Direct visualization of the charge transfer state dynamics in dilute-donor organic photovoltaic blends
Nature Communications Springer Nature 15:1 (2024) 9851
Abstract:
The interconversion dynamics between charge transfer state charges (CTCs) and separated charges (SCs) is still an unresolved issue in the field of organic photovoltaics. Here, a transient absorption spectroscopy (TAS) study of a thermally evaporated small-molecule:fullerene system (α6T:C60) in different morphologies (dilute intermixed and phase separated) is presented. Spectral decomposition reveals two charge species with distinct absorption characteristics and different dynamics. Using time-dependent density functional theory, these species are identified as CTCs and SCs, where the spectral differences arise from broken symmetry in the charge transfer state that turns forbidden transitions into allowed ones. Based on this assignment, a kinetic model is formulated allowing the characterization of the charge generation, separation, and recombination mechanisms. We find that SCs are either formed directly from excitons within a few picoseconds or more slowly (~30–80 ps) from reversible splitting of CTCs. These findings constitute the first unambiguous observation of spectrally resolved CTCs and SCs.From generation to collection – impact of deposition temperature on charge carrier dynamics of high-performance vacuum-processed organic solar cells
Energy & Environmental Science Royal Society of Chemistry (RSC) (2024)
Abstract:
<jats:p>Substrate heating during co-evaporation of bulk heterojunction organic solar cells aids phase separation and improves performance. While recombination remains unaffected, hole transport improves due to more crystalline donor domains.</jats:p>Roadmap on established and emerging photovoltaics for sustainable energy conversion
Journal of Physics: Energy IOP Publishing (2024)
Abstract:
Machine learning discovery of cost-efficient dry cooler designs for concentrated solar power plants
Scientific Reports Nature Research 14:1 (2024) 19086
Abstract:
Concentrated solar power (CSP) is one of the few sustainable energy technologies that offers day-to-night energy storage. Recent development of the supercritical carbon dioxide (sCO2) Brayton cycle has made CSP a potentially cost-competitive energy source. However, as CSP plants are most efficient in desert regions, where there is high solar irradiance and low land cost, careful design of a dry cooling system is crucial to make CSP practical. In this work, we present a machine learning system to optimize the factory design and configuration of a dry cooling system for an sCO2 Brayton cycle CSP plant. For this, we develop a physics-based simulation of the cooling properties of an air-cooled heat exchanger. The simulator is able to construct a dry cooling system satisfying a wide variety of power cycle requirements (e.g., 10–100 MW) for any surface air temperature. Using this simulator, we leverage recent results in high-dimensional Bayesian optimization to optimize dry cooler designs that minimize lifetime cost for a given location, reducing this cost by 67% compared to recently proposed designs. Our simulation and optimization framework can increase the development pace of economically-viable sustainable energy generation systems.Improved reverse bias stability in p–i–n perovskite solar cells with optimized hole transport materials and less reactive electrodes
Nature Energy Nature Research 9:10 (2024) 1275-1284