Ce chapitre présente les cellules solaires à colorant (DSSC), une technologie photovoltaïque émergente inspirée de la photosynthèse. Il détaille leur principe de fonctionnement, les progrès dans les matériaux (colorants, électrolytes, oxydes semiconducteurs), leurs applications (intégration architecturale, électronique nomade) et les perspectives d’amélioration, notamment pour l’Internet des Objets (IoT).

Thieno[3,2-b]thiophene-based diketopyrrolopyrrole (DPP) derivatives are highly promising building blocks for low-bandgap organic semiconductors, yet their dialdehyde counterparts remain underexplored due to limited synthetic accessibility. Herein, we report an optimized and scalable synthesis of the thieno[3,2-b]thiophene DPP dialdehyde, featuring an efficient one-pot introduction of a nitrile functionality and enabling multigram-scale production. This key intermediate was subsequently employed to prepare a series of π-conjugated small molecules of A–D–A–D–A structure via a straightforward Knoevenagel condensation with various acceptor units, thus avoiding the use of organometallic cross-coupling reactions. The resulting materials exhibit broad optical absorption and low bandgaps, with electrochemical and optical bandgaps in the ranges of 1.05–1.50eV and 1.43–1.62eV, respectively. The tetranitrofluorene DPP derivative synthesized displays the lowest electronic bandgap (1.05eV), highlighting the effectiveness of conjugation extension of this π-conjugated system. Experimental results are in good agreement with time-dependent density functional theory calculations, with the HSE06 functional providing the most accurate description of frontier orbital energies. When evaluated in organic field-effect transistors, the materials show n-type behavior, with the tetracyano DPP derivative exhibiting the highest electron mobility, reaching (2.8 ± 0.4) × 10⁻³ cm²·V⁻¹·s⁻¹ after thermal annealing. Overall, this work demonstrates that thieno[3,2-b]thiophene DPP dialdehyde is a versatile and synthetically accessible platform for the development of low-bandgap organic semiconductors via a metal-free strategy, opening new possibilities for scalable and high-performance electronic materials.

Exciton dynamics play a crucial role in determining the efficiency of organic photovoltaic devices and photo-detectors. However, establishing clear correlations between molecular structure and exciton diffusion length remains a significant challenge, limiting the rational design of more efficient materials. In this study, we investigate exciton transport in thin films of a planar dumbbell-shaped electron donor composed of discotic triazatruxene end-groups and an electron-deficient central unit. These molecules self-assemble into unique bridged-columnar structures, which are known to support efficient charge transport, although their impact on exciton dynamics had not yet been explored. Using a combination of time-resolved photoluminescence (TRPL), spatially resolved TRPL, and exciton-exciton annihilation measurements, we examine how structural order influences exciton diffusion in both the columnar-nematic and crystalline phases. We show that crystallization leads to a twofold increase in exciton diffusion length, reaching values comparable to those observed in state-of-the-art non-fullerene acceptors. Although the molecules exhibit a typical Stokes shift that is not particularly favorable for F & ouml;rster energy transfer (FRET), efficient exciton transport is nonetheless achieved-enabled by long exciton lifetimes and anisotropic energy transfer within its distinctive bridged-columnar architecture. These results, supported by FRET analysis, highlight the effectiveness of the molecule's tailored dumbbell-shaped design and its ability to self-assemble into ordered structures that support both long-range exciton diffusion and efficient charge mobility.

