Related papers: The pH sensitivity of solvated tectomer electronic…
A lattice model of a hetero-polymer with random hydrophilic-hydrophobic charges interacting with the solvent is introduced, whose continnuum counterpart has been proposed by T. Garel, L. Leibler and H. Orland {J. Phys. II France 4, 2139…
Biocompatible microencapsulation is of widespread interest for the targeted delivery of active species in fields such as pharmaceuticals, cosmetics and agro-chemistry. Capsules obtained by the self-assembly of polymers at interfaces enable…
The self-organized dopant percolative filamentary model, entirely orbital in character (no fictive spins), explains chemical trends in superconductive transition temperatures Tc, assuming that Cooper pairs are formed near dopants because…
Liquids are an important part of many common manipulation tasks in human environments. If we wish to have robots that can accomplish these types of tasks, they must be able to interact with liquids in an intelligent manner. In this paper,…
Recent advances in experimental and computational techniques have allowed for an accurate description of the adsorption of ionic liquids on metallic electrodes. It is now well established that they adopt a multi-layered structure, and that…
Knotted fields in classical and quantum systems have long been recognized for their non-trivial topologies and particle-like behavior, but practical applications have been limited by the difficulty of stabilizing them. Recently, stable…
Liquid electrolytes are critical components of next-generation energy storage systems, enabling fast ion transport, minimizing interfacial resistance, and ensuring electrochemical stability for long-term battery performance. However,…
We propose the first, to our knowledge, coarse-grained modeling strategy for peptides where the effect of changes of the pH can be efficiently described. The idea is based on modeling the effects of the pH value on the main driving…
Progress in the application of machine learning techniques to the prediction of solid-state and molecular materials properties has been greatly facilitated by the development state-of-the-art feature representations and novel deep learning…
Flexible photonics offers the possibility to realize wearable sensors by bridging the advantages of flexible materials and photonic sensing elements. Recently, optical resonators have emerged as a tool to improve its over sensitivity by…
Solving geometric tasks involving point clouds by using machine learning is a challenging problem. Standard feed-forward neural networks combine linear or, if the bias parameter is included, affine layers and activation functions. Their…
A simple model for the formation of the polymer-enzyme conjugates has been proposed and described using corresponding extension of the Wertheim's first-order thermodynamic perturbation theory (TPT1) for the system of associating chain…
We present thermopneumatic pixels (TPPs), which are tactile actuators designed for rapid fabrication and straightforward integration into compact wearable and surface-based haptic systems. Each TPP converts low-voltage ($\sim$10 V)…
The covalent functionalisation of type I atelocollagen with either 4-vinylbenzyl or methacrylamide residues is presented as a simple synthetic strategy to achieve customisable, cell-friendly UV-cured hydrogel networks with widespread…
Soft matter materials and polymers are widely used in the controlled delivery of drugs. Simulation and modeling provide insight at the atomic scale enabling a level of control unavailable to experiments. We present a workflow protocol for…
Model order reduction provides low-complexity high-fidelity surrogate models that allow rapid and accurate solutions of parametric differential equations. The development of reduced order models for parametric \emph{nonlinear} Hamiltonian…
Micro and nanostructured electrodes form an integral part of a wide variety of electrochemical systems for biomolecule detection, batteries, solar cells, scanning electrochemical microscopy, etc. Given the complexity of the electrode…
We propose a grid-like computational model of tubular reactors. The architecture is inspired by the computations performed by solvers of partial differential equations which describe the dynamics of the chemical process inside a tubular…
Polymers underpin applications across energy, healthcare, and materials science, yet their vast chemical space makes systematic discovery challenging. Most machine learning approaches represent polymers as molecular graphs of a single…
Determining the structure of water adsorbed on solid surfaces is a notoriously difficult task, and pushes the limits of experimental and theoretical techniques. Here, we follow the evolution of water agglomerates on Fe3O4(001); a complex…