Assessing the Conformational Landscape of Dicarboxylic Acids Using Ab Initio Molecular Dynamics: The Role of Phase and Intermolecular Interactions

构象异构 分子间力 计算化学 能源景观 化学 分子动力学 化学物理 从头算 氢键 分子 密度泛函理论 反应性(心理学) 最大值和最小值 有机化学 数学分析 病理 医学 生物化学 数学 替代医学
作者
Kelsey Richardson,Mahdi M. Abu‐Omar,Phillip Christopher,Vojtěch Vlček
出处
期刊:Journal of Physical Chemistry B [American Chemical Society]
卷期号:129 (28): 7195-7202
标识
DOI:10.1021/acs.jpcb.5c01628
摘要

Molecules often adopt multiple conformations with distinct energies and reactivities, making it essential to characterize their conformational free energy landscape to understand their reactivity. Traditionally, computational studies identify stable molecular configurations using direct energy minimization with density functional theory (DFT), which effectively locates local minima. However, this approach does not fully capture the conformational landscape, particularly in the condensed phase where intermolecular interactions are playing a significant role. Here, we address this limitation by employing ab initio molecular dynamics (AIMD) to simulate the conformers of three dicarboxylic acids (DCAs), in both vapor and condensed phases. Our findings show that while direct energy minimization predicts the predominant conformer for fumaric acid (FA), AIMD is necessary to account for complex intermolecular interactions that stabilize additional conformers in succinic acid (SA) and maleic acid (MA). Specifically, AIMD reveals conformers that direct energy minimization does not predict to be thermally accessible but are stabilized by condensed-phase interactions. Additionally, we demonstrate a direct correlation between the density of the SA environment and the probability of forming external hydrogen bonds, which affects the conformational distribution. Finally, we demonstrate that these conformational distributions can serve as predictors for reactivity in an industrially relevant polyurethane acidolysis reaction.
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
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
sen发布了新的文献求助10
刚刚
rocka发布了新的文献求助10
1秒前
1秒前
dj发布了新的文献求助10
1秒前
慕青应助zch采纳,获得10
1秒前
顺利手套完成签到,获得积分10
2秒前
jam发布了新的文献求助10
2秒前
陶醉发箍完成签到 ,获得积分10
2秒前
3秒前
欢呼完成签到,获得积分10
3秒前
单薄绿海发布了新的文献求助10
3秒前
哈基米完成签到,获得积分10
4秒前
Jasper应助科研通管家采纳,获得10
4秒前
英姑应助科研通管家采纳,获得30
4秒前
Ava应助科研通管家采纳,获得10
4秒前
FashionBoy应助科研通管家采纳,获得10
4秒前
v0id应助科研通管家采纳,获得10
4秒前
打打应助科研通管家采纳,获得10
4秒前
传奇3应助科研通管家采纳,获得10
5秒前
xqx发布了新的文献求助30
5秒前
桐桐应助朴实成风采纳,获得10
5秒前
Akim应助sw采纳,获得10
6秒前
科研小白完成签到,获得积分10
6秒前
6秒前
跳跃凝阳完成签到,获得积分10
6秒前
领导范儿应助好运粥采纳,获得10
7秒前
时尚平露完成签到,获得积分20
7秒前
7秒前
ding应助弗洛伊德的梦采纳,获得10
8秒前
yimax完成签到 ,获得积分10
8秒前
Uranus发布了新的文献求助30
8秒前
冷静的无颜完成签到 ,获得积分10
9秒前
li发布了新的文献求助10
9秒前
leaf发布了新的文献求助10
10秒前
10秒前
zqs发布了新的文献求助10
11秒前
13秒前
科研通AI6.4应助兴奋如松采纳,获得10
13秒前
13秒前
DW应助Lin采纳,获得10
14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
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
A Case Study on Hotels as Noncongregate Emergency Living Accommodations for Returning Citizens 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 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7764230
求助须知:如何正确求助?哪些是违规求助? 9308452
关于积分的说明 20305907
捐赠科研通 7348907
什么是DOI,文献DOI怎么找? 3314299
关于科研通互助平台的介绍 2463883
邀请新用户注册赠送积分活动 2328400