Carbazole and Diketopyrrolopyrrole-Based D-A π-Conjugated Oligomers Accessed via Direct C–H Arylation for Opto-Electronic Property and Performance Study

Zhang, Xiafeng; Feng, Lingwei; Zhang, Kai; Liu, Shiyong

doi:10.3390/molecules27249031

Cited by 6 publications

(5 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…CP-T, CP-BT, CP-BTT, CP-TT, and CP-DTT were prepared with DArP. DBCS (121 mg, 0.33 mmol) with T (28 mg, 1 equiv), BT (55.3 mg, 1 equiv), BTT (82.7 mg, 1 equiv), TT (46.7 mg, 1 equiv), DTT (65.3 mg, 1 equiv), Pd 2 (dba) 3 (4.6 mg, 1.5 mol %), P(o-MeOPh) 3 (3.5 mg, 3 mol %), anhydrous Cs 2 CO 3 (434.4 mg, 2 equiv), PivOH (10.3 mg, 30 mol%), and toluene (5 mL) was added to Schlenk tubes [50][51][52][53]. Each reaction system was deoxidized by a reiterative vacuum and argon filling.…”

Section: Synthesis Of Cpsmentioning

confidence: 99%

Effect of Controlling Thiophene Rings on D-A Polymer Photocatalysts Accessed via Direct Arylation for Hydrogen Production

Liu

Peng

et al. 2023

Molecules

Self Cite

View full text Add to dashboard Cite

Conjugated polymer photocatalysts for hydrogen production have the advantages of an adjustable structure, strong response in the visible light region, adjustable energy levels, and easy functionalization. Using an atom- and step-economic direct C–H arylation method, dibromocyanostilbene was polymerized with thiophene, dithiophene, terthiophene, and fused thienothiophene and dithienothiophene, respectively, to produce donor–acceptor (D-A)-type linear conjugated polymers containing different thiophene derivatives with different conjugation lengths. Among them, the D-A polymer photocatalyst constructed from dithienothiophene could significantly broaden the spectral response, with a hydrogen evolution rate up to 12.15 mmol h−1 g−1. The results showed that the increase in the number of fused rings on thiophene building blocks was beneficial to the photocatalytic hydrogen production of cyanostyrylphene-based linear polymers. For the unfused dithiophene and terthiophene, the increase in the number of thiophene rings enabled more rotation freedom between the thiophene rings and reduced the intrinsic charge mobility, resulting in lower hydrogen production performance accordingly. This study provides a suitable process for the design of electron donors for D-A polymer photocatalysts.

show abstract

Section: Synthesis Of Cpsmentioning

confidence: 99%

Effect of Controlling Thiophene Rings on D-A Polymer Photocatalysts Accessed via Direct Arylation for Hydrogen Production

Liu

Peng

et al. 2023

Molecules

Self Cite

View full text Add to dashboard Cite

show abstract

“…Up till now, polymers and small molecules are two kinds of typical materials used in OSCs, their oligomeric counterparts, however, have received much less attention. [ 36‐45 ] Actually, monodisperse ( Ɖ = 1.0) π‐conjugated oligomers (π‐CO), as mediate bridges between small molecules and polymers, are expected to simultaneously combine the advantages of the defined structures of molecules, and the high light/thermal stability of polymers, owing to their moderately elongated backbones. [ 40‐41 ] Zhan et al .…”

Section: Background and Originality Contentmentioning

confidence: 99%

“…Besides oligomeric NFAs, several oligomeric donors have also been developed to pair with fullerene derivatives for BHJ devices. [ 38,46‐48 ]…”

Section: Background and Originality Contentmentioning

confidence: 99%

Synthesis of Long‐Chain Oligomeric Donor and Acceptors via Direct Arylation for Organic Solar Cells^†

Wu,

He,

Huang

et al. 2023

Chin. J. Chem.

View full text Add to dashboard Cite

Comprehensive SummaryThe rapid synthesis of structurally complicated electron donors & acceptors still remains a major challenge in organic solar cells (OSC). In this work, we developed a highly efficient strategy to access long‐chain oligomeric donor and acceptors for OSC applications. A series of cyclopentadithiophene (CPDT) and benzothiadiazole (BT)‐based π‐conjugated oligomers, i.e., three oligomeric acceptors (BTDT)n‐IC (n= 1‐3) and one long‐chain oligomeric donor (BTDT)4‐RD, are facilely synthesized by an atom‐ and step‐economical, and labor‐saving direct C−H arylation (DACH) reaction (i.e., C−H/C−Br cross coupling). Note that (BTDT)4‐RD involving five CPDT, four BT and two rhodamine (RD) building blocks is the longest oligomeric donor in the fullerene‐free OSC devices ever reported. The dependence of the structure‐property‐performance correlation of (BTDT)n‐IC (n = 1‐3) and (BTDT)4‐RD on the π‐conjugation lengths are thoroughly investigated by opto‐electrochemical measurements, bulk heterojunction (BHJ) OSC devices and microscopies. The (BTDT)1‐IC:PBDB‐T and (BTDT)4‐RD:Y6 BHJs achieve power conversion efficiencies of 9.14% and 4.51%, respectively. Our findings demonstrate that DACH reaction is a powerful tool to tune the opto‐electronic properties and device performances by regulating the lengths of π‐conjugated oligomers with varied numbers of repeating units.This article is protected by copyright. All rights reserved.

