Is one performing the treatment data of adsorption kinetics correctly?

动力学 吸附 非线性系统 热力学 动能 数学 曲线拟合 应用数学 反应速率常数 线性模型 常量(计算机编程) 化学 统计 物理 物理化学 计算机科学 经典力学 量子力学 程序设计语言
作者
Éder C. Lima,Farooq Sher,Ashish Guleria,Mohammad Reza Saeb,Ioannis Anastopoulos,Hai Nguyen Tran,Ahmad Hosseini‐Bandegharaei
出处
期刊:Journal of environmental chemical engineering [Elsevier BV]
卷期号:9 (2): 104813-104813 被引量:267
标识
DOI:10.1016/j.jece.2020.104813
摘要

In the literature, the linear form of the pseudo-first-order (PFO) and pseudo-second-order (PSO) models are often applied for fitting the data of adsorption kinetics. Many authors have applied the linear form of the PSO model and concluded that such a kinetics is better fitted, based on the values of adsorption capacity at the equilibrium (qe) and the high value (which should be close to 1.0) of the coefficient of determination (R2). The linearized PFO model is usually ruled-out because the values of qe and R2 are worse than those obtained by the linearized PSO. On the other hand, the nonlinear fitting of data is highly recommended for the use of equations that are not typically linear such as kinetics data. In this communication, the data of 52 articles (containing 225 experiments of adsorption kinetics) were collected, and the kinetic data were treated using the linear and nonlinear PFO and PSO models. Results indicated that the values of k2 (the rate constant of the PSO model) calculated from the nonlinear fitting method were quite different from those acquired from the linear one. However, the values of qe2 (adsorption capacity at the equilibrium of the PSO model) are in complete agreement, which induces users to an erroneous decision. Using a linearized kinetic model, all the 225 values of R2 of the PSO model were closer to 1.0 than PFO. However, when nonlinearized fitting of the data was used, 122 out of 225 cases (54.22%) showed that the nonlinear PFO is better fitted than the PSO kinetic model.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
wo_qq111完成签到,获得积分10
1秒前
糟糕的学姐完成签到,获得积分10
1秒前
白白白发布了新的文献求助10
3秒前
Hello应助饿得咕咕地采纳,获得10
3秒前
科研通AI5应助勤奋幻柏采纳,获得30
3秒前
3秒前
4秒前
amy发布了新的文献求助10
4秒前
sci_zt发布了新的文献求助10
5秒前
5秒前
鳗鱼中心完成签到,获得积分10
6秒前
科目三应助z1z1z采纳,获得10
7秒前
8秒前
8秒前
彪壮的一曲完成签到 ,获得积分20
10秒前
JamesPei应助amy采纳,获得10
11秒前
1l2kl发布了新的文献求助10
12秒前
13秒前
14秒前
英俊的铭应助li采纳,获得10
15秒前
丘比特应助时尚的如南采纳,获得10
16秒前
科研通AI5应助kingfisher采纳,获得10
16秒前
Wanfeng发布了新的文献求助200
18秒前
打打应助ljw采纳,获得10
20秒前
典雅的语蝶完成签到,获得积分10
20秒前
田様应助oweing采纳,获得10
21秒前
领导范儿应助科研通管家采纳,获得10
22秒前
pluto应助科研通管家采纳,获得10
22秒前
科研通AI5应助科研通管家采纳,获得10
22秒前
科研通AI5应助科研通管家采纳,获得10
22秒前
慕青应助科研通管家采纳,获得10
23秒前
脑洞疼应助scichu采纳,获得10
23秒前
李爱国应助科研通管家采纳,获得10
23秒前
Akim应助科研通管家采纳,获得10
23秒前
科研通AI2S应助科研通管家采纳,获得10
23秒前
星辰大海应助科研通管家采纳,获得10
23秒前
子车茗应助科研通管家采纳,获得30
23秒前
23秒前
pluto应助科研通管家采纳,获得10
23秒前
pluto应助科研通管家采纳,获得10
23秒前
高分求助中
(应助此贴封号)【重要!!请各位详细阅读】【科研通的精品贴汇总】 10000
Quantum reference frames : from quantum information to spacetime 888
줄기세포 생물학 800
Pediatric Injectable Drugs 500
Instant Bonding Epoxy Technology 500
ASHP Injectable Drug Information 2025 Edition 400
DEALKOXYLATION OF β-CYANOPROPIONALDEYHDE DIMETHYL ACETAL 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4386576
求助须知:如何正确求助?哪些是违规求助? 3878893
关于积分的说明 12082974
捐赠科研通 3522486
什么是DOI,文献DOI怎么找? 1933199
邀请新用户注册赠送积分活动 974147
科研通“疑难数据库(出版商)”最低求助积分说明 872339