Combining <i>ab initio</i> and <i>ab initio</i> molecular dynamics simulations to predict the complex refractive indices of organic polymers

Wang, Chengchao; Li, Xiaoning

doi:10.1039/d2cp04768c

Cited by 2 publications

(2 citation statements)

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“…The specific structures in polymers result in diverse properties and applications, for example, fibers, films, storage containers, pipes, cables, and so on. Although many studies have been conducted in the computational investigations of polymers, [264–268] the usage of HTC method is relatively limited in these studies. The following reasons should not be ignored.…”

Section: Applications Of Htc In Materials Developmentmentioning

confidence: 99%

Advances in data‐assisted high‐throughput computations for material design

Xu,

Zhang,

Huo

et al. 2023

Materials Genome Engineering Advances

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Extensive trial and error in the variable space is the main cause of low efficiency and high cost in material development. The experimental tasks can be reduced significantly in the case that the variable space is narrowed down by reliable computer simulations. Because of their numerous variables in material design, however, the variable space is still too large to be accessed thoroughly even with a computational approach. High‐throughput computations (HTC) make it possible to complete a material screening in a large space by replacing the conventionally manual and sequential operations with automatic, robust, and concurrent streamlines. The efficiency of HTC, which is one of the pillars of materials genome engineering, has been verified in many studies, but its applications are still limited by demanding computational costs. Introduction of data mining and artificial intelligence into HTC has become an effective approach to solve the problem. In the past years, many studies have focused on the development and application of HTC and data combined approaches, which is considered as a new paradigm in computational materials science. This review focuses on the main advances in the field of data‐assisted HTC for material research and development and provides our outlook on its future development.

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Section: Applications Of Htc In Materials Developmentmentioning

confidence: 99%

Advances in data‐assisted high‐throughput computations for material design

Xu,

Zhang,

Huo

et al. 2023

Materials Genome Engineering Advances

View full text Add to dashboard Cite

show abstract

“…12 We can predict modified polymers either by laboratory preparation or by real-time timedependent density functional theory (TDDFT) and ab initio molecular dynamics (AIMD) simulations. 13,14 However, there are still some key issues that limit the practical application of modified polymers, such as (1) most modified polymers need to be prepared via multi-step reactions and have complex synthesis steps, resulting in their low yields and high costs; (2) the large number of aromatic ring structures in the molecule reduces the transmittance of the material, 15 and the introduction of excessive sulfur atoms worsens the thermodynamic stability; 16 (3) the substitution of atoms or groups tends to deteriorate the stability of the polymer structure; 17 (4) the refractive index of the modified polymers formed by adding atoms or groups to the organic polymer is generally below 1.8. 15,18,19 The other approach is to disperse highly refractive inorganic nanoparticles into the organic polymer to form composites.…”

Section: Introductionmentioning

confidence: 99%