AIMC Topic: Polymers

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Generating a vast chemical space for high polar surface area triphenylamine polymers by machine learning-DFT calculations assisted reverse engineering for photovoltaics.

Journal of molecular graphics & modelling
The total polar surface area (TPSA) is a crucial parameter in photovoltaic (PV) materials, as it directly influences their solubility, processability, and device performance. This study leverages machine learning-assisted reverse engineering to gener...

Anticoagulation colloidal microrobots based on heparin-mimicking polymers.

Journal of colloid and interface science
Coagulation within blood vessels is a major cause of cardiovascular disease and global mortality, highlighting the urgent need for effective anticoagulant strategies. In this study, we introduce a dynamic and highly efficient anticoagulant platform, ...

Application of rheology to hot melt extrusion: Theory and practice.

International journal of pharmaceutics
Hot melt extrusion (HME) has become a key manufacturing method in the pharmaceutical industry for developing novel drug delivery systems, due to its solvent-free nature, ease of operation, and ability to achieve one-step molding and continuous proces...

Assessing Uncertainty in Machine Learning for Polymer Property Prediction: A Benchmark Study.

Journal of chemical information and modeling
Machine learning (ML) has emerged as a transformative tool in material science, enabling accelerated discovery and design of novel molecules while reducing experimental costs. Uncertainty quantification (UQ) is crucial for enhancing the reliability o...

Band Gap and Reorganization Energy Prediction of Conducting Polymers by the Integration of Machine Learning and Density Functional Theory.

Journal of chemical information and modeling
The performance and reliability of machine learning (ML)-quantitative structure-property relationship (QSPR) models depend on the quality, size, and diversity of the data set used for model training. In this study, we manually curated a large-scale d...

A Multichannel Continuum Robot for Diagnosis and Treatment of Vascular Lesions.

ACS biomaterials science & engineering
In recent years, continuum soft robots have emerged as a promising avenue for the advancement of therapeutic interventions. However, the current continuum robots are often limited to singular functionalities and exhibit a deficiency in diagnostic ca...

PolyCrit: An Online Collaborative Platform for Polymer Characterization.

Journal of chromatography. A
Polymer liquid chromatography at critical conditions (LCCC) is a chromatographic separation condition achieved by carefully balancing the interaction of a polymer with stationary and mobile phases to make the elution time of a polymer in chromatograp...

Prediction of the Appropriate Temperature and Pressure for Polymer Dissolution Using Machine Learning Models.

Molecular informatics
The widespread use of polymer solutions in the chemical industry poses a significant challenge in determining optimal dissolution conditions. Traditionally, researchers have relied on experimental methods to estimate the processing parameters needed ...

Multi-Cover Persistence (MCP)-based machine learning for polymer property prediction.

Briefings in bioinformatics
Accurate and efficient prediction of polymers properties is crucial for polymer design. Recently, data-driven artificial intelligence (AI) models have demonstrated great promise in polymers property analysis. Even with the great progresses, a pivotal...

Effects of interlayer reflection and interpixel interaction in diffractive optical neural networks.

Optics letters
Multilayer diffractive optical neural networks (DONNs) can perform machine learning (ML) tasks at the speed of light with low energy consumption. Decreasing the number of diffractive layers can reduce inevitable material and diffraction losses to imp...