Slow Photons for Photocatalysis and Photovoltaics

Solar light is widely recognized as one of the most valuable renewable energy sources for the future. However, the development of solar-energy technologies is severely hindered by poor energy-conversion efficiencies due to low optical-absorption coefficients and low quantum-conversion yield of current-generation materials. Huge efforts have been devoted to investigating new strategies to improve the utilization of solar energy. Different chemical and physical strategies have been used to extend the spectral range or increase the conversion efficiency of materials, leading to very promising results. However, these methods have now begun to reach their limits. What is therefore the next big concept that could efficiently be used to enhance light harvesting? Despite its discovery many years ago, with the potential for becoming a powerful tool for enhanced light harvesting, the slow-photon effect, a manifestation of light-propagation control due to photonic structures, has largely been overlooked. This review presents theoretical as well as experimental progress on this effect, revealing that the photoreactivity of materials can be dramatically enhanced by exploiting slow photons. It is predicted that successful implementation of this strategy may open a very promising avenue for a broad spectrum of light-energy-conversion technologies

Segregated Algorithms for the Numerical Simulation of Cardiac Electromechanics in the Left Human Ventricle

We propose and numerically assess three segregated ( partitioned) algorithms for the numerical solution of the coupled electromechanics problem for the left human ventricle. We split the coupled problem into its core mathematical models and we proceed to their numerical approximation. Space and time discretizations of the core problems are carried out by means of the Finite Element Method and Backward Differentiation Formulas, respectively. In our mathematical model, electrophysiology is represented by the monodomain equation while the Holzapfel-Ogden strain energy function is used for the passive characterization of tissue mechanics. A transmurally variable active strain model is used for the active deformation of the fibers of the myocardium to couple the electrophysiology and the mechanics in the framework of the active strain model. In this work, we focus on the numerical strategy to deal with the solution of the coupled model, which is based on novel segregated algorithms that we propose. These also allow using different time discretization schemes for the core submodels, thus leading to the formulation of staggered algorithms, a feature that we systematically exploit to increase the efficiency of the overall computational procedure. By means of numerical tests we show that these staggered algorithms feature (at least) first order of accuracy. We take advantage of the efficiency of the segregated schemes to solve, in a High Performance Computing framework, the cardiac electromechanics problem for the human left ventricle, for both idealized and subject-specific configurations