Nonfullerene solar cells have increased their efficiencies up to 13%, yet quantum efficiencies are still limited to 80%. Here we report efficient nonfullerene solar cells with quantum efficiencies ...approaching unity. This is achieved with overlapping absorption bands of donor and acceptor that increases the photon absorption strength in the range from about 570 to 700 nm, thus, almost all incident photons are absorbed in the active layer. The charges generated are found to dissociate with negligible geminate recombination losses resulting in a short-circuit current density of 20 mA cm
along with open-circuit voltages >1 V, which is remarkable for a 1.6 eV bandgap system. Most importantly, the unique nano-morphology of the donor:acceptor blend results in a substantially improved stability under illumination. Understanding the efficient charge separation in nonfullerene acceptors can pave the way to robust and recombination-free organic solar cells.
Molecular doping is often used in organic semiconductors to tune their (opto)electronic properties. Despite its versatility, however, its application in organic photovoltaics (OPVs) remains limited ...and restricted to p‐type dopants. In an effort to control the charge transport within the bulk‐heterojunction (BHJ) of OPVs, the n‐type dopant benzyl viologen (BV) is incorporated in a BHJ composed of the donor polymer PM6 and the small‐molecule acceptor IT‐4F. The power conversion efficiency (PCE) of the cells is found to increase from 13.2% to 14.4% upon addition of 0.004 wt% BV. Analysis of the photoactive materials and devices reveals that BV acts simultaneously as n‐type dopant and microstructure modifier for the BHJ. Under optimal BV concentrations, these synergistic effects result in balanced hole and electron mobilities, higher absorption coefficients and increased charge‐carrier density within the BHJ, while significantly extending the cells' shelf‐lifetime. The n‐type doping strategy is applied to five additional BHJ systems, for which similarly remarkable performance improvements are obtained. OPVs of particular interest are based on the ternary PM6:Y6:PC71BM:BV(0.004 wt%) blend for which a maximum PCE of 17.1%, is obtained. The effectiveness of the n‐doping strategy highlights electron transport in NFA‐based OPVs as being a key issue.
Addition of the n‐type dopant benzyl viologen (BV) into several best‐in‐class organic bulk‐heterojunctions (BHJ) is shown to consistently improve the power conversion efficiency (PCE) of the resulting solar cells. The presence of BV inside the BHJs increases the absorption coefficient, balances charge transport, and enhances the charge‐carrier density. These synergistic effects result in organic photovoltaics with a maximum PCE of 17.1%.
A simple approach that enables a consistent enhancement of the electron extracting properties of the widely used small‐molecule Phen‐NaDPO and its application in organic solar cells (OSCs) is ...reported. It is shown that addition of minute amounts of the inorganic molecule Sn(SCN)2 into Phen‐NaDPO improves both the electron transport and its film‐forming properties. Use of Phen‐NaDPO:Sn(SCN)2 blend as the electron transport layer (ETL) in binary PM6:IT‐4F OSCs leads to a remarkable increase in the cells' power conversion efficiency (PCE) from 12.6% (Phen‐NaDPO) to 13.5% (Phen‐NaDPO:Sn(SCN)2). Combining the hybrid ETL with the best‐in‐class organic ternary PM6:Y6:PC70BM systems results to a similarly remarkable PCE increase from 14.2% (Phen‐NaDPO) to 15.6% (Phen‐NaDPO:Sn(SCN)2). The consistent PCE enhancement is attributed to reduced trap‐assisted carrier recombination at the bulk‐heterojunction/ETL interface due to the presence of new energy states formed upon chemical interaction of Phen‐NaDPO with Sn(SCN)2. The versatility of this hybrid ETL is further demonstrated with its application in perovskite solar cells for which an increase in the PCE from 16.6% to 18.2% is also demonstrated.
The electron extracting properties of the widely used electron transporting layer (ETL) material Phen‐NaDPO are remarkably enhanced via simple addition of the wide‐bandgap inorganic material tin (II) thiocyanate (Sn(SCN)2). Use of this hybrid ETL system in organic and perovskite solar cells results in consistent efficiency improvements due to the reduced trap‐assisted recombination and efficient electron extraction.
