Systematic Study on the Morphological Development of Blade-Coated Conjugated Polymer Thin Films via In Situ Measurements

Conjugated Polymer Process Ontology and Experimental Data Repository for Organic Field-Effect Transistors

Polymer-based semiconductors and organic electronics encapsulate a significant research thrust for informatics-driven materials development. However, device measurements are described by a complex array of design and parameter choices, many of which are sparsely reported. For example, the mobility of a polymer-based organic field-effect transistor (OFET) may vary by several orders of magnitude for a given polymer as a plethora of parameters related to solution processing, interface design/surface treatment, thin-film deposition, postprocessing, and measurement settings have a profound effect on the value of the final measurement. Incomplete contextual, experimental details hamper the availability of reusable data applicable for data-driven optimization, modeling (e.g., machine learning), and analysis of new organic devices. To curate organic device databases that contain reproducible and findable, accessible, interoperable, and reusable (FAIR) experimental data records, data ontologies that fully describe sample provenance and process history are required. However, standards for generating such process ontologies are not widely adopted for experimental materials domains. In this work, we design and implement an object-relational database for storing experimental records of OFETs. A data structure is generated by drawing on an international standard for batch process control (ISA-88) to facilitate the design. We then mobilize these representative data records, curated from the literature and laboratory experiments, to enable data-driven learning of process-structure-property relationships. The work presented herein opens the door for the broader adoption of data management practices and design standards for both the organic electronics and the wider materials community.

Meniscus-Guided Deposition of Organic Semiconductor Thin Films: Materials, Mechanism, and Application in Organic Field-Effect Transistors

Solution-processable organic semiconductors are one of the promising materials for the next generation of organic electronic products, which call for high-performance materials and mature processing technologies. Among many solution processing methods, meniscus-guided coating (MGC) techniques have the advantages of large-area, low-cost, adjustable film aggregation, and good compatibility with the roll-to-roll process, showing good research results in the preparation of high-performance organic field-effect transistors. In this review, the types of MGC techniques are first listed and the relevant mechanisms (wetting mechanism, fluid mechanism, and deposition mechanism) are introduced. The MGC processes are focused and the effect of the key coating parameters on the thin film morphology and performance with examples is illustrated. Then, the performance of transistors based on small molecule semiconductors and polymer semiconductor thin films prepared by various MGC techniques is summarized. In the third section, various recent thin film morphology control strategies combined with the MGCs are introduced. Finally, the advanced progress of large-area transistor arrays and the challenges for roll-to-roll processes are presented using MGCs. Nowadays, the application of MGCs is still in the exploration stage, its mechanism is still unclear, and the precise control of film deposition still needs experience accumulation.

The Solution is the Solution: Data-Driven Elucidation of Solution-to-Device Feature Transfer for π-Conjugated Polymer Semiconductors

The advent of data analytics techniques and materials informatics provides opportunities to accelerate the discovery and development of organic semiconductors for electronic devices. However, the development of engineering solutions is limited by the ability to control thin-film morphology in an immense parameter space. The combination of high-throughput experimentation (HTE) laboratory techniques and data analytics offers tremendous avenues to traverse the expansive domains of tunable variables offered by organic semiconductor thin films. This Perspective outlines the steps required to incorporate a comprehensive informatics methodology into the experimental development of polymer-based organic semiconductor technologies. The translation of solution processing and property metrics to thin-film behavior is crucial to inform efficient HTE for data collection and application of data-centric tools to construct new process-structure-property relationships. We argue that detailed investigation of the solution state prior to deposition in conjunction with thin-film characterization will yield a deeper understanding of the physicochemical mechanisms influencing performance in π-conjugated polymer electronics, with data-driven approaches offering predictive capabilities previously unattainable via traditional experimental means.

Operando Characterization of Organic Mixed Ionic/Electronic Conducting Materials

Operando characterization plays an important role in revealing the structure-property relationships of organic mixed ionic/electronic conductors (OMIECs), enabling the direct observation of dynamic changes during device operation and thus guiding the development of new materials. This review focuses on the application of different operando characterization techniques in the study of OMIECs, highlighting the time-dependent and bias-dependent structure, composition, and morphology information extracted from these techniques. We first illustrate the needs, requirements, and challenges of operando characterization then provide an overview of relevant experimental techniques, including spectroscopy, scattering, microbalance, microprobe, and electron microscopy. We also compare different in silico methods and discuss the interplay of these computational methods with experimental techniques. Finally, we provide an outlook on the future development of operando for OMIEC-based devices and look toward multimodal operando techniques for more comprehensive and accurate description of OMIECs.