show abstract

“…Training runs for a total of 150 epochs, with the model parameters being checkpointed at the end of every epoch and, at the end of training, the checkpoint with the best validation performance is chosen as the final state. Data augmentation is implemented in two ways: once in logit-space by using manifold mixup (Zhang et al, 2018), and also directly on the input waveforms in the form of random additive 1/f-noise with an RMS power drawn from the distribution U [0.0, 0.2] • rms(signal).…”

Section: Deep Learning-based Model Iii: 2d-cnnmentioning

confidence: 99%

The potential of convolutional neural networks for identifying neural states based on electrophysiological signals: experiments on synthetic and real patient data

Rodríguez

Tan

2023

Front. Hum. Neurosci.

View full text Add to dashboard Cite

Processing incoming neural oscillatory signals in real-time and decoding from them relevant behavioral or pathological states is often required for adaptive Deep Brain Stimulation (aDBS) and other brain-computer interface (BCI) applications. Most current approaches rely on first extracting a set of predefined features, such as the power in canonical frequency bands or various time-domain features, and then training machine learning systems that use those predefined features as inputs and infer what the underlying brain state is at each given time point. However, whether this algorithmic approach is best suited to extract all available information contained within the neural waveforms remains an open question. Here, we aim to explore different algorithmic approaches in terms of their potential to yield improvements in decoding performance based on neural activity such as measured through local field potentials (LFPs) recordings or electroencephalography (EEG). In particular, we aim to explore the potential of end-to-end convolutional neural networks, and compare this approach with other machine learning methods that are based on extracting predefined feature sets. To this end, we implement and train a number of machine learning models, based either on manually constructed features or, in the case of deep learning-based models, on features directly learnt from the data. We benchmark these models on the task of identifying neural states using simulated data, which incorporates waveform features previously linked to physiological and pathological functions. We then assess the performance of these models in decoding movements based on local field potentials recorded from the motor thalamus of patients with essential tremor. Our findings, derived from both simulated and real patient data, suggest that end-to-end deep learning-based methods may surpass feature-based approaches, particularly when the relevant patterns within the waveform data are either unknown, difficult to quantify, or when there may be, from the point of view of the predefined feature extraction pipeline, unidentified features that could contribute to decoding performance. The methodologies proposed in this study might hold potential for application in adaptive deep brain stimulation (aDBS) and other brain-computer interface systems.

show abstract

Carbazole and Diketopyrrolopyrrole-Based D-A π-Conjugated Oligomers Accessed via Direct C–H Arylation for Opto-Electronic Property and Performance Study

Cited by 6 publications

References 44 publications

Effect of Controlling Thiophene Rings on D-A Polymer Photocatalysts Accessed via Direct Arylation for Hydrogen Production

Effect of Controlling Thiophene Rings on D-A Polymer Photocatalysts Accessed via Direct Arylation for Hydrogen Production

Synthesis of Long‐Chain Oligomeric Donor and Acceptors via Direct Arylation for Organic Solar Cells^†

The potential of convolutional neural networks for identifying neural states based on electrophysiological signals: experiments on synthetic and real patient data

Contact Info

Product

Resources

About

Carbazole and Diketopyrrolopyrrole-Based D-A π-Conjugated Oligomers Accessed via Direct C–H Arylation for Opto-Electronic Property and Performance Study

Cited by 6 publications

References 44 publications

Effect of Controlling Thiophene Rings on D-A Polymer Photocatalysts Accessed via Direct Arylation for Hydrogen Production

Effect of Controlling Thiophene Rings on D-A Polymer Photocatalysts Accessed via Direct Arylation for Hydrogen Production

Synthesis of Long‐Chain Oligomeric Donor and Acceptors via Direct Arylation for Organic Solar Cells†

The potential of convolutional neural networks for identifying neural states based on electrophysiological signals: experiments on synthetic and real patient data

Contact Info

Product

Resources

About

Synthesis of Long‐Chain Oligomeric Donor and Acceptors via Direct Arylation for Organic Solar Cells^†