A series of novel conjugated semiconducting polymers based on the unsubstituted thiazolo[5,4‐ d ]thiazole (TzTz) unit is synthesized using atom‐economic and environmentally friendly direct (hetero)arylation polymerization (DHAP). The versatility of the proposed polymerization conditions, employing a non‐chlorinated and moderately toxic solvent and cooperative palladium/copper bimetallic catalytic system, is demonstrated through the use of seven comonomers with varying electron‐withdrawing strength: 2,2′‐bithiophene (BT), 6,7‐difluoroquinoxaline (Qx), thieno[3,4‐ c ]pyrrole‐4,6(5H)‐dione (TPD), 5,6‐difluorobenzo[ c ][1,2,5]thiadiazole (BTD), isoindigo (IID), para‐azaquinodimethane (AQM) and 2,5‐dihydropyrrolo[3,4‐c]pyrrole‐1,4‐dione (DPP). The resulting TzTz‐based copolymers exhibit optical bandgaps between 1.5 and 2.0 eV with HOMO/LUMO energy levels spanning from −5.2/−3.3 eV to −5.4/−3.9 eV. They all show satisfactory thermal stability for electronic applications (Td = 300−360 °C). Notably, TzTz‐based copolymers are observed they generally exhibit improved backbone planarity and deeper LUMO levels than their thiophene derivatives. A synthesis tool to finely lower the LUMO levels of next‐generation A‐A’ copolymers in view of increasing the performance and air‐stability of doped organic electronics is believed to be provided by this work.

In this study, we investigate how the addition of polyvinylpyrrolidone (PVP), a thermoplastic polymer, contributes to enhance the processability, thermomechanical and semiconducting properties of a semiconducting polymer without side chains. Here, polypyrrole (PPy) is chosen as reference semiconducting polymer. Different blend ratio of polyvinylpyrrolidone/polypyrrole (PPy/PVP) is prepared by in situ polymerization in acidic solution. The pre-requisite for an effective gain in mechanical properties is to ensure an intimate mixing of both polymers. The miscibility of PPy with PVP is assessed preliminarily using thermodynamic approaches derived from the appropriate group contribution theory which is confirmed experimentally by thermal measurements using differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA), respectively. All PPy/PVP blend ratios exhibit a single glass transition temperature (Tg) characteristic of their appropriate miscibility in the solid state. The morphology and thermal behavior of PPy/PVP mixtures are investigated by DSC and TGA. The potential specific interactions between PPy and PVP moieties are investigated both qualitatively and quantitatively using Fourier transform infrared spectroscopy (FTIR). The FTIR study reveals specific interactions mainly hydrogen bonding between antagonist groups of PPy and PVP. The TGA showed an improved thermal stability. The optical gap of PPy in the mixture PPy/PVP (0.8–0.5 eV) determined by UV–Visible spectrophotometry is attributed to π → π* transition, while the electric conductivity measured by the four-point method revealed their semiconducting behavior (57–3960 µS cm−1). Electrochemical impedance spectroscopy (EIS) exhibits semicircles attributed to bulk material, whose diameter decreases with increasing temperature, thus confirming the semiconducting behavior of PPy; the data obey to an Arrhenius law with an activation energy of 0.1 eV and the conduction occurs by electrons delocalization through alternating double bonds.

ABSTRACT Organic Photovoltaic (OPV) Devices Have Emerged as a Promising Alternative to Conventional Solar Cells due to Their Flexibility, Lightweight Nature, and Potential for Low‐cost Production. However, Optimizing OPV Performance Remains a Complex Challenge, Traditionally Requiring Extensive Experimental Trials or Computational Chemistry Approaches Based on Molecular Descriptors. To Accelerate the Development of High‐efficiency OPVs, Artificial Intelligence (AI) Has Been Increasingly Utilized, Particularly Machine Learning Models That Rely on Chemical Descriptors. While these Methods Have Shown Success, They Are Often Limited by the Quality and Completeness of the Selected Descriptors, Potentially Overlooking Key Structural and Morphological Information. In this Work, We Propose a Novel Deep Learning Framework Leveraging Convolutional Neural Networks (CNNs) to Predict OPV Performance Directly from 2D Images of Donor and Acceptor Materials. By Employing a Customized Representation of Molecular Structures, Our Approach Captures Spatial and Hierarchical Patterns That Traditional Descriptors Based ML Models May Miss. We Compare Our Model's Predictive Capability to Conventional Machine Learning Techniques and Demonstrate Its Potential for Improving Prediction Accuracy and Generalization without Need to Add the Frontier Molecular Orbitals (FMOs) to Enhance Predictions. Our Findings Highlight the Power of Deep Learning in Accelerating the Discovery of Efficient Organic Photovoltaic Materials, Paving the Way for a Data‐driven Approach to Materials Science and Device Optimization.

