Salvador León

With organic solar cells surpassing 20% efficiency, the focus is shifting toward understanding the more complex mechanisms in ternary blends. This work investigates the distinct working principles of ternary organic solar cells based on a polymer donor (D) and a nonfullerene acceptor (NFA), with a fullerene acceptor (FA) as the third component. A systematic comparison between ternary D:NFA:FA systems, with different components and compositions, and D:NFA:NFA systems was conducted. In all systems, the open‐circuit voltage increased with a higher fullerene ratio, correlating with the fullerene's LUMO position, indicating its involvement in charge transfer (CT) state formation. Various analytical methods and simulations reveal that the investigated D:NFA:FA systems follow an alloy model, where the CT state is delocalized over both acceptors, even in systems with strong surface energy differences between the acceptors. Notably, recombination behavior is largely unaffected by the nature of the third component and is primarily linked to the CT state energy. Based on the internal quantum efficiency characteristics, we propose that the positive effect of fullerenes as third components arises not from reduced nonradiative recombination as often suggested but from more efficient exciton splitting. image

Perovskite solar cells (PSCs) have recently achieved over 26 % power conversion efficiency, challenging the dominance of silicon‐based alternatives. This progress is significantly driven by innovations in hole transport materials (HTMs), which notably influence the efficiency and stability of PSCs. However, conventional organic HTMs like Spiro‐OMeTAD and PTAA, although highly efficient, suffer from thermal degradation, moisture ingress, and high cost. This study explores the potential of iminodibenzyl, a moiety known for its strong electron‐donating capabilities in pharmaceutical applications, as a novel HTM. A series of fluorene‐based derivatives incorporating iminodibenzyl (TMF‐2 and TDF‐2) and diphenylamine (TMF‐1 and TDF‐1) units were synthesized and characterized. The new HTMs demonstrated commendable optical, electrochemical, and thermal properties, as well as enhanced photostability. Among them, TDF‐2 achieved a power conversion efficiency (PCE) of 19.38 %, the highest of the new materials. Although these efficiencies are slightly lower than the benchmark PTAA (20.20 %), the study underscores the potential of iminodibenzyl to enhance photostability and increase HOMO levels, making it a promising candidate for future HTM development in PSCs.

This research explores the electronic properties and conformational dynamics of the ZnP‐COPV‐ (Zinc Porphyrin ‐ Carbon bridged Oligo Phenylenevinylene ‐ Fullerene) organic semiconductor via specialized Density Functional Theory (DFT) and Molecular Dynamics (MD) computational techniques. First, through DFT calculations, essential HOMO (Highest Occupied Molecular Orbital), LUMO (Lowest Unoccupied Molecular Orbital), and Molecular Electrostatic Potential (MEP) electronic attributes are meticulously dissected providing insights into the intricate charge transfer processes between the constituent donor‐acceptor moieties. Furthermore, MD simulations are employed to unveil the molecular system's multifaceted conformational flexibility and stability. The Root‐mean‐squared deviation (RMSD), end‐to‐end distance, and torsional angles quantitative analysis of conformational attributes support the carbon‐bridged oligo‐phenylenevinylene (COPV) molecular wire's ‐skeleton planar and rigid conformation. This minimal end‐to‐end distance variation (within Å) compared to the initially extended structure and the constrained torsional motion (within for ZnP‐COPV and for COPV‐) after thermalization showcases COPV's ability to maintain structural rigidity over time, aligning with the concept of effective ‐conjugation. Finally, through the lens of time dependent (TD)‐DFT, the dynamic evolution of the HOMO–LUMO energy gap, TD‐DFT excitation energies and oscillator strengths are explored as the molecular structure transforms over time. The observed energy gap variation underscores the molecule's adaptability in the face of structural modifications, hinting at an intriguing connection between structural stability and enhanced electronic properties. The research provides a comprehensive understanding of the intricate interplay between conformational dynamics and electronic attributes in organic semiconductors, providing quantitative insights crucial for designing stable, high‐performance materials for cutting‐edge optoelectronic applications and helping advance the collective understanding of sustainable energy conversion.

Dumbbell‐shaped systems based on PAHs‐BODIPY‐triarylamine hybrids TM‐(01‐04) are designed as novel and highly efficient hole‐transporting materials for usage in planar inverted perovskite solar cells. BODIPY is employed as a bridge between the PAH units, and the effects of the conjugated π‐system's covalent attachment and size are investigated. Fluorescence quenching, 3D fluorescence heat maps, and theoretical studies support energy transfer within the moieties. The systems are extremely resistant to UVC 254 nm germicidal light sources and present remarkable thermal stability at degradation temperatures exceeding 350 °C. Integrating these systems into perovskite solar cells results in outstanding power conversion efficiency (PCE), with TM‐02‐based devices exhibiting a PCE of 20.26%. The devices base on TM‐01, TM‐03, and TM‐04 achieve PCE values of 16.98%, 17.58%, and 18.80%, respectively. The long‐term stability of these devices is measured for 600 h, with initial efficiency retention between 94% and 86%. The TM‐04‐based device presents noticeable stability of 94%, better than the reference polymer PTAA with 91%. These findings highlight the exciting potential of dumbbell‐shaped systems based on PAHs‐BODIPY‐triarylamine derivatives for next‐generation photovoltaics.

