Abstract:A new electron-rich spirothienoquinoline
unit,
t
BuSAF-Th, has been developed via
incorporation of a thienyl unit instead of a phenyl unit into the
six-membered ring of the spiroacridine (SAF) and utilized for the
first time as a building block for constructing small-molecule electron
donors in organic solar cells (OSCs) and as active layers in organic
resistive memory devices. The resulting three-dimensional spirothienoquinoline-containing 1–4 exhibit high-lying highest occupied
molecular orbital (HOMO) ener… Show more
“…As a final test, the optimal ϵV H V P +rVGG model has been applied (Figure and Tables S6 and S7) to a series of 30 organic photofunctional materials reported by Yam and co-workers. − These test molecules are not included in the CSD data set. In addition to the high correlation ( r > 0.95, Figure b and c), the ML-predicted excited-state energies for both low-lying singlet and triplet states exhibit notably low MAEs (<0.14 eV, Figure d) in comparison to the PBE0-computed references.…”
We present a novel class of one-electron multi-channel
molecular
orbital images (MolOrbImages) designed for the prediction of excited-state
energetics in conjunction with the state-of-the-art VGG-type machine-learning
architecture. By representing hole and particle states in the excitation
process as channels of MolOrbImages, the revised VGG model achieves
excellent prediction accuracy for both low-lying singlet and triplet
states, with mean absolute errors (MAEs) of <0.08 and <0.1 eV
for QM9 molecules and large photofunctional materials with up to 560
atoms, respectively. Remarkably, the model demonstrates exceptional
performance (MAE < 1 kcal/mol) for the T1 state of QM9
molecules, making it a non-system-specific model that approaches chemical
accuracy. The general rules attained, for instance, the improved performance
with well-defined MO energies and the reduced overfitting concern
via the inclusion of physically insightful hole–particle information,
provide invaluable guidelines for the further design of orbital-based
descriptors targeting molecular excited states.
“…As a final test, the optimal ϵV H V P +rVGG model has been applied (Figure and Tables S6 and S7) to a series of 30 organic photofunctional materials reported by Yam and co-workers. − These test molecules are not included in the CSD data set. In addition to the high correlation ( r > 0.95, Figure b and c), the ML-predicted excited-state energies for both low-lying singlet and triplet states exhibit notably low MAEs (<0.14 eV, Figure d) in comparison to the PBE0-computed references.…”
We present a novel class of one-electron multi-channel
molecular
orbital images (MolOrbImages) designed for the prediction of excited-state
energetics in conjunction with the state-of-the-art VGG-type machine-learning
architecture. By representing hole and particle states in the excitation
process as channels of MolOrbImages, the revised VGG model achieves
excellent prediction accuracy for both low-lying singlet and triplet
states, with mean absolute errors (MAEs) of <0.08 and <0.1 eV
for QM9 molecules and large photofunctional materials with up to 560
atoms, respectively. Remarkably, the model demonstrates exceptional
performance (MAE < 1 kcal/mol) for the T1 state of QM9
molecules, making it a non-system-specific model that approaches chemical
accuracy. The general rules attained, for instance, the improved performance
with well-defined MO energies and the reduced overfitting concern
via the inclusion of physically insightful hole–particle information,
provide invaluable guidelines for the further design of orbital-based
descriptors targeting molecular excited states.