Organic solar cells (OSCs) can achieve power conversion efficiencies around 20%. Yet, further improvements in efficiency and long-term stability are necessary to rival the dominant silicon technology. Key factors influencing OSC performance include device architecture and the active-layer semiconducting organic materials. In this study, we utilize artificial intelligence (AI) techniques to analyze an experimental dataset of organic semiconductors used in the active layer of OSCs. We propose an AI-based methodology to predict the performance of OSCs using the chemical structure of Donor-Acceptor (D/A) pairs. The method employs Simplified Molecular Input Line Entry System (SMILES) representations to extract molecular features. These features, selected according to maximum relevance and minimum redundancy criteria, are used by supervised machine learning regression algorithms to predict the main photovoltaic parameters. Our AI model demonstrates significant predictive power. Further, we use our model to predict the photovoltaic parameters of (D/A) pairs that were not included in our initial dataset. These findings highlight the potential of AI-driven analysis to accurately estimate the photovoltaic potential of new (D/A) pairs before synthesizing them and therefore to accelerate the development of commercially viable OPV devices and to lower the materials research cost.

Aqueous dispersions of organic semiconducting nanoparticles (NPs) are particularly attractive as inks for the environmentally friendly preparation of organic solar cells. The internal morphology of the NPs, which depends on their elaboration process, is a key parameter, which has a significant influence on the final morphology of the active layer and therefore its effectiveness. In the present study, core-shell (PF2:PC71BM) NPs were prepared by miniemulsion. Their internal morphology including the composition of the two phases was characterized by scanning transmission X-ray microscopy (STXM) showing a core composed of 77% PC71BM and a shell composed of 75% PF2. It was found that thermal annealing promotes PC71BM diffusion from the core to the shell, increasing its proportion in the shell from 25% to 42%. This annealing, when applied after NPs deposition by spincoating, allows partial coalescence of the NPs, reducing the roughness of the active layer, and increases electron mobility, thus demonstrating the formation of PC71BM percolation paths for electron transport. A PCE of 1.6% could thus be obtained after 10min of thermal annealing at 100°C. At higher temperature, Grazing-Incidence Wide-Angle X-Ray Scattering (GIWAXS) analyses demonstrate the modification of the PF2 structuration from randomly oriented lamella after deposition to edge-on orientation after annealing, leading to an unfavorable decrease of the hole mobility in the direction perpendicular to the substrate, while increasing the hole mobility in the substrate plane. This study demonstrates the need to systematically characterize the internal morphology of NPs in order to rationalize the morphology of the active layer and optimize its properties.

The search for efficient organic photovoltaics materials is crucial for advancing solar energy technologies due to their potential for low-cost, lightweight, and flexible solar cells compared to traditional inorganic photovoltaics. In this study, we employed a machine learning (ML) approach to predict the key photovoltaic parameters, namely the open-circuit voltage (Voc), the short-circuit current density (Jsc) and the power conversion efficiency (PCE) of organic semiconductors used in the active-layer of organic solar cells. We trained our ML model on a comprehensive dataset of known donor-acceptor (D/A) pairs and their respective photovoltaic properties. Using this trained model, we generated and evaluated numerous novel (D/A) combinations and predicted their Voc, Jsc and PCE values. This high-throughput screening enabled us to identify promising (D/A) pairs that have not yet been explored in the literature. As a result, our findings demonstrate the power of machine learning in accelerating the discovery and optimization of new materials combinations for organic photovoltaics, potentially leading to more efficient and cost-effective solar cells, thus advancing the viability of sustainable energy solutions.

