High-performance vertical field-effect organic photovoltaics

A Domino Protocol toward High-performance Unsymmetrical Dibenzo[d,d']thieno[2,3-b;4,5-b']dithiophenes Semiconductors

Unsymmetric organic semiconductors have many advantages such as good solubility, rich intermolecular interactions for potential various optoelectronic applications. However, their synthesis is more challenging due to intricate structures thus normally suffering tedious synthesis. Herein, we report a trisulfur radical anion (S3⋅-) triggered domino thienannulation strategy for the synthesis of dibenzo[d,d']thieno[2,3-b;4,5-b']dithiophenes (DBTDTs) using readily available 1-halo-2-ethynylbenzenes as starting materials. This domino protocol features no metal catalyst and the formation of six C-S and one C-C bonds in a one-pot reaction. Mechanistic study revealed a unique domino radical anion pathway. Single crystal structure analysis of unsymmetric DBTDT shows that its unique unsymmetric structure endows rich and multiple weak S⋅⋅⋅S interactions between molecules, which enables the large intermolecular transfer integrals of 86 meV and efficient charge transport performance with a carrier mobility of 1.52 cm2 V-1 s-1. This study provides a facile and highly efficient synthetic strategy for more high-performance unsymmetric organic semiconductors.

In-depth theoretical analysis of the influence of an external electric field on charge transport parameters

It is important to develop materials with environmental stability and long device shelf life for use in organic field-effect transistors (OFETs). The microscopic, molecular-level nature of the organic layer in OFETs is not yet well understood. The stability of geometric and electronic structures and the regulation of the external electric field (EEF) on the charge transport properties of four typical homogeneous organic semiconductors (OSCs) were investigated by density functional theory (DFT). The results showed that under the EEF, the structural changes in single-bond linked oligomers were more sensitive and complex than those of condensed molecules, and there were non-monotonic changes in their reorganization energy (λ) during charge transport under an EEF consisting of decreases and then increases (Series D). The change in λ under an EEF can be preliminarily and qualitatively determined by the change in the frontier molecular orbitals (FMOs) - the number of C-atoms with nonbonding characteristics. For single-bonded molecules, the transfer integral is basically unchanged under a low EEF, but it will greatly change at a high EEF. Because the structure and properties of the molecule will greatly change under different EEFs, the effect of an EEF should be fully considered when determining the intrinsic mobility of OSCs, which could cause a deviation 0.3-20 times in mobility. According to detailed calculations, one heterogeneous oligomer, TH-BTz, was designed. Its λ can be greatly reduced under an EEF, and the change in the energy level of FMOs can be adjusted to different degrees. This study provides a reasonable idea for verification of the experimental mobility value and also provides guidance for the directional design of stable high-mobility OSCs.

Toward grouped-reservoir computing: organic neuromorphic vertical transistor with distributed reservoir states for efficient recognition and prediction

Reservoir computing has attracted considerable attention due to its low training cost. However, existing neuromorphic hardware, focusing mainly on shallow-reservoir computing, faces challenges in providing adequate spatial and temporal scales characteristic for effective computing. Here, we report an ultra-short channel organic neuromorphic vertical transistor with distributed reservoir states. The carrier dynamics used to map signals are enriched by coupled multivariate physics mechanisms, while the vertical architecture employed greatly increases the feedback intensity of the device. Consequently, the device as a reservoir, effectively mapping sequential signals into distributed reservoir state space with 1152 reservoir states, and the range ratio of temporal and spatial characteristics can simultaneously reach 2640 and 650, respectively. The grouped-reservoir computing based on the device can simultaneously adapt to different spatiotemporal task, achieving recognition accuracy over 94% and prediction correlation over 95%. This work proposes a new strategy for developing high-performance reservoir computing networks.