“…The lower band gap of CB films suggested a more vital CT ability in the film state to promote charge carrier migration. To better comprehend the UV–vis spectra, the time-dependent density-functional theory (TD-DFT) calculations were performed using the GGA/BLYP function. − The specific absorption positions and intensities are presented in Figure S12, and the corresponding descriptions of the first 12 singlet–singlet electronic transition features are provided in Table S1. These results demonstrated that the high-energy absorption band corresponds to electronic transitions from LUMO to LUMO + 2 and LUMO + 3, while the ICT effect of CB could be attributed to the LUMO-to-LUMO + 1 transition …”
Section: Results
and Discussionmentioning
confidence: 99%
“…However, the current declined sharply at −3.6 V from 6.1 × 10 –2 to 2.2 × 10 –5 A, when the device underwent a negative sweep from 0 to −5 V, indicating a reverse course from the HCS to LCS state. This transition represented that the stored information can be readily erased, revealing a Flash-type behavior. − Notably, the nanofiber-based device could realize the ON/OFF transformation by switching the positive or negative applied voltage. Given that the film thickness of the active medium layer is also an important factor in controlling the electrical properties of the memristor.…”
Section: Results
and Discussionmentioning
confidence: 99%
“…Besides, the CV measurements of CB in the MeCN/ DMSO mixed solution show stable repeatability even after undergoing multiple cycle scans (Figure S13). According to the following two equations: HOMO = −[(E ox onset − E Fc ) + 4.8] and LUMO = HOMO + E g , 43 the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy levels were calculated to be −5.33 and −3.61 eV, respectively. The standard work functions of Al (Φ Al ) and ITO (Φ ITO ) electrodes were considered as −4.3 and −4.8 eV, respectively.…”
Electrophoretic
deposition (EPD) has been recognized as a promising
large-scale film preparation technology for industrial application.
Inspired by the conventional EPD method and the crystal diffusion
growth strategy, we propose a modified electrophoretic-induced self-assembly
deposition (EPAD) technique to control the morphologies of organic
functional materials. Here, an ionic-type dye with a conjugated skeleton
and strong noncovalent interactions, celestine blue (CB), is chosen
as a module molecule for EPAD investigation. As expected, CB molecules
can assemble into different nanostructures, dominated by applied voltage,
concentration effect, and duration. Compared to a nanopillar layered
packing structure formed by the traditional spin-coating method, the
EPAD approach can produce a nanofiber structure under a fixed condition
of 10 V/10 min. Intriguingly, a memristor device based on a pillar-like
nanostructure exhibits WORM-type behavior, while a device based on
nanofibers presents Flash memory performance. The assemble process
and the memory mechanism are uncovered by molecular dynamics simulations
and density-functional theory (DFT) calculations. This work endows
the typical EPD technique with a fresh application scenario, where
an in-depth study on the growth mechanism of nanofibers and the positive
effect of unique morphologies on memristor performance are offered.
“…(b) The nitrogen atoms in terpyridine group exhibit strong coordination ability with transition metals, which can enhance the thermostability and conductivity of organic semiconductors; [ 18 ] (c) Metal Co(II) as the central atom has good redox activity to offer two or more electrical stable states; [ 19 ] and (d) The distinct molecular structures between organic ligand and OSMCs help to induce the variable memory characteristics and figure out information‐storage mechanism. [ 20 ]…”
Section: Background and Originality Contentmentioning
Comprehensive Summary
In the information‐explosion era, developing novel algorithms and memristive devices has become a promising concept for next‐generation capacity enlargement technology. Organic small molecule‐based devices displaying superior learning‐memory performance have attracted much attention, except for the existence of poor heat‐resilience and mediocre conductivity. In this paper, a strategy of transforming an organic‐type data‐storage material to metal complex is proposed to resolve these intrinsic issues. A pristine NDI‐derivative (NIPy) and its corresponding Co(II) complex (CoNIPy) are synthesized for the purpose of electrical property investigation. CoNIPy complex‐based memristive device exhibits superior ternary WORM memory performance compared with the binary behavior of NIPy, including >104 s of reading, lower threshold voltage (Vth), 1: 102: 105 of OFF/ON1/ON2 current ratio, and long‐term stability in heating environment. The variable learning‐memory behavior can be attributed to the enhanced ligand‐to‐metal charge transfer (LMCT) and improved redox activity after the introduction of central metal atom and coordination bond. These studies on material innovation and optimal performance are of great importance not only for environmentally‐robust memristive devices but also for practical application of a host of organic electronic devices.
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