相关论文: Computational discovery of bifunctional organic se…
Light activated local stimulation and sensing of biological cells offers enormous potential for minimally invasive bioelectronic interfaces. Organic semiconductors are a promising material class to achieve this kind of transduction due to…
Solar cells based on organic compounds are a proven emergent alternative to conventional electrical energy generation. Here, we provide a computational study of power conversion efficiency optimization of BODIPY-derivatives by means of…
High-performance programmable silicon photonic circuits are considered to be a critical part of next generation architectures for optical processing, photonic quantum circuits and neural networks. Low-loss optical phase change materials…
Computational searching and screening of new functional materials exploiting earth abundant elements can accelerate developments of their energy applications. Based on a state-of-the-art materials search algorithm and ab initio…
Over the last two decades the organic solar cell community has synthesised tens of thousands of novel polymers and small molecules in the search for an optimum light harvesting material. These materials were often crudely evaluated simply…
Numerical simulation of a solar cell can provide various information that can be useful to maximize its power conversion efficiency (PCE). In that respect we carried out a set of numerical simulation using AFORS-HET simulation program.…
Simultaneously optimizing performances, processability and fabrication cost of organic electronic materials is the continual source of compromise hindering the development of disruptive applications. In this work, we identified a strategy…
In the past decade, photoemission orbital tomography (POT) has evolved into a powerful tool to investigate the electronic structure of organic molecules adsorbed on surfaces. Here we show that POT allows for the comprehensive experimental…
Tailoring the functional properties of advanced organic/inorganic heterogeonous devices to their intended technological applications requires knowledge and control of the microscopic structure inside the device. Atomistic quantum mechanical…
Finding low-energy molecular conformers is challenging due to the high dimensionality of the search space and the computational cost of accurate quantum chemical methods for determining conformer structures and energies. Here, we combine…
This monograph describes nine years of research carried out at the Institute for Electronics, Micro-electronics and Nanotechnologies (IEMN), developed around defining a generic concept for detection, filling a void between metrological…
We discuss implications of a recent experimental breakthrough which uses a fluorescence-doped flexible semiconducting polymer to construct a single-molecule sensor which can detect ultra-weak forces in the molecular environment, with a grey…
Perovskite solar cells (PSCs) have experienced a remarkable rise in power conversion efficiency (PCE) over the past 15 years, positioning them as a promising alternative or complement to silicon for large-scale photovoltaic deployment.…
Machine learning methods have shown promise in predicting molecular properties, and given sufficient training data machine learning approaches can enable rapid high-throughput virtual screening of large libraries of compounds. Graph-based…
Neural networks have proven effective for solving many difficult computational problems. Implementing complex neural networks in software is very computationally expensive. To explore the limits of information processing, it will be…
Cu based ternary chalcogenides are gathering attention for sustainable energy applications due to their reduced complexity compared to quaternary alternatives. We used drift diffusion modeling to evaluate the feasibility of photovoltaics…
Proteins perform critical processes in all living systems: converting solar energy into chemical energy, replicating DNA, as the basis of highly performant materials, sensing and much more. While an incredible range of functionality has…
Quantum Computing (QC) offers outstanding potential for molecular characterization and drug discovery, particularly in solving complex properties like the Ground State Energy (GSE) of biomolecules. However, QC faces challenges due to…
Harnessing the optoelectronic response of organic semiconductors requires a thorough understanding of the fundamental light-matter interaction that is dominated by the excitation of correlated electron-hole pairs, i.e. excitons. The nature…
In recent years, GW-BSE has been proven to be extremely successful in studying the quasiparticle (QP) bandstructures and excitonic effects in the optical properties of materials. However, the massive computational cost associated with such…