and CF4 in silicalite are found to obey IAS theory, while benzene/methane and cyclohexane/methane in silicalite are nonideal. The mixture of argon and CF4 is ideal despite the large difference in the sizes of the two species. This contradicts previous hypotheses in the literature, which state that mixtures of species of unequal size do not adsorb ideally. The nonideal behavior of the benzene/methane and cyclohexane/methane systems occurs because of adsorbent heterogeneity in these systems, which depends on both sorbent and sorbate. In addition, we use a lattice gas model with parameters derived from atomistic simulation to demonstrate analytically that a sufficiently energetically heterogeneous adsorbent will result in the breakdown of IAS theory even in the absence of interactions between sorbates.
Many excited states in the hadron spectrum have large branching ratios to three-hadron final states. Understanding such particles from first principles QCD requires input from lattice QCD with one-, two-, and three-meson interpolators as well as a reliable three-body formalism relating finite-volume spectra at unphysical pion mass values to the scattering amplitudes at the physical point. In this work, we provide the first-ever calculation of the resonance parameters of the ω meson from lattice QCD, including an update of the formalism through matching to effective field theories.
CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, PR China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China.
Objective: Interoception plays an important role in psychological functioning and mental and physical health. Recent studies have highlighted the need to distinguish between different aspects of interoception in self-report measures, including subjective interoceptive accuracy and attention. However, there is currently no questionnaire available in Chinese to measure either of these aspects, especially in patients with chronic pain conditions.
We study the fine structure constant dependence of the rates of some selected radiative capture reactions within the framework of so-called Halo Effective Field Theory in order to assess the adequacy of some assumptions made on the Coulomb penetrability. We find that this dependence deviates from that implied by a parameterization of the cross sections of this effect via a simple penetration factor. Some features of this fine-structure dependence are discussed, in particular its potential impact on the abundances of the light elements in primordial nucleosynthesis.
Hadronic resonances emerge from strong interactions encoding the dynamics of quarks and gluons. The structure of these resonances can be probed by virtual photons parametrized in transition form factors. In this study, twelve N^{*} and Δ transition form factors at the pole are extracted from data with the center-of-mass energy from πN threshold to 1.
Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, 52428 Jülich, Germany.
The susceptible-infected-recovered (SIR) model and its variants form the foundation of our understanding of the spread of diseases. Here, each agent can be in one of three states (susceptible, infected, or recovered), and transitions between these states follow a stochastic process. The probability of an agent becoming infected depends on the number of its infected neighbors, hence all agents are correlated.
