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We develop a transferable machine learning model which predicts structural relaxation from amorphous supercooled liquid structures. The trained networks are able to predict dynamic heterogeneity across a broad range of temperatures and time…
Photomechanical actuation is demonstrated in two coupled liquid crystal elastomer photomechanical optical devices (PODs) acting in series. The response function of an individual POD is characterized and used to predict the temporal response…
Simulation techniques based on accurate and efficient representations of potential energy surfaces are urgently needed for the understanding of complex aqueous systems such as solid-liquid interfaces. Here, we present a machine learning…
The homotopy theory of topological defects is a powerful tool for organizing and unifying many ideas across a broad range of physical systems. Recently, experimental progress has been made in controlling and measuring colloidal inclusions…
The enthalpy of mixing in the liquid phase is a thermodynamic property reflecting interactions between elements that is key to predict phase transformations. Widely used models exist to predict it, but they have never been systematically…
Based on deep neural networks (DNNs), deep learning has been successfully applied to many problems, but its mechanism is still not well understood -- especially the reason why over-parametrized DNNs can generalize. A recent statistical…
The importance of haptic in-sensor computing devices has been increasing. In this study, we successfully fabricated a haptic sensor with a hierarchical structure via the sacrificial template method, using carbon…
We present a unified framework to systematically embed complex knotted and linked structures, beyond the torus family, into diverse topological phases, including Hopf insulators, classical spin liquids, topological semimetals, and…
The success of the Materials Genome Initiative has led to opportunities for data-driven approaches for materials discovery. The recent development of Polymer Genome (PG), which is a machine learning (ML) based data-driven informatics…
As high-performance organic semiconductors, {\pi}-conjugated polymers have attracted much attention due to their charming advantages including low-cost, solution processability, mechanical flexibility, and tunable optoelectronic properties.…
The conformational behavior of a coarse-grained finite polymer chain near an attractive spherical surface was investigated by means of multicanonical Monte Carlo computer simulations. In a detailed analysis of canonical equilibrium data…
Topological superfluids are of technological relevance since they are believed to host Majorana bound states, a powerful resource for quantum computation and memory. Here we propose to realize topological superfluidity with fermionic atoms…
Living organisms rely on molecular networks, such as gene circuits and signaling pathways, for information processing and robust decision-making in crowded, noisy environments. Recent advances show that interacting biomolecules…
In 2008, researchers at the Hewlett-Packard (HP) laboratories claimed to have found an analytical physical model for a genuine memristor device [1]. The model is considered for a thin TiO_2 film containing a region which is highly…
Structural and thermodynamic properties of the model solution containing charged oligomers and the equivalent number of counterions were studied by means of the canonical Monte Carlo simulation technique. The oligomers are represented as…
The two-phase thermodynamic (2PT) model {[}J. Chem. Phys., \textbf{119}, 11792 (2003){]} provides a promising paradigm to efficiently determine the ionic entropies of liquids from molecular dynamics (MD). In this model, the vibrational…
This article reviews recent progress in two-dimensional (2D) hybrid structures that integrate transition metal dichalcogenides (TMDs) with photochromic molecules for photodetector applications. Atomically thin TMD semiconductors offer…
An ensemble of electrons trapped above superfluid helium offers a paradigm system for investigating and controlling collective charge dynamics in low-dimensional electronic matter. Of particular interest is the ability to spatially control…
The recent rapid deployment of datacenter infrastructures for performing large language models (LLMs) and related artificial intelligence (AI) applications in the clouds is predicted to incur an exponentially growing energy consumption in…
In biology, ligand mediated transitions (LMT), where the binding of a molecular ligand onto the binding site of a receptor molecule leads to a well-defined change in the conformation of the receptor, are often referred to as 'the second…