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Journal ArticleDOI

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

TL;DR: It is shown that when a solution processable organic semiconductor (6,13-bis(triisopropylsilylethynyl)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.
Abstract: 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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Citations
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01 Mar 2004
TL;DR: In this paper, a self-aligned regioregular poly(3-hexylthiophene) (P3HT) has been used to control the intermolecular interaction at the interface between P3HT and the insulator substrate by using self-assembled monolayers (SAMs) functionalized with various groups (NH2, NH2, OH, and CH3).
Abstract: 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.

391 citations

Journal ArticleDOI
TL;DR: A critical review of noteworthy applications that demonstrate how computational chemistry and machine learning can be used together to provide insightful predictions in molecular and materials modeling, retrosyntheses, catalysis, and drug design are reviewed.
Abstract: 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.

158 citations

Journal ArticleDOI
TL;DR: In this paper, the authors provide a review of the applications of computational chemistry and machine learning in molecular and materials modeling, retrosyntheses, catalysis, and drug design.
Abstract: 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.

155 citations

Journal ArticleDOI
Stuart J. Davies1, Iveren Abiem2, Kamariah Abu Salim3, Salomón Aguilar1  +156 moreInstitutions (79)
TL;DR: ForestGEO as discussed by the authors is a network of scientists and long-term forest dynamics plots (FDPs) spanning the Earth's major forest types, which together provide a holistic view of forest functioning.

103 citations

Journal ArticleDOI
TL;DR: In this article, the authors discuss the foremost applications of artificial intelligence (AI), particularly deep learning (DL) algorithms, in single-photon emission computed tomography (SPECT) and positron emission tomography(PET) imaging.

82 citations

References
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Journal ArticleDOI
TL;DR: It is demonstrated that the flexible pressure-sensitive organic thin film transistors fabrication can be used for non-invasive, high fidelity, continuous radial artery pulse wave monitoring, which may lead to the use of flexible pressure sensors in mobile health monitoring and remote diagnostics in cardiovascular medicine.
Abstract: Flexible pressure sensors are essential parts of an electronic skin to allow future biomedical prostheses and robots to naturally interact with humans and the environment. Mobile biomonitoring in long-term medical diagnostics is another attractive application for these sensors. Here we report the fabrication of flexible pressure-sensitive organic thin film transistors with a maximum sensitivity of 8.4 kPa(-1), a fast response time of 15,000 cycles and a low power consumption of <1 mW. The combination of a microstructured polydimethylsiloxane dielectric and the high-mobility semiconducting polyisoindigobithiophene-siloxane in a monolithic transistor design enabled us to operate the devices in the subthreshold regime, where the capacitance change upon compression of the dielectric is strongly amplified. We demonstrate that our sensors can be used for non-invasive, high fidelity, continuous radial artery pulse wave monitoring, which may lead to the use of flexible pressure sensors in mobile health monitoring and remote diagnostics in cardiovascular medicine.

1,691 citations

Journal ArticleDOI
TL;DR: This paper review in more detail related work that originated at IBM during the last four years and has led to the fabrication of high-performance organic transistors on flexible, transparent plastic substrates requiring low operating voltages.
Abstract: In this paper we review recent progress in materials, fabrication processes, device designs, and applications related to organic thin-film transistors (OTFTs), with an emphasis on papers published during the last three years. Some earlier papers that played an important role in shaping the OTFT field are included, and a number of previously published review papers that cover that early period more completely are referenced. We also review in more detail related work that originated at IBM during the last four years and has led to the fabrication of high-performance organic transistors on flexible, transparent plastic substrates requiring low operating voltages.

1,192 citations

Journal ArticleDOI
TL;DR: The most important advances with regard to fundamental research, sensing mechanisms, and application of nanostructured materials for room-temperature conductometric sensor devices are reviewed here and particular emphasis is given to the relation between the nanostructure and sensor properties in an attempt to address structure-property correlations.
Abstract: Sensor technology has an important effect on many aspects in our society, and has gained much progress, propelled by the development of nanoscience and nanotechnology. Current research efforts are directed toward developing high-performance gas sensors with low operating temperature at low fabrication costs. A gas sensor working at room temperature is very appealing as it provides very low power consumption and does not require a heater for high-temperature operation, and hence simplifies the fabrication of sensor devices and reduces the operating cost. Nanostructured materials are at the core of the development of any room-temperature sensing platform. The most important advances with regard to fundamental research, sensing mechanisms, and application of nanostructured materials for room-temperature conductometric sensor devices are reviewed here. Particular emphasis is given to the relation between the nanostructure and sensor properties in an attempt to address structure-property correlations. Finally, some future research perspectives and new challenges that the field of room-temperature sensors will have to address are also discussed.

1,096 citations

Journal ArticleDOI
TL;DR: This paper reviews the chemical sensors and biosensors based on two types of OTFTs, including organic field-effect transistors (OFETs) and organic electrochemical transistor (OECTs), mainly focusing on the papers published in the past 10 years.
Abstract: Organic thin-film transistors (OTFTs) show promising applications in various chemical and biological sensors. The advantages of OTFT-based sensors include high sensitivity, low cost, easy fabrication, flexibility and biocompatibility. In this paper, we review the chemical sensors and biosensors based on two types of OTFTs, including organic field-effect transistors (OFETs) and organic electrochemical transistors (OECTs), mainly focusing on the papers published in the past 10 years. Various types of OTFT-based sensors, including pH, ion, glucose, DNA, enzyme, antibody-antigen, cell-based sensors, dopamine sensor, etc., are classified and described in the paper in sequence. The sensing mechanisms and the detection limits of the devices are described in details. It is expected that OTFTs may have more important applications in chemical and biological sensing with the development of organic electronics.

796 citations

Journal ArticleDOI
TL;DR: In this article, a diffusion equation was formulated by assuming that an inflammable gas (target gas) moves inside the film by Knudsen diffusion, while it reacts with the adsorbed oxygen following a first-order reaction kinetic.
Abstract: Influences of gas transport phenomena on the sensitivity of a thin film semiconductor gas sensor were investigated theoretically. A diffusion equation was formulated by assuming that an inflammable gas (target gas) moves inside the film by Knudsen diffusion, while it reacts with the adsorbed oxygen following a first-order reaction kinetic. By solving this equation under steady-state conditions, the target gas concentration inside the film was derived as a function of depth (x) from the film surface, Knudsen diffusion coefficient (DK), rate constant (k) and film thickness (L). The gas concentration profile thus obtained allowed to estimate the gas sensitivity (S) defined as the resistance ratio (Ra/Rg), under the assumption that the sheet conductance of the film at depth x is linear to the gas concentration there with a proportionality constant (sensitivity coefficient), a. The derived equation shows that S decreases sigmoidally down to unity with an increase in L k/D K . Further by assuming that the temperature dependence of rate constant (k) and sensitivity coefficient (a) follows Arrenius type ones with respective activation energies, it was possible to derive a general expression of S involving temperature (T). The expression shows that, when the activation energies are selected properly, the S versus T correlation results in a volcano-shaped one, its height increasing with decreasing L. The dependence of S on L at constant T as well as on T at constant L can thus be simulated fairly well based on the equation.

550 citations

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