In this work, we show how to obtain internal monodispersed gold nanoparticles inside polydopamine (PDA) nanospheres that are also externally decorated with gold. The number of internal nanoparticles is affected by the size of the PDA nanosphere used, and the lower limit in the number of gold nanoparticles in the center of decorated nanospheres, one single gold nanoparticle, has been reached. In addition, extensive molecular dynamics simulations of PDA nanospheres based on four different chemical motifs, in the presence of water and with different sizes, have been performed to gain insight into the arrangements capable of accommodating cavities. In particular, PDA nanospheres based on pyranoacridinotrione (PYR) units provide good agreement with the experimental attainment of internal metal nanoparticles. In these, the stacking of PYR units leads to a particular morphology, with large portions of space occupied by the solvent, that would explain the observed formation of gold nanoparticles inside the PDA nanosphere.

The use of renewable monomers to make new polyesters which could replace the ones obtained from petrochemical resources employing green processes is attracting a lot of attention these days. With this in mind, three different macrolactones, ω-pentadecalactone, globalide and 6-hexadecenlactone, have been polymerized in bulk by enzymatic ring opening polymerization (e-ROP) using immobilized Candida antarctica lipase B to give their corresponding polymacrolactones (PMLs). For the first time, these PMLs have been depolymerized enzymatically in solution with the concourse of the same enzyme and at mild temperatures. GPC, NMR and ESI MS demonstrated that the main products recovered after the enzymatic processive recycling were cyclic monomers and dimers, with a small amount of higher size macrocyclic oligoesters (MCOs). It was observed that these depolymerizations followed a Michaelis–Menten kinetic model. Finally it was shown that these MCOs could be repolymerized. This research provides a biosynthetic method for chemical recycling of these interesting polymeric materials providing a pathway towards a circular economy.

The synthesis, photophysical properties and E/Z photoisomerization kinetics in solution and in the solid state of a series of three new 3-(-aryl)-1,1,1-trifluoro-3-(2-phenylhydrazono)propan-2-ones (1a–c, Scheme 1) are reported here. Both E and Z isomers were fully characterized by ¹H-, ¹³C- and ¹⁹F-NMR spectroscopy, and single crystal X-ray diffraction analysis was performed for all thermodynamically stable E isomers. The introduction of the trifluoromethyl ketone group as well as the different methyl and trifluoromethyl susbtituents on the hydrazone and the aromatic rings causes significant changes in the photoisomerization dynamics. The N–H⋯F–C(sp³) interaction is believed to have a prominent role in the stabilization of the metastable Z isomer of 1c which has a very slow back thermal isomerization rate compared to 1a and 1b. DFT calculations support the experimental findings and provide the foundation for future design of new photoswitching materials with promising applications in several technological fields.

Organic semiconductors are indispensable for today’s display technologies in the form of organic light-emitting diodes (OLEDs) and further optoelectronic applications. However, organic materials do not reach the same charge carrier mobility as inorganic semiconductors, limiting the efficiency of devices. To find or even design new organic semiconductors with higher charge carrier mobility, computational approaches, in particular multiscale models, are becoming increasingly important. However, such models are computationally very costly, especially when large systems and long timescales are required, which is the case to compute static and dynamic energy disorder, i.e., the dominant factor to determine charge transport. Here, we overcome this drawback by integrating machine learning models into multiscale simulations. This allows us to obtain unprecedented insight into relevant microscopic materials properties, in particular static and dynamic disorder contributions for a series of application-relevant molecules. We find that static disorder and thus the distribution of shallow traps are highly asymmetrical for many materials, impacting widely considered Gaussian disorder models. We furthermore analyze characteristic energy level fluctuation times and compare them to typical hopping rates to evaluate the importance of dynamic disorder for charge transport. We hope that our findings will significantly improve the accuracy of computational methods used to predict application-relevant materials properties of organic semiconductors and thus make these methods applicable for virtual materials design.

Organic semiconductors are indispensable for today's display technologies in form of organic light emitting diodes (OLEDs) and further optoelectronic applications. However, organic materials do not reach the same charge carrier mobility as inorganic semiconductors, limiting the efficiency of devices. To find or even design new organic semiconductors with higher charge carrier mobility, computational approaches, in particular multiscale models, are becoming increasingly important. However, such models are computationally very costly, especially when large systems and long time scales are required, which is the case to compute static and dynamic energy disorder, i.e. dominant factor to determine charge transport. Here we overcome this drawback by integrating machine learning models into multiscale simulations. This allows us to obtain unprecedented insight into relevant microscopic materials properties, in particular static and dynamic disorder contributions for a series of application-relevant molecules. We find that static disorder and thus the distribution of shallow traps is highly asymmetrical for many materials, impacting widely considered Gaussian disorder models. We furthermore analyse characteristic energy level fluctuation times and compare them to typical hopping rates to evaluate the importance of dynamic disorder for charge transport. We hope that our findings will significantly improve the accuracy of computational methods used to predict application relevant materials properties of organic semiconductors, and thus make these methods applicable for virtual materials design.