The performance of polymer solar cells (PSCs) is commonly improved using additives or annealing treatment. However, these processes are accompanied by disadvantages, including poor reproducibility and stability. Herein, a molecular design strategy is proposed to obtain additive-and annealing-free PSCs. IDTOT2F containing two alkoxyl side chains at the central unit of the nonfullerene acceptor IDTT2F was developed. This molecular design results in excellent solubility in solutions, ordered molecular packing in films, slightly elevated energy levels, and a higher film absorption coefficient. Compared with its counterpart IDTT2F, its improved solubility provides an active layer with better morphology, its ordered molecular packing enhances the charge mobility in blend films, and its slightly elevated energy level furnishes a higher open-circuit voltage of devices. As a result, IDTOT2F-based devices display a maximum power conversion efficiency of 12.79%, which is one of the highest values reported for a PSC fabricated without any extra treatment.
The performance of Li anodes is extremely affected by the solvation of Li ions, leading to preferential reduction of the solvation sheath and subsequent formation of fragile solid–electrolyte interphase (SEI), Li dendrites, and low coulombic efficiency (CE). Herein, we propose a novel strategy to regulate the solvation sheath, through the introduction of intermolecular hydrogen bonds with both the anions of Li salt and the solvent by small amount additives. The addition of such hydrogen bonds reduced the LUMO energy level of anions in electrolyte, promoted the formation of a robust SEI, reduced the amount of free solvent molecules, and enhanced stability of electrolytes. Based on this strategy, flat and dense lithium deposition was obtained. Even under lean electrolytes, at a current density of 1 mA cm−2 with a fixed capacity of 3 mAh cm−2, the Li–Cu cells showed an impressive CE value of 99.2 %. The Li‐LiFePO4 full cells showed long‐term cycling stability for more than 1000 cycles at 1 C, with a total capacity loss of only 15 mAh g−1.
The structural designability of organic electrode materials makes them attractive for symmetric all‐organic batteries (SAOBs) by virtue of different plateaus. However, quite a few works have reported all‐organic batteries and it is still challenging to develop a high‐performance organic material for SAOBs. Herein, a small molecule, 2,3,7,8‐tetraaminophenazine‐1,4,6,9‐tetraone (TAPT), is reported for SAOBs. The rich C=O and C=N groups ensure the high capacity at both plateaus for C=O/C−O and C=N/C−N redox reactions, which are hence utilized as cathodic and anodic active centers respectively. Moreover, the presence of C=O, C=N and NH2 groups resulted in plentiful strong intermolecular interactions, leading to layered structures, insolubility and high stability. The rich functional groups also facilitated the chelation of N and O with Li cations and hence benefited the storage of Li cations. The electrochemical performances of TAPT‐based SAOBs outperformed all of the previously reported SAOBs.
The development of efficient models for predicting specific properties through machine learning is of great importance for the innovation of chemistry and material science. However, predicting global electronic structure properties like Frontier molecular orbital highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy levels and their HOMO–LUMO gaps from the small-sized molecule data to larger molecules remains a challenge. Here, we develop a multilevel attention neural network, named DeepMoleNet, to enable chemical interpretable insights being fused into multitask learning through (1) weighting contributions from various atoms and (2) taking the atom-centered symmetry functions (ACSFs) as the teacher descriptor. The efficient prediction of 12 properties including dipole moment, HOMO, and Gibbs free energy within chemical accuracy is achieved by using multiple benchmarks, both at the equilibrium and nonequilibrium geometries, including up to 110,000 records of data in QM9, 400,000 records in MD17, and 280,000 records in ANI-1ccx for random split evaluation. The good transferability for predicting larger molecules outside the training set is demonstrated in both equilibrium QM9 and Alchemy data sets at the density functional theory (DFT) level. Additional tests on nonequilibrium molecular conformations from DFT-based MD17 data set and ANI-1ccx data set with coupled cluster accuracy as well as the public test sets of singlet fission molecules, biomolecules, long oligomers, and protein with up to 140 atoms show reasonable predictions for thermodynamics and electronic structure properties. The proposed multilevel attention neural network is applicable to high-throughput screening of numerous chemical species in both equilibrium and nonequilibrium molecular spaces to accelerate rational designs of drug-like molecules, material candidates, and chemical reactions.
Four noncovalently fused-ring electron acceptors p-DOC6-2F, o-DOC6-2F, o-DOC8-2F, and o-DOC2C6-2F have been designed and synthesized. p-DOC6-2F and o-DOC6-2F have the same molecular backbone but different molecular shapes and symmetries. p-DOC6-2F has an S-shaped molecular backbone and C 2h symmetry, whereas o-DOC6-2F possesses a U-shaped molecular backbone and C 2v symmetry. The molecular shape and symmetry can influence the dipole moment, solubility, optical absorption, energy level, molecular packing, and film morphology. Compared with the corresponding p-DOC6-2F, o-DOC6-2F exhibits better solubility, a wider band gap, and a larger dipole moment. When blended with the donor polymer PBDB-T, the C 2v symmetric o-DOC6-2F can form an appropriate active layer morphology, whereas the C 2h symmetric p-DOC6-2F forms oversized domains. Organic solar cells (OSCs) based on p-DOC6-2F, o-DOC6-2F, o-DOC8-2F, and o-DOC2C6-2F obtained power conversion efficiencies of 9. 23, 11.87, 11.23, and 10.80%, respectively. The result reveals that the molecular symmetry can facilely regulate the performance of OSCs.
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