Disorder-driven doping activation in organic semiconductors

Conductivity doping of organic semiconductors is an essential prerequisite for many organic devices, but the specifics of dopant activation are still not well understood. Using many-body simulations that include Coulomb interactions and dopant ionization/de-ionization events explicitly we here show significant doping efficiency even before the electron affinity of the dopant exceeds the ionization potential of the organic matrix (p-doping), similar to organic salts. We explicitly demonstrate that the ionization of weak molecular dopants in organic semiconductors is a disorder-, rather than thermally induced process. Practical implications of this finding are a weak dependence of the ionized dopant fraction on the electron affinity of the dopant, and an enhanced ionization of the weak dopants upon increasing dopant molar fraction. As a result, strategies towards dopant optimization should aim for presently neglected goals, such as the binding energy in host-dopant charge-transfer states being responsible for the number of mobile charge carriers. Insights into reported effects are provided from the analysis of the density of states, where two novel features appear upon partial dopant ionization. The findings in this work can be used in the rational design of dopant molecules and devices

Toward Design of Novel Materials for Organic Electronics

Materials for organic electronics are presently used in prominent applications, such as displays in mobile devices, while being intensely researched for other purposes, such as organic photovoltaics, large-area devices, and thin-film transistors. Many of the challenges to improve and optimize these applications are material related and there is a nearly infinite chemical space that needs to be explored to identify the most suitable material candidates. Established experimental approaches struggle with the size and complexity of this chemical space. Herein, the development of simulation methods is addressed, with a particular emphasis on predictive multiscale protocols, to complement experimental research in the identification of novel materials and illustrate the potential of these methods with a few prominent recent applications. Finally, the potential of machine learning and methods based on artificial intelligence is discussed to further accelerate the search for new materials

Towards an optimal contact metal for CNTFETs

Downscaling of the contact length Lc of a side-contacted carbon nanotube field-effect transistor (CNTFET) is challenging because of the rapidly increasing contact resistance as Lc falls below 20–50 nm. If in agreement with existing experimental results, theoretical work might answer the question, which metals yield the lowest CNT–metal contact resistance and what physical mechanisms govern the geometry dependence of the contact resistance. However, at the scale of 10 nm, parameter-free models of electron transport become computationally prohibitively expensive. In our work we used a dedicated combination of the Green function formalism and density functional theory to perform an overall ab initio simulation of extended CNT–metal contacts of an arbitrary length (including infinite), a previously not achievable level of simulations. We provide a systematic and comprehensive discussion of metal–CNT contact properties as a function of the metal type and the contact length. We have found and been able to explain very uncommon relations between chemical, physical and electrical properties observed in CNT–metal contacts. The calculated electrical characteristics are in reasonable quantitative agreement and exhibit similar trends as the latest experimental data in terms of: (i) contact resistance for Lc = ∞, (ii) scaling of contact resistance Rc(Lc); (iii) metal-defined polarity of a CNTFET. Our results can guide technology development and contact material selection for downscaling the length of side-contacts below 10 nm

Sensing Molecules with Metal–Organic Framework Functionalized Graphene Transistors

Graphene is inherently sensitive to vicinal dielectrics and local charge distributions, a property that can be probed by the position of the Dirac point in graphene field-effect transistors. Exploiting this as a useful sensing principle requires selectivity; however, graphene itself exhibits no molecule-specific interaction. Complementarily, metal–organic frameworks can be tailored to selective adsorption of specific molecular species. Here, a selective ethanol sensor is demonstrated by growing a surface-mounted metal–organic framework (SURMOF) directly onto graphene field-effect transistors (GFETs). Unprecedented shifts of the Dirac point, as large as 15 V, are observed when the SURMOF/GFET is exposed to ethanol, while a vanishingly small response is observed for isopropanol, methanol, and other constituents of the air, including water. The synthesis and conditioning of the hybrid materials sensor with its functional characteristics are described and a model is proposed to explain the origin, magnitude, and direction of the Dirac point voltage shift. Tailoring multiple SURMOFs to adsorb specific gases on an array of such devices thus generates a versatile, selective, and highly sensitive platform for sensing applications

Towards a multiscale modeling framework for metal-CNT interfaces

INTRODUCTION Very recently, astonishing experimental results for ultra-short Carbon nanotube transistors (CNTFETs) with channel lengths below 10 nm were published in While in DFT simulations the metal atoms of the contacts are included in the simulation of a transistor explicitly, they are considered in the TB approach only by a well-defined self-energy and properly chosen coupling parameters. In the EFM approach the extended metal coated tube region is reduced to a single point and included in the EFM simulations by means of boundary conditions comprising an effective dispersion relation and an effective injection gap (see RESULTS From the experimental device structure described in [1], three similar structures compatible with the different simulation methods are derived. From the DFT and the TB simulation results, effective dispersion relations are derived for the EFM approach allowing the calculation of the current voltage characteristics for different coupling strengths by means o