A new NFA design based on the unusual BODIPY unit as the central electron accepting component is described. All derivatives exhibit low optical bandgaps, high extinction coefficients and LUMO levels deep enough to be used as NFAs.

Incorporation of a benzothiadiazole moiety into a thiophene and naphthalene diimide-based copolymer improves electron mobility, conductivity and stability in the doped state.

Dynamic windows allow monitoring of in-door solar radiation and thus improve user comfort and energy efficiency in buildings and vehicles. Existing technologies are, however, hampered by limitations in switching speed, energy efficiency, user control, or production costs. Here, we introduce a new concept for self-powered switchable glazing that combines a nematic liquid crystal, as an electro-optic active layer, with an organic photovoltaic material . The latter aligns the liquid crystal molecules and generates, under illumination, an electric field that changes the molecular orientation and thereby the device transmittance in the visible and near-infrared region. Small-area devices can be switched from clear to dark in hundreds of milliseconds without an external power supply. The drop in transmittance can be adjusted using a variable resistor and is shown to be reversible and stable for more than 5 h. First solution-processed large-area (15 cm2) devices are presented, and prospects for smart window applications are discussed.

We describe the synthesis of two new dumbbell-shaped small molecules used as near ultra-violet absorbers for transparent organic solar cell application. The electron-donor TAT units, sandwiching the central chromophore, constitute very efficient π-stacking platforms that are nevertheless highly soluble thanks to the presence of three alkyl chains. The TAT units are used in combination, with a small central electron donor unit, either a carbazole or a thieno[3,2-b]thiophene (TT) unit. The two new dumbbell-shaped small molecules including only electron-donor units are strongly absorbing in the near UV range, due to the reduced electronic conjugation. Combined with a suitable hole mobility, the most conjugated thieno[3,2-b]thiophene-based derivative, when used as electron-donor component in a bulk heterojunction organic solar cell, exhibits a 48% of average visible transmittance with a power conversion efficiency close to 2%.

Hydrogen bonds are noncovalent interactions able to improve the electronic properties of self-assembled semiconductors. Nevertheless, it is necessary to control the parameters influencing the formation of hydrogen bonds to achieve hierarchical structures with enhanced properties. In this work, we explore two hydrogen-bonded thiophene-capped diketopyrrolopyrrole (DPP) derivatives containing amides with different topology (C- or N-centered) and compare them to a control analogue without hydrogen bonds. We demonstrate the differences in the optoelectronic and self-assembly properties of the two amide-containing DPP derivatives, as well as in their charge carrier lifetimes. We prove the superior properties of the hydrogen-bonded derivatives in comparison to the control molecule without hydrogen bonds, and show that our molecular design strategy results in supramolecular structures with particularly long charge carrier lifetimes compared to other amide-containing semiconductors reported in the literature.

Savez-vous que le photovoltaïque organique présente de véritables atouts pour offrir une production durable et renouvelable d’électricité, notamment légèreté, flexibilité et faible coût énergétique de production ? Cependant, certains verrous subsistent avant l'industrialisation massive de panneaux photovoltaïques organiques.

Over the past decade, halogenated semiconducting polymers have attracted considerable interest due to their outstanding optoelectronic properties. Thus, in most of today's organic photovoltaic devices benchmark organic semiconductors are halogenated materials, either electron donor polymers or non‐fullerene acceptor (NFA) small molecules. However, the nature and position of the substituted halogen atoms in halogenated semiconducting polymers impact, through self‐assembly modification, their optoelectronic properties in a way that is difficult to predict. Yet, the solid‐state self‐assembling of these materials has been shown to be a key parameter toward high charge transport properties and photovoltaic efficiencies. In this context, there is still a need to develop analytical methods that will enable an atomic‐scale structural characterization of these materials as a function of the halogenation. In this study, the solid‐state nuclear magnetic resonance (NMR) under magic angle spinning (MAS) is explored as a tool to investigate the local structure and supramolecular organization of a series of conjugated polymers, specially designed for this study. Through a comprehensive study using complementary techniques, including MAS–NMR, small and wide‐angle X‐ray scattering, and molecular modeling investigations, the molecular conformation of these polymers in relation to their chemical composition, is successfully determined.

