Nonlinear dynamical modeling of adsorption and desorption processes with power-law kinetics: Application to CO_{2} capture.

Phys Rev E

IMS Laboratory, Bordeaux University, UMR CNRS 5218-351, Cours de la Libération, 33405 Talence Cedex, France.

Published: November 2020

Modeling of random sequential adsorption (RSA) process is studied in this paper as this kind of process is close to the surface adsorption phenomenon that is, for instance, exploited in gas sensors or for liquid or gas purification. Analysis and simulation of the RSA process is first performed to highlight a power-law kinetic behavior. Such behaviors are often modeled in the literature with fractional models. The paper, however, shows that fractional models are not able to capture some important properties of the RSA process. A nonlinear model and the associated parameters tuning method are, thus, proposed. A discussion on the ability of the proposed model to capture the power-law kinetics without exhibiting some of the drawbacks of fractional models is proposed. This nonlinear model is then modified to take into account the reverse desorption process. The proposed modeling approach is applied to experimental data of CO_{2} capture.

Download full-text PDF

Source
http://dx.doi.org/10.1103/PhysRevE.102.052102DOI Listing

Publication Analysis

Top Keywords

rsa process
12
fractional models
12
power-law kinetics
8
co_{2} capture
8
nonlinear model
8
process
5
nonlinear dynamical
4
dynamical modeling
4
modeling adsorption
4
adsorption desorption
4

Similar Publications

Background: Alzheimer's Disease (AD) is characterized by progressive impairment of cognition and memory, including the loss of episodic memory. The use of non-invasive brain stimulation therapies to modulate memory encoding processes is a promising avenue for potential treatment. Previous studies have shown that the use of Transcranial Magnetic Stimulation (TMS) applied to lateral parietal cortex can improve memory in older adults who have received a diagnosis of Mild Cognitive Impairment.

View Article and Find Full Text PDF

Clinical Manifestations.

Alzheimers Dement

December 2024

KU Leuven, Leuven, Belgium.

Background: Connected speech has been explored as a possible marker for Alzheimer's disease (AD) by employing language models based on machine learning. However, most previous approaches are based on scene description tasks, and it is unclear how different types of connected speech and differences across subjects' speech relate to changes in their brains.

Method: We analyzed transcripts of Flemish Dutch connected speech from interviews from 74 cognitively healthy elderly adults (mean MMSE = 28.

View Article and Find Full Text PDF

Efficient control strategy for electric furnace temperature regulation using quadratic interpolation optimization.

Sci Rep

January 2025

Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics, National Academy of Sciences of Ukraine, Beresteyskiy, 56, Kyiv-57, Kyiv, 03680, Ukraine.

Electric furnaces play an important role in many industrial processes where precise temperature control is essential to ensure production efficiency and product quality. Traditional proportional-integral-derivative (PID) controllers and their modified versions are commonly used to maintain temperature stability by reacting quickly to deviations. In this study, the real PID plus second-order derivative (RPIDD) controller is introduced for the first time for industrial temperature control applications, which is a novel alternative that has not yet been investigated in the literature.

View Article and Find Full Text PDF

Deep language models (DLMs) have exhibited remarkable language understanding and generation capabilities, prompting researchers to explore the similarities between their internal mechanisms and human language cognitive processing. This study investigated the representational similarity (RS) between the abstractive summarization (ABS) models and the human brain and its correlation to the performance of ABS tasks. Specifically, representational similarity analysis (RSA) was used to measure the similarity between the representational patterns (RPs) of the BART, PEGASUS, and T5 models' hidden layers and the human brain's language RPs under different spatiotemporal conditions.

View Article and Find Full Text PDF

Objective: To explore the biological relationship between the regulatory signal pathways involved in differentially expressed genes and recurrent spontaneous abortion (RSA) by analyzing the gene expression microarray data of unexplained RSA.

Methods: The gene expression profile data of chorionic villi from unexplained recurrent abortion with normal karyotype and selective induced abortion were compared. Differentially expressed genes were analyzed by the "Limma" package in R Studio, and Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis were carried out with "Cluster Profiler" and "org.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!