The capture of CO2 by biochar has recently become one of the cornerstones of circular economy models for a sustainable society. In this work, we synthesized an activated biocarbon using Trametes ...gibbosa (BioACTG) in a one-step synthesis. We investigated CO2 adsorption mechanisms under five different temperatures using a statistical physics approach. The data was better represented by the multilayer model with two distinguished energies, providing more accurate values for the estimated parameters. According to the number of carbon dioxide molecules per site (n) and the densities of the receptor sites (Dzif), the tendency to form a second layer increased as the temperature increased. The adsorption of CO2 on BioACTG was exothermic (the values of Qasat = 15.5 mmol/g at 273 K decrease to 10.5 mmol/g at 353 K), and the temperature influenced CO2 as well as the morphological features of the process. A computational approach was used to investigate the electronic properties of the adsorbate, showing that its lowest unoccupied orbital (LUMO) heavily contributed to the high efficiency of the process which was ruled by pore diffusion mechanisms driven by energetic fluctuations. Other molecules present in CO2-rich mixtures were also investigated, showing that their concentration limited their competitiveness with CO2.
Adjusted isotherms of CO2 adsorbed onto BioACTG by the multilayer model with saturation. Display omitted
•BioACTG uptake of CO2 occurred in multilayer.•Temperature highly influenced the adsorbate energetic distributions.•The morphological features of the adsorbent varied as temperature increased.•Pore diffusion was driven by LUMO.•Competitive effects would only be significant in high concentration.
Global warming, extreme climate events, earthquakes and their accompanying socioeconomic disasters pose significant risks to humanity. Yet due to the nonlinear feedbacks, multiple interactions and ...complex structures of the Earth system, the understanding and, in particular, the prediction of such disruptive events represent formidable challenges to both scientific and policy communities. During the past years, the emergence and evolution of Earth system science has attracted much attention and produced new concepts and frameworks. Especially, novel statistical physics and complex networks-based techniques have been developed and implemented to substantially advance our knowledge of the Earth system, including climate extreme events, earthquakes and geological relief features, leading to substantially improved predictive performances. We present here a comprehensive review on the recent scientific progress in the development and application of how combined statistical physics and complex systems science approaches such as critical phenomena, network theory, percolation, tipping points analysis, and entropy can be applied to complex Earth systems. Notably, these integrating tools and approaches provide new insights and perspectives for understanding the dynamics of the Earth systems. The overall aim of this review is to offer readers the knowledge on how statistical physics concepts and theories can be useful in the field of Earth system science.
We introduce an efficient numerical implementation of a Markov Chain Monte Carlo method to sample a probability distribution on a manifold (introduced theoretically in Zappa, Holmes-Cerfon, Goodman ...(2018) 53), where the manifold is defined by the level set of constraint functions, and the probability distribution may involve the pseudodeterminant of the Jacobian of the constraints, as arises in physical sampling problems. The algorithm is easy to implement and scales well to problems with thousands of dimensions and with complex sets of constraints provided their Jacobian retains sparsity. The algorithm uses direct linear algebra and requires a single matrix factorization per proposal point, which enhances its efficiency over previously proposed methods but becomes the computational bottleneck of the algorithm in high dimensions. We test the algorithm on several examples inspired by soft-matter physics and materials science to study its complexity and properties.
•Introduces numerical algorithm for sampling probability distribution on a manifold.•Manifold is defined by level set of constraint functions, such as bond-distances.•Algorithm is efficient in problems with thousands of dimensions.•Requires one sparse matrix factorization per proposal point.•Tested on examples from soft-matter physics with “soft” constraints.
A classical metastable state possesses a local free energy minimum at infinite sizes, but not a global one. This concept is phase size independent. We have studied a number of experimental results ...and proposed a new concept that there exists a wide range of metastable states in polymers on different length scales where their metastability is critically determined by the phase size and dimensionality. Metastable states are also observed in phase transformations that are kinetically impeded on the pathway to thermodynamic equilibrium. This was illustrated in structural and morphological investigations of crystallization and mesophase transitions, liquid-liquid phase separation, vitrification and gel formation, as well as combinations of these transformation processes. The phase behaviours in polymers are thus dominated by interlinks of metastable states on different length scales. This concept successfully explains many experimental observations and provides a new way to connect different aspects of polymer physics.
* Written by a leading scholar and industry expert* Presents new and cutting edge material encouraging innovation and future research* Connects hot topics and leading research in one concise volume
For a one-dimensional spin chain with random local interactions, we prove that many-body localization follows from a physically reasonable assumption that limits the amount of level attraction in the ...system. The construction uses a sequence of local unitary transformations to diagonalize the Hamiltonian and connect the exact many-body eigenfunctions to the original basis vectors.
The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, ...or clustering, i.e. the organization of vertices in clusters, with many edges joining vertices of the same cluster and comparatively few edges joining vertices of different clusters. Such clusters, or communities, can be considered as fairly independent compartments of a graph, playing a similar role like, e.g., the tissues or the organs in the human body. Detecting communities is of great importance in sociology, biology and computer science, disciplines where systems are often represented as graphs. This problem is very hard and not yet satisfactorily solved, despite the huge effort of a large interdisciplinary community of scientists working on it over the past few years. We will attempt a thorough exposition of the topic, from the definition of the main elements of the problem, to the presentation of most methods developed, with a special focus on techniques designed by statistical physicists, from the discussion of crucial issues like the significance of clustering and how methods should be tested and compared against each other, to the description of applications to real networks.
MEMS Linear and Nonlinear Statics and Dynamicspresents the necessary analytical and computational tools for MEMS designers to model and simulate most known MEMS devices, structures, and phenomena. ...This book also provides an in-depth analysis and treatment of the most common static and dynamic phenomena in MEMS that are encountered by engineers. Coverage also includes nonlinear modeling approaches to modeling various MEMS phenomena of a nonlinear nature, such as those due to electrostatic forces, squeeze-film damping, and large deflection of structures. The book also:Includes examples of numerous MEMS devices and structures that require static or dynamic modelingProvides code for programs in Matlab, Mathematica, and ANSYS for simulating the behavior of MEMS structuresProvides real world problems related to the dynamics of MEMS such as dynamics of electrostatically actuated devices, stiction and adhesion of microbeams due to electrostatic and capillary forcesMEMS Linear and Nonlinear Statics and Dynamics is an ideal volume for researchers and engineers working in MEMS design and fabrication.
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