A study on the formaldehyde emission parameters of porous building materials based on adsorption potential theory

吸附 热扩散率 材料科学 扩散 多孔性 热力学 甲醛 多孔介质 分配系数 化学 物理化学 复合材料 物理 色谱法 有机化学
作者
Xiaojun Zhou,Yanfeng Liu,Cong Song,Jiaping Liu
出处
期刊:Building and Environment [Elsevier BV]
卷期号:106: 254-264 被引量:23
标识
DOI:10.1016/j.buildenv.2016.07.003
摘要

The emission of formaldehyde from building materials is characterized by three key parameters: the initial emittable concentration, the partition coefficient, and the diffusion coefficient. Scholars have conducted considerable research to determine these three parameters. However, the experimental methods are mostly time consuming, and the experimental data cannot provide a mechanism to explain the influence of the main control factors on the emission parameters. Theoretical prediction models have been built to predict a certain parameter based on different theories and with different applicable scopes. Thus, it is necessary to establish a theoretical system that can analyze the formaldehyde emission process based on a fundamental theory and can simultaneously predict the emission parameters. Based on adsorption potential theory, this paper disassembled the pore structure of porous building materials and calculated the adsorption potential for a given pore diameter. According to the relationship between the molecular kinetic energy and the adsorption potential, the emittable ratios for each independent potential field were calculated. The initial emittable concentration of the whole material was finally obtained by reconstruction. Our previous study proposed a prediction model for the partition coefficient based on adsorption potential theory. Combining this proposed model with the effective diffusivity model, a new correlation between the diffusion coefficient and temperature was derived. Three types of medium density fiberboards and one type of particle board were used in the mercury intrusion porosimetry tests and the environmental chamber experiments of formaldehyde emission. The emission parameters calculated by the prediction models agreed well with the experimental data.

科研通智能强力驱动
Strongly Powered by AbleSci AI
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
lzq发布了新的文献求助10
刚刚
刚刚
刚刚
刚刚
刚刚
brown完成签到,获得积分10
1秒前
1秒前
英姑应助科研通管家采纳,获得10
1秒前
1秒前
爆米花应助科研通管家采纳,获得10
1秒前
乘云去发布了新的文献求助10
3秒前
koui发布了新的文献求助10
4秒前
桐拾叁完成签到,获得积分10
4秒前
科研通AI2S应助JieyuWen采纳,获得10
5秒前
不三不四完成签到,获得积分10
6秒前
心灵美致远完成签到,获得积分10
7秒前
可莉完成签到 ,获得积分10
8秒前
标致踏歌发布了新的文献求助10
9秒前
10秒前
DZ完成签到,获得积分10
12秒前
勤恳的仙人掌完成签到 ,获得积分10
14秒前
科研通AI6.1应助可可采纳,获得10
14秒前
彭于晏应助桐拾叁采纳,获得10
15秒前
18秒前
19秒前
Iloveyou完成签到,获得积分10
21秒前
21秒前
黄函发布了新的文献求助10
23秒前
Sunnig盈完成签到,获得积分10
23秒前
yao发布了新的文献求助10
27秒前
Zjt完成签到,获得积分10
27秒前
han发布了新的文献求助30
28秒前
29秒前
yulian完成签到,获得积分10
29秒前
tom完成签到,获得积分10
32秒前
HY发布了新的文献求助10
34秒前
34秒前
34秒前
随便起个吧完成签到 ,获得积分10
35秒前
yao完成签到,获得积分10
37秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Various Faces of Animal Metaphor in English and Polish 800
Signals, Systems, and Signal Processing 610
Photodetectors: From Ultraviolet to Infrared 500
On the Dragon Seas, a sailor's adventures in the far east 500
Yangtze Reminiscences. Some Notes And Recollections Of Service With The China Navigation Company Ltd., 1925-1939 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6353286
求助须知:如何正确求助?哪些是违规求助? 8168273
关于积分的说明 17192186
捐赠科研通 5409372
什么是DOI,文献DOI怎么找? 2863734
邀请新用户注册赠送积分活动 1841051
关于科研通互助平台的介绍 1689834