The use of Non-Fullerene Acceptors (NFAs) in the active layer of organic solar cells (OSCs) has made it possible to exceed 18% conversion efficiency. However, OSCs still present stability issues under operational conditions that need to be surpassed for their industrialization. In this work, we investigated binary and ternary blends to examine their efficiency and their stability as active layers of OSCs. We used a fluorinated polymer (PF2) as an electron donor and two different electron acceptors, a fullerene derivative (PC71BM) and a NFA (EH-IDTBR). We demonstrated that using EH-IDTBR instead of PC71BM leads to a decrease in efficiency attributed to the low out-of-plane electron mobility measured in the blend. However, using EH-IDTBR as single electron-acceptor significantly enhanced the OSCs stability under continuous illumination. Ternary blends were tested to reach simultaneously a high efficiency and a long-term stability. The best efficiency/stability compromise appeared to be when using EH-IDTBR only as electron-acceptor. We identified changes in the main charge-carrier recombination mechanism in photo-degraded devices from bimolecular in low EH-IDTBR content blends to trap-assisted in high EH-IDTBR ones. Finally, the blend morphology at a nanometer scale appeared as stable in high EH-IDTBR content blends while photo-degradation impacted significantly the morphology of the low EH-IDTBR content blend.

Two new dumbbell-shaped molecules based on two solubilizing and structuring triazatruxene (TAT) units linked by a central chromophore were synthesized and studied. The central chromophore was an electro-deficient fluorene-malononitrile (FM) unit, that can be functionalized symmetrically on two different positions, giving rise to two positional isomers, called TAT-pFM and TAT-mFM, when the TATs are connected to the 2,7- and 3,6-positions, respectively. The two isomers exhibited different electronic conjugation pathways that drastically affect their absorption properties and energy levels. Moreover, while TAT-pFM was organized in a stable 3D mesomorphic structure from room-temperature to the melting point, TAT-mFM remained crystalline and decomposed before melting. Finally, despite a lower hole mobility, the TAT-mFM exhibited the highest Power Conversion Efficiency (PCE) of about 2 % in organic solar cells. This higher PCE was attributed essentially to the pronounced internal charge transfer band contribution to the charge photogeneration observed in TAT-mFM solar cells.

Nowadays, climate change is a reality because energy demand is mostly satisfied by fossil fuels which are limited resources and also responsible for greenhouse gas emissions. Actions have to be undertaken to overcome this issue. Among the solutions proposed to this is the development and use of new energy sources called renewable energies. By renewable energy, we understand energies coming from the sun, wind, geothermal, water, or biomass. Of these, solar energy is one of the most abundant, clean, effective, and easily deployed. One of the efficient ways to exploit solar energy is photovoltaics. Two decades of research have allowed organic photovoltaics to appear today as an alternative to their conventional and inorganic counterparts. However, several issues have to be addressed in order to ease their production on an industrial level. Bulk heterojunction (BHJ) solar cells based on the blend of two types of conjugated molecules acting as an electron donor (hole transport) and an electron acceptor (electron transport) are the most efficient organic solar cells. Further, using non-fullerene acceptors (or NFA) in these BHJ solar cells have recently gained a broad interest due to their great potential to realize high conversion efficiencies (more than 18%) with a long lifetime over the conventional polymer/fullerene blend solar cells. Here we provide an overview of the recent progress of different existing and growing photovoltaic technologies. We also provide prospects for the future development of organic photovoltaic devices.