In this paper, analytic modeling for the design of a transient thermal invisibility cloak with imperfect interfaces is presented together with numerical simulations. In contrast to steady-state conditions, it is shown that an object can only be made partially invisible under a transient-state condition with either ideal or imperfect interfaces. The thermal visibility of an object to the external region can be optimally suppressed under certain conditions referred to as the "weak invisibility conditions" for the transient response, which are different from the "strong invisibility conditions" that can completely conceal an object in a steady state. In the formulation, a homogeneous metamaterial with constant volumetric heat capacity and constant anisotropic conductivity tensor is employed. It can be demonstrated that the interface's bonding conditions will have a significant effect on the design of metamaterials. Two typical types of imperfect interfaces, referred to as low-conductivity- and high-conductivity-type interfaces, are considered. Conditions, that render an object mostly undetectable, are analytically found and expressed in simple forms under quasi-static approximations. Within the quasi-static limit, the thermal localization in the target region can be tuned with the anisotropy of the conductivity tensor. Thermal shielding or concentrating effects in the target region are exemplified based on finite element simulations to demonstrate the manipulation of heat flux in the target region. The present findings make new advances in theoretical fundamentals and numerical simulations on the effect of the imperfect interface in the transient regime and can serve as guidelines in the design of thermal metamaterials through the entire conduction process.
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http://dx.doi.org/10.3390/ma16062297 | DOI Listing |
Proteins have proven to be useful agents in a variety of fields, from serving as potent therapeutics to enabling complex catalysis for chemical manufacture. However, they remain difficult to design and are instead typically selected for using extensive screens or directed evolution. Recent developments in protein large language models have enabled fast generation of diverse protein sequences in unexplored regions of protein space predicted to fold into varied structures, bind relevant targets, and catalyze novel reactions.
View Article and Find Full Text PDFNeuroimage
February 2025
Medical Physics Department, Centre François Baclesse, Caen 14000, France; CNRS, ISTCT UMR6030, GIP CYCERON, Normandie Université, Université de Caen Normandie, Caen 14000, France. Electronic address:
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View Article and Find Full Text PDFACS Appl Mater Interfaces
January 2025
Barrer Centre, Department of Chemical Engineering, Imperial College London, London SW7 2AZ, United Kingdom.
Graphene oxide (GO)-based membranes have demonstrated great potential in water treatment. However, microdefects in the framework of GO membranes induced by the imperfect stacking of GO nanosheets undermine their size-sieving ability and structural stability in aqueous systems. This study proposes a targeted growth approach by growing zeolitic imidazolate framework-8 (ZIF-8) nanocrystals precisely to patch microdefects as well as to cross-link the porous graphene oxide (PGO) flakes coated on the outer surface of the hollow fiber (HF) alumina substrate (named the hybrid PGO/ZIF-8 membrane).
View Article and Find Full Text PDFSoft Matter
January 2025
Department of Physics, Durham University, Durham, DH1 3LE, UK.
Nanoparticle adhesion at liquid interfaces plays an important role in drug delivery, dust removal, the adsorption of aerosols, and controlled self-assembly. However, quantitative measurements of capillary interactions at the nanoscale are challenging, with most existing results at the micrometre to millimetre scale. Here, we combine atomic force microscopy (AFM) and computational simulations to investigate the adhesion and removal of nanoparticles from liquid interfaces as a function of the particles' geometry and wettability.
View Article and Find Full Text PDFIntracortical motor brain-computer interfaces (BCIs) are expensive and time-consuming to design because accurate evaluation traditionally requires real-time experiments. In a BCI system, a user interacts with an imperfect decoder and continuously changes motor commands in response to unexpected decoded movements. This "closed-loop" nature of BCI leads to emergent interactions between the user and decoder that are challenging to model.
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