With the aim of enhancing the field-effect mobility by promoting surface-mediated two-dimensional molecular ordering in self-aligned regioregular poly(3-hexylthiophene) (P3HT) we have controlled the intermolecular interaction at the interface between P3HT and the insulator substrate by using self-assembled monolayers (SAMs) functionalized with various groups (–NH2, –OH, and –CH3). We have found that, depending on the properties of the substrate surface, the P3HT nanocrystals adopt two different orientations—parallel and perpendicular to the insulator substrate—which have field-effect mobilities that differ by more than a factor of 4, and that are as high as 0.28 cm2 V–1 s–1. This surprising increase in field-effect mobility arises in particular for the perpendicular orientation of the nanocrystals with respect to the insulator substrate. Further, the perpendicular orientation of P3HT nanocrystals can be explained by the following factors: the unshared electron pairs of the SAM end groups, the π–H interactions between the thienyl-backbone bearing π-systems and the H (hydrogen) atoms of the SAM end groups, and interdigitation between the alkyl chains of P3HT and the alkyl chains of the SAMs.

Enhancement of Field-Effect Mobility by Surface-Mediated Molecular Ordering in Regioregular Polythiophene Thin Film Transistor

Machine learning models are poised to make a transformative impact on chemical sciences by dramatically accelerating computational algorithms and amplifying insights available from computational chemistry methods. However, achieving this requires a confluence and coaction of expertise in computer science and physical sciences. This Review is written for new and experienced researchers working at the intersection of both fields. We first provide concise tutorials of computational chemistry and machine learning methods, showing how insights involving both can be achieved. We follow with a critical review of noteworthy applications that demonstrate how computational chemistry and machine learning can be used together to provide insightful (and useful) predictions in molecular and materials modeling, retrosyntheses, catalysis, and drug design.

Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems.

Machine learning models are poised to make a transformative impact on chemical sciences by dramatically accelerating computational algorithms and amplifying insights available from computational chemistry methods. However, achieving this requires a confluence and coaction of expertise in computer science and physical sciences. This review is written for new and experienced researchers working at the intersection of both fields. We first provide concise tutorials of computational chemistry and machine learning methods, showing how insights involving both can be achieved. We then follow with a critical review of noteworthy applications that demonstrate how computational chemistry and machine learning can be used together to provide insightful (and useful) predictions in molecular and materials modeling, retrosyntheses, catalysis, and drug design.

The development of materials with high efficiency and stable signal output in a bent state is important for flexible electronics. Grain boundaries provide lasting inspiration and a promising avenue for designing advanced functionalities using nanomaterials. Combining bulk defects in polycrystalline materials is shown to result in rich new electronic structures, catalytic activities, and mechanical properties for many applications. However, direct evidence that grain boundaries can create new physicochemical properties in flexible electronics is lacking. Here, a combination of bulk electrosensitive measurements, density functional theory calculations, and atomic force microscopy technology with quantitative nanomechanical mapping is used to show that grain boundaries in polycrystalline wires are more active and mechanically stable than single-crystalline wires for real-time detection of chemical analytes. The existence of a grain boundary improves the electronic and mechanical properties, which activate and stabilize materials, and allow new opportunities to design highly sensitive, flexible chemical sensors.

Grain-Boundary-Induced Drastic Sensing Performance Enhancement of Polycrystalline-Microwire Printed Gas Sensors

ForestGEO: Understanding forest diversity and dynamics through a global observatory network

Blending organic semiconductors with insulating polymers has been known to be an effective way to overcome the disadvantages of single-component organic semiconductors for high-performance organic field-effect transistors (OFETs). We show that when a solution processable organic semiconductor (6,13-bis(triisopropylsilylethynyl)pentacene, TIPS-pentacene) is blended with an insulating polymer (PS), morphological and structural characteristics of the blend films could be significantly influenced by the processing conditions like the spin coating time. Although vertical phase-separated structures (TIPS-pentacene-top/PS-bottom) were formed on the substrate regardless of the spin coating time, the spin time governed the growth mode of the TIPS-pentacene molecules that phase-separated and crystallized on the insulating polymer. Excess residual solvent in samples spun for a short duration induces a convective flow in the drying droplet, thereby leading to one-dimensional (1D) growth mode of TIPS-pentacene crystals. In contrast, after an appropriate spin-coating time, an optimum amount of the residual solvent in the film led to two-dimensional (2D) growth mode of TIPS-pentacene crystals. The 2D spherulites of TIPS-pentacene are extremely advantageous for improving the field-effect mobility of FETs compared to needle-like 1D structures, because of the high surface coverage of crystals with a unique continuous film structure. In addition, the porous structure observed in the 2D crystalline film allows gas molecules to easily penetrate into the channel region, thereby improving the gas sensing properties.

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Effect of Crystallization Modes in TIPS-pentacene/Insulating Polymer Blends on the Gas Sensing Properties of Organic Field-Effect Transistors

Effects of Grain Boundary Density on the Gas Sensing Properties of Triethylsilylethynyl‐Anthradithiophene Field‐Effect Transistors

Enhanced Gas Sensing Performance of Organic Field-Effect Transistors by Modulating the Dimensions of Triethylsilylethynyl-Anthradithiophene Microcrystal Arrays

Gas Sensors: Enhanced Gas Sensing Performance of Organic Field‐Effect Transistors by Modulating the Dimensions of Triethylsilylethynyl‐Anthradithiophene Microcrystal Arrays (Adv. Mater. Interfaces 4/2020)

The present invention relates to a method for manufacturing a gas sensor comprising a substrate, an organic semiconductor thin film formed on the substrate, a source electrode, and a drain electrode. According to the present invention, the method comprises the steps of: (a) preparing a solution dissolving an organic semiconductor compound therein and adjusting a mixing time of the solution to increase the number of crystal nuclei of an organic semiconductor in the solution; (b) coating the solution having the increased number of crystal nuclei on a substrate and drying the solution to manufacture a thin film; and (c) allowing the thin film to come in contact with solvent steam to crystallize the organic semiconductor compound of a thin film to manufacture an organic semiconductor thin film including an aggregated crystal formed by a plurality of crystal grains grown from the center of the plurality of crystal nuclei met each other. Accordingly, the mixing time of the organic semiconductor solution is adjusted to adjust the number of aggregations of the organic semiconductor, thereby increasing the density of a grain boundary of the organic semiconductor thin film. Moreover, an organic semiconductor thin film with a high grain boundary density is applied, thereby increasing a reaction speed and sensitivity.

Yena Seo

Papers

Effect of Crystallization Modes in TIPS-pentacene/Insulating Polymer Blends on the Gas Sensing Properties of Organic Field-Effect Transistors

Effects of Grain Boundary Density on the Gas Sensing Properties of Triethylsilylethynyl‐Anthradithiophene Field‐Effect Transistors

Enhanced Gas Sensing Performance of Organic Field-Effect Transistors by Modulating the Dimensions of Triethylsilylethynyl-Anthradithiophene Microcrystal Arrays

Gas Sensors: Enhanced Gas Sensing Performance of Organic Field‐Effect Transistors by Modulating the Dimensions of Triethylsilylethynyl‐Anthradithiophene Microcrystal Arrays (Adv. Mater. Interfaces 4/2020)

Method for preparing organic semiconductor thin film and method for fabricating gas sensor comprising the same