Accurate GW frontier orbital energies of 134 kilo molecules.

HOMO and LUMO energies are critical molecular properties that typically require high accuracy computations for practical applicability. Until now, a comprehensive dataset containing sufficiently accurate HOMO and LUMO energies has been unavailable. In this study, we introduce a new dataset of HOMO/LUMO energies for QM9 compounds, calculated using the GW method. The GW method offers adequate HOMO/LUMO prediction accuracy for diverse applications, exhibiting mean unsigned errors of 100 meV in the GW100 benchmark dataset. This database may serve as a benchmark of HOMO/LUMO prediction, delta-learning, and transfer learning, particularly for larger molecules where GW is the most accurate but still numerically feasible method. We anticipate that this dataset will enable the development of more accurate machine learning models for predicting molecular properties.

Controlling doping efficiency in organic semiconductors by tuning short-range overscreening.

Conductivity doping has emerged as an indispensable method to overcome the inherently low conductivity of amorphous organic semiconductors, which presents a great challenge in organic electronics applications. While tuning ionization potential and electron affinity of dopant and matrix is a common approach to control the doping efficiency, many other effects also play an important role. Here, we show that the quadrupole moment of the dopant anion in conjunction with the mutual near-field host-dopant orientation have a crucial impact on the conductivity. In particular, a large positive quadrupole moment of a dopant leads to an overscreening in host-dopant integer charge transfer complexes. Exploitation of this effect may enhance the conductivity by several orders of magnitude. This finding paves the way to a computer-aided systematic and efficient design of highly conducting amorphous small molecule doped organic semiconductors.

Molecular-Engineered Biradicals Based on the YIII-Phthalocyanine Platform.

A mixed-ligand phthalocyanine/porphyrin yttrium(III) radical double-decker complex (DD) was synthesized using the custom-made 5,10,15-tris(4-methoxyphenyl)-20-(4-((trimethylsilyl)ethynyl)phenyl)porphyrin. The trimethylsilyl functionality was then used to couple two such complexes into biradicals through rigid tethers. Glaser coupling was used to synthesize a short-tethered biradical (C1) and Sonogashira coupling to synthesize longer-tethered ones (C2 and C3). Field-swept echo-detected (FSED), saturation recovery, and spin nutation-pulsed electron paramagnetic resonance experiments revealed marked similarities of the magnetic properties of DD with those of the parent [Y(pc)2]• complex, both in the solid state and in CD2Cl2/CDCl3 4:1 frozen glasses. FSED experiments on the biradicals C2 and C3 revealed a spectral broadening with respect to the spectra of DD and [Y(pc)2]• assigned to the effect of dipolar interactions in solution. Apart from the main resonance, satellite features were also observed, which were simulated with dipole-dipole pairs of shortest distances, suggesting spin delocalization on the organic tether. FSED experiments on C1 yielded spectral line shapes that could not be simulated as the integration of the off-resonance echoes was complicated by field-dependent modulations. While, for all dimers, the on-resonance spin nutation experiments yielded Rabi oscillations of the same frequencies, off-resonance nutations on C1 yielded Rabi oscillations that could be assigned to a MS = -1 to MS = 0 transition within a S = 1 multiplet. The DFT calculations showed that the trans conformation of the complexes was significantly more stable than the cis one and that it induced a marked spin delocalization over the rigid organic tether. This "spin leakage" was most pronounced for the shortest biradical C1.

Room-temperature spin nutations in a magnetically condensed phase of [Y(pc)2]˙.

FID-detected nutations of the antiferromagnetic crystal form of [Y(pc)2]˙ demonstrated that its radical spin can be coherently driven in its magnetically condensed undeuterated phase and at room temperature. Liquid-helium nutations revealed additional Rabi oscillations assigned to transitions within higher-multiplicity states of finite-sized chain fragments.

De Novo Simulation of Charge Transport through Organic Single-Carrier Devices.

In amorphous organic semiconductor devices, electrons and holes are transported through layers of small organic molecules or polymers. The overall performance of the device depends both on the material and the device configuration. Measuring a single device configuration requires a large effort of synthesizing the molecules and fabricating the device, rendering the search for promising materials in the vast molecular space both nontrivial and time-consuming. This effort could be greatly reduced by computing the device characteristics from the first principles. Here, we compute transport characteristics of unipolar single-layer devices of prototypical hole- and electron-transporting materials, N,N'-di(1-naphthyl)-N,N'-diphenyl-(1,1'-biphenyl)-4,4'-diamine (α-NPD) and 2,2',2″-(1,3,5-benzinetriyl)-tris(1-phenyl-1-H-benzimidazole) (TPBi) using a first-principles multiscale approach that requires only the molecular constituents and the device geometry. This approach of generating a digital twin of the entire device can be extended to multilayer stacks and enables the computer design of materials and devices to facilitate systematic improvement of organic light-emitting diode (OLED) devices.

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.

Analyzing Dynamical Disorder for Charge Transport in Organic Semiconductors via Machine Learning.

Organic semiconductors are indispensable for today's display technologies in the form of organic light-emitting diodes (OLEDs) and further optoelectronic applications. However, organic materials do not reach the same charge carrier mobility as inorganic semiconductors, limiting the efficiency of devices. To find or even design new organic semiconductors with higher charge carrier mobility, computational approaches, in particular multiscale models, are becoming increasingly important. However, such models are computationally very costly, especially when large systems and long timescales are required, which is the case to compute static and dynamic energy disorder, i.e., the dominant factor to determine charge transport. Here, we overcome this drawback by integrating machine learning models into multiscale simulations. This allows us to obtain unprecedented insight into relevant microscopic materials properties, in particular static and dynamic disorder contributions for a series of application-relevant molecules. We find that static disorder and thus the distribution of shallow traps are highly asymmetrical for many materials, impacting widely considered Gaussian disorder models. We furthermore analyze characteristic energy level fluctuation times and compare them to typical hopