Noncovalent semiconducting polymer monolayers for high-performance field-effect transistors

Polymer-Unit Graph: Advancing Interpretability in Graph Neural Network Machine Learning for Organic Polymer Semiconductor Materials

The graph representation of complex materials plays a crucial role in the field of inorganic and organic materials investigations for developing data-centric materials science, such as those using graph neural networks (GNNs). However, the currently prevalent GNN models are primarily employed for investigating periodic crystals and organic small molecule data, yet they still encounter challenges in terms of interpretability and computational efficiency when applied to polymer monomers and organic macromolecules data. There is still a lack of graph representation of organic polymers and macromolecules specifically tailored for GNN models to explore the structural characteristics. The Polymer-unit Graph, a novel coarse-grained graph representation method introduced in study, is dedicated to expressing and analyzing polymers and macromolecules. By incorporating the Polymer-unit Graph into the GNN models and analyzing the organic semiconductor (OSC) materials database, it becomes possible to uncover intricate structure-property relationships involving branched-chain engineering, fluoridation substitution, and donor-acceptor combination effects on the elementary structure of OSC polymers. Furthermore, the Polymer-unit Graph enables visualizing the relationship between target properties and polymer units while reducing training time by an impressive 98% and minimizing molecular graph representation models. In conclusion, the Polymer-unit Graph successfully integrates the concept of Polymer-unit into the field of GNNs, enabling more accurate analysis and understanding of organic polymers and macromolecules.

Achieving Ideal and Environmentally Stable n-Type Charge Transport in Polymer Field-Effect Transistors

Realizing ideal charge transport in field-effect transistors (FETs) of conjugated polymers is crucial for evaluating device performance, such as carrier mobility and practical applications of conjugated polymers. However, the current FETs using conjugated polymers as the active layers generally show certain non-ideal transport characteristics and poor stability. Here, ideal charge transport of n-type polymer FETs is achieved on flexible polyimide substrates by using an organic-inorganic hybrid double-layer dielectric. Deposited conjugated polymer films show highly ordered structures and low disorder, which are supported by grazing-incidence wide-angle X-ray scattering, near-edge X-ray absorption fine structure, and molecular dynamics simulations. Furthermore, the organic-inorganic hybrid double-layer dielectric provides low interfacial defects, leading to excellent charge transport in FETs with high electron mobility (1.49 ± 0.46 cm2 V-1 s-1) and ideal reliability factors (102 ± 7%). Fabricated polymer FETs show a self-encapsulation effect, resulting in high stability of the FET charge transport. The polymer FETs still work with high mobility above 1 cm2 V-1 s-1 after storage in air for more than 300 days. Compared with state-of-the-art conjugated polymer FETs, this work simultaneously achieves ideal charge transport and environmental stability in n-type polymer FETs, facilitating rapid device optimization of high-performance polymer electronics.

Efficient N-Type Organic Electrochemical Transistors and Field-Effect Transistors Based on PNDI-Copolymers Bearing Fluorinated Selenophene-Vinylene-Selenophenes

n-Type organic electrochemical transistors (OECTs) and organic field-effect transistors (OFETs) are less developed than their p-type counterparts. Herein, polynaphthalenediimide (PNDI)-based copolymers bearing novel fluorinated selenophene-vinylene-selenophene (FSVS) units as efficient materials for both n-type OECTs and n-type OFETs are reported. The PNDI polymers with oligo(ethylene glycol) (EG7) side chains P(NDIEG7-FSVS), affords a high µC* of > 0.2 F cm-1  V-1  s-1 , outperforming the benchmark n-type Pg4NDI-T2 and Pg4NDI-gT2 by two orders of magnitude. The deep-lying LUMO of -4.63 eV endows P(NDIEG7-FSVS) with an ultra-low threshold voltage of 0.16 V. Moreover, the conjugated polymer with octyldodecyl (OD) side chains P(NDIOD-FSVS) exhibits a surprisingly low energetic disorder with an Urbach energy of 36 meV and an ultra-low activation energy of 39 meV, resulting in high electron mobility of up to 0.32 cm2  V-1  s-1 in n-type OFETs. These results demonstrate the great potential for simultaneously achieving a lower LUMO and a tighter intermolecular packing for the next-generation efficient n-type organic electronics.

Polymer-Unit Fingerprint (PUFp): An Accessible Expression of Polymer Organic Semiconductors for Machine Learning

High-performance organic semiconductors (OSCs) can be designed based on the identification of functional units and their role in the material properties. Herein, we present a polymer-unit fingerprint (PUFp) generation framework, "Python-based polymer-unit-recognition script" (PURS), to identify the subunits "polymer unit" in the polymer and generate polymer-unit fingerprint (PUFp). Using 678 collected OSC data, machine learning (ML) models can be used to determine structure-mobility relationships by using PUFp as a structural input, and the classification accuracy reaches 85.2%. A polymer-unit library consisting of 445 units is constructed, and the key polymer units affecting the mobility of OSCs are identified. By investigating the combinations of polymer units with mobility performance, a scheme for designing OSCs by combining ML approaches and PUFp information is proposed. This scheme not only passively predicts OSC mobility but also actively provides structural guidance for high-mobility OSC material design. The proposed scheme demonstrates the ability to screen materials through pre-evaluation and classification ML steps and is an alternative methodology for applying ML in high-mobility OSC discovery.

Tuning the nanostructure and molecular orientation of high molecular weight diketopyrrolopyrrole-based polymers for high-performance field-effect transistors

As a versatile class of semiconductors, diketopyrrolopyrrole (DPP)-based conjugated polymers are well suited for applications of next-generation plastic electronics because of their excellent and tunable optoelectronic properties via a rational design of chemical structures. However, it remains a challenge to unravel and eventually influence the correlation between their solution-state aggregation and solid-state microstructure. In this contribution, the solution-state aggregation of high molecular weight PDPP3T is effectively enhanced by solvent selectivity, and a fibril-like nanostructure with short-range and long-range order is generated and tuned in thin films. The predominant role of solvent quality on polymer packing orientation is revealed, with an orientational transition from a face-on to an edge-on texture for the same PDPP3T. The resultant edge-on arranged films lead to a significant improvement in charge transport in transistors, and the field-effect hole mobility reaches 2.12 cm² V^-1 s^-1 with a drain current on/off ratio of up to 10⁸. Our findings offer a new strategy for enhancing the device performance of polymer electronic devices.

Role of Interfacial Interactions in the Graphene-Directed Assembly of Monolayer Conjugated Polymers

Development of graphene-organic hybrid electronics is one of the most promising directions for next-generation electronic materials. However, it remains challenging to understand the graphene-organic semiconductor interactions right at the interface, which is key to designing hybrid electronics. Herein, we study the influence of graphene on the multiscale morphology of solution-processed monolayers of conjugated polymers (PII-2T, DPP-BTz, DPP2T-TT, and DPP-T-TMS). The strong interaction between graphene and PII-2T was manifested in the high fiber density and high film coverage of monolayer films deposited on graphene compared to plasma SiO2 substrates. The monolayer films on graphene also exhibited a higher relative degree of crystallinity and dichroic ratio or polymer alignment, i.e., higher degree of order. Raman spectroscopy revealed the increased backbone planarity of the conjugated polymers upon deposition on graphene as well as the existence of electronic interaction across the interface. This speculation was further substantiated by the results of photoelectron spectroscopy (XPS and UPS) of PII-2T, which showed a decrease in binding energy of several atomic energy levels, movement of the Fermi level toward HOMO, and an increase in work function, all of which indicate p-doping of the polymer. Our results provide a new level of understanding on graphene-polymer interactions at nanoscopic interfaces and the consequent impact on multiscale morphology, which will aid in the design of efficient graphene-organic hybrid electronics.