Efficiencies of organic photovoltaic (OPV) devices have been steadily climbing, but there is still a prominent gap in understanding the relationship between fabrication and performance. Side chain ...substitution is one processing parameter that can change OPV device efficiency considerably, primarily because of variations in morphology. In this work, we explain the morphological link between side chain selection and device performance in one polymer to aid in the development of design rules more broadly. We study the morphology of an OPV active layer using a PBDTTPD-backbone polymer with four different side chain configurations, which are shown to change device efficiency by up to 4 times. The optimal device has the smallest domain sizes, the highest degree of crystallinity, and the most face-on character. This is achieved with two branched 2-ethylhexyl (2EH) side chains placed symmetrically on the BDT unit and a linear octyl (C8) side chain on the TPD unit. Substituting either side chain (C14 on BDT and/or 2EH on TPD) makes the orientation less face-on, while the TPD side chain primarily affects domain size. For all side chains, the addition of fullerene increases polymer crystallization compared to the neat film, but the degree of mixing between polymer and fullerene varies with side chain. Interestingly, the optimal device has a negligible amount of mixed phase. The domain sizes present in the optimal system are remarkably unchanged with a changing fullerene ratio between 10 and 90%, hinting that the polymer preferentially self-assembles into 10–20 nm crystallites regardless of concentration. The formation of this crystallite may be the key factor inhibiting mixed phase.
Perovskite solar cells are one of the most promising photovoltaic technologies due to their rapid increase in power conversion efficiency (3.8% to 21.1%) in a very short period of time and the ...relative ease of their fabrication compared to traditional inorganic solar cells. One of the drawbacks of perovskite solar cells is their limited stability in non-inert atmospheres. In the inverted device configuration this lack of stability can be attributed to the inclusion of poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) as the hole transporting layer. Herein we report the synthesis of two new triarylamine based hole transporting materials, synthesised from readily available starting materials. These new materials show increased power conversion efficiencies, of 13.0% and 12.1%, compared to PEDOT:PSS (10.9%) and exhibit increased stability achieving lifetimes in excess of 500 hours. Both molecules are solution processible at low temperatures and show potential for low cost, scalable production of large scale perovskite solar cells on flexible substrates.
Four solution-processable, linear conjugated polymers of intrinsic porosity are synthesised and tested for gas phase carbon dioxide photoreduction. The polymers' photoreduction efficiency is ...investigated as a function of their porosity, optical properties, energy levels and photoluminescence. All polymers successfully form carbon monoxide as the main product, without the addition of metal co-catalysts. The best performing single component polymer yields a rate of 66 μmol h
m
, which we attribute to the polymer exhibiting macroporosity and the longest exciton lifetimes. The addition of copper iodide, as a source of a copper co-catalyst in the polymers shows an increase in rate, with the best performing polymer achieving a rate of 175 μmol h
m
. The polymers are active for over 100 h under operating conditions. This work shows the potential of processable polymers of intrinsic porosity for use in the gas phase photoreduction of carbon dioxide towards solar fuels.
Cotton (
) is an economically important crop and is widely cultivated around the globe. However, the major problem of cotton is its high vulnerability to biotic and abiotic stresses. It has been ...around three decades since the cotton plant was genetically engineered with genes encoding insecticidal proteins (mainly Cry proteins) with an aim to protect it against insect attack. Several studies have been reported on the impact of these genes on cotton production and fiber quality. However, the metabolites responsible for conferring resistance in genetically modified cotton need to be explored. The current work aims to unveil the key metabolites responsible for insect resistance in Bt cotton and also compare the conventional multivariate analysis methods with deep learning approaches to perform clustering analysis. We aim to unveil the marker compounds which are responsible for inducing insect resistance in cotton plants. For this purpose, we employed 1H-NMR spectroscopy to perform metabolite profiling of Bt and non-Bt cotton varieties, and a total of 42 different metabolites were identified in cotton plants. In cluster analysis, deep learning approaches (linear discriminant analysis (LDA) and neural networks) showed better separation among cotton varieties compared to conventional methods (principal component analysis (PCA) and orthogonal partial least square discriminant analysis (OPLSDA)). The key metabolites responsible for inter-class separation were terpinolene, α-ketoglutaric acid, aspartic acid, stigmasterol, fructose, maltose, arabinose, xylulose, cinnamic acid, malic acid, valine, nonanoic acid, citrulline, and shikimic acid. The metabolites which regulated differently with the level of significance
< 0.001 amongst different cotton varieties belonged to the tricarboxylic acid cycle (TCA), Shikimic acid, and phenylpropanoid pathways. Our analyses underscore a biosignature of metabolites that might involve in inducing insect resistance in Bt cotton. Moreover, novel evidence from our study could be used in the metabolic engineering of these biological pathways to improve the resilience of Bt cotton against insect/pest attacks. Lastly, our findings are also in complete support of employing deep machine learning algorithms as a useful tool in metabolomics studies.
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