Related papers: Exploring high thermal conductivity polymers via i…
Tailoring the thermal conductivity of polymers is central to enlarge their applications in the thermal management of flexible integrated circuits. Progress has been made over the past decade by fabricating materials with various…
The development of differentiable invariant descriptors for accurate representations of atomic environments plays a central role in the success of interatomic potentials for chemistry and materials science. We introduce a method to generate…
Thermoresponsive polymer architectures have become integral building blocks of 'smart' functional materials in modern applications. For a large range of developments, e.g., for drug delivery or nanocatalytic carrier systems, the selective…
Poly(ethylene terephthalate) (PET), a widely used thermoplastic in packaging, textiles, and engineering applications, is valued for its strength, clarity, and chemical resistance. Increasing environmental impact concerns and regulatory…
Tuning the heat flow is fundamentally important for the design of advanced functional materials. Here, polymers are of particular importance because they provide different pathways for the energy transfer. More specifically, the heat flow…
Accurate simulation of the printing process is essential for improving print quality, reducing waste, and optimizing the printing parameters of extrusion-based additive manufacturing. Traditional additive manufacturing simulations are very…
Scanning Thermal Microscopy (SThM) uses micromachined thermal sensors integrated in a force sensing cantilever with a nanoscale tip can be highly useful for exploration of thermal management of nanoscale semiconductor devices. As well as…
Predicting optoelectronic properties of large-scale atomistic systems under realistic conditions is crucial for rational materials design, yet computationally prohibitive with first-principles simulations. Recent neural network models have…
The development of smart polymer materials is reviewed and illustrated. Important examples of these polymers include conducting polymers, ionic gels, stimulus-response be used polymers, liquid crystalline polymers and piezoelectric…
Accurate prediction of pure component physiochemical properties is crucial for process integration, multiscale modeling, and optimization. In this work, an enhanced framework for pure component property prediction by using explainable…
Hybrid molecular dynamics/Monte Carlo simulations used to study melts of unentangled, thermoreversibly associating supramolecular polymers. In this first of a series of papers, we describe and validate a model that is effective in…
Photostriction is a phenomenon that can potentially improve the precision of light-driven actuation, the sensitivity of photodetection, and the efficiency of optical energy harvesting. However, known materials with significant…
Deep learning models were developed and implemented to aid the search for new heavy fermion compounds. For the purpose of these calculations a database of more than 200 heavy fermions was compiled from the literature. The deep learning…
Machine learning techniques are used to explore the intrinsic origins of the hydrodynamic thermal transport and to find new materials interesting for science and engineering. The hydrodynamic thermal transport is governed intrinsically by…
Predicting the strength of materials requires considering various length and time scales, striking a balance between accuracy and efficiency. Peierls stress measures material strength by evaluating dislocation resistance to plastic flow,…
Synthetic polymeric materials underpin fundamental technologies in the energy, electronics, consumer goods, and medical sectors, yet their development still suffers from prolonged design timelines. Although polymer informatics tools have…
Understanding the thermal behavior of additive manufacturing (AM) processes is crucial for enhancing the quality control and enabling customized process design. Most purely physics-based computational models suffer from intensive…
Modern product design in the engineering domain is increasingly driven by computational analysis including finite-element based simulation, computational optimization, and modern data analysis techniques such as machine learning. To apply…
The thermodynamics and transport properties of polymeric materials are essential for the design of reactors and for the development of polymer deconstruction processes. Existing property prediction tools such as correlations based on…
Polymer-related materials exhibit rich glassy behaviors at different length scales due to their various molecular structures and topological constraints. Recent studies have identified transient interpenetration of the long-chain rings…