6 research outputs found
A multiscale modeling study of loss processes in block-copolymer-based solar cell nanodevices
Flexible photovoltaic devices possess promising perspectives in opto-electronic technologies, where high mobility and/or large-scale applicability are important. However, their usefulness in such applications is currently still limited due to the low level of optimization of their performance and durability. For the improvement of these properties, a better understanding and control of small-scale annihilation phenomena involved in the photovoltaic process, such as exciton loss and charge carrier loss, is necessary, which typically implicates multiple length- and time-scales. Here, we study the causes for their occurrence on the example of nanostructured diblock- and triblock-copolymer systems by making use of a novel solar-cell simulation algorithm and explore new routes to optimize their photovoltaic properties. A particular focus is set on the investigation of exciton and charge carrier loss phenomena and their dependence on the inter-monomeric interaction strength, chain architecture, and external mechanical loading. Our simulation results reveal that in the regime from low up to intermediate χ-parameters an increasing number of continuous percolation paths is created. In this parameter range, the internal quantum efficiency (IQE) increases up to a maximum, characterized by a minimum in the number of charge losses due to charge recombination. In the regime of high χ-parameters both block-copolymer systems form nanostructures with a large number of bottlenecks and dead ends. These lead to a large number of charge losses due to charge recombination, charge trapping, and a deteriorated exciton dissociation, resulting in a significant drop in the IQE. Moreover, we find that the photovoltaic performance of the triblock-copolymer material decreases with increasing mechanical loading, caused by a growing number of charge losses due to charge recombination and charge accumulation. Finally, we demonstrate that the process of charge trapping in defects can be reversed by changing the polarity of the electrodes, which confers these materials the ability to be used as charge storage media
A new multiscale modeling method for simulating the loss processes in polymer solar cell nanodevices
The photoelectric power conversion efficiency of polymer solar cells is till now, compared to conventional inorganic solar cells, still relatively low with maximum values ranging from 7% to 8%. This essentially relates to the existence of exciton and charge carrier loss phenomena, reducing the performance of polymer solar cells significantly. In this paper we introduce a new computer simulation technique, which permits to explore the causes of the occurrence of such phenomena at the nanoscale and to design new photovoltaic materials with optimized opto-electronic properties. Our approach consists in coupling a mesoscopic field-theoretic method with a suitable dynamic Monte Carlo algorithm, to model the elementary photovoltaic processes. Using this algorithm, we investigate the influence of structural characteristics and different device conditions on the exciton generation and charge transport efficiencies in case of a novel nanostructured polymer blend. More specifically, we find that the disjunction of continuous percolation paths leads to the creation of dead ends, resulting in charge carrier losses through charge recombination. Moreover, we observe that defects are characterized by a low exciton dissociation efficiency due to a high charge accumulation, counteracting the charge generation process. From these observations, we conclude that both the charge carrier loss and the exciton loss phenomena lead to a dramatic decrease in the internal quantum efficiency. Finally, by analyzing the photovoltaic behavior of the nanostructures under different circuit conditions, we demonstrate that charge injection significantly determines the impact of the defects on the solar cell performance
Development and application of field-based multiscale modeling techniques for optimizing the performance of polymer nanodevices
The goal of this thesis was to develop and apply field-based multiscale modeling techniques, to better understand and improve the performance of polymer-based nanodevices, used in optoelectronic applications. For this purpose, we used the SCFT technique, to compute the polymeric morphologies, in combination with a suitable DMC algorithm, to simulate the photovoltaic processes. The application of this coupled multiscale approach enabled us to treat a large variety of polymer systems of large system size at low computational costs
Flow-Induced Formation of Thin PEO Fibers in Water and Their Stability After the Strain Release
A multiscale modeling study of loss processes in block-copolymer-based solar cell nanodevices
Probing Silica–Biomolecule Interactions by Solid-State NMR and Molecular Dynamics Simulations
Understanding
the molecular interactions between inorganic phases
such as silica and organic material is fundamental for chromatographic
applications, for tailoring silica–enzyme interactions, and
for elucidating the mechanisms of biomineralization. The formation,
structure, and properties of the organic/inorganic interface is crucial
in this context. Here, we investigate the interaction of selectively <sup>13</sup>C-labeled choline with <sup>29</sup>Si-labeled monosilicic
acid/silica at the molecular level. Silica/choline nanocomposites
were analyzed by solid-state NMR spectroscopy in combination with
extended molecular dynamics (MD) simulations to understand the silica/organic
interface. Cross-polarization magic angle spinning (CP MAS)-based
NMR experiments like <sup>1</sup>H–<sup>13</sup>C CP-REDOR
(rotational-echo double resonance), <sup>1</sup>H–<sup>13</sup>C HETCOR (heteronuclear correlation), and <sup>1</sup>H–<sup>29</sup>Si–<sup>1</sup>H double CP are employed to determine
spatial parameters. The measurement of <sup>29</sup>Si–<sup>13</sup>C internuclear distances for selectively <sup>13</sup>C-labeled
choline provides an experimental parameter that allows the direct
verification of MD simulations. Atomistic modeling using classical
MD methodologies is performed using the INTERFACE force field. The
modeling results are in excellent agreement with the experimental
data and reveal the relevant molecular conformations as well as the
nature and interplay of the interactions between the choline cation
and the silica surface. Electrostatic interactions and hydrogen bonding
are both important and depend strongly on the hydration level as well
as the charge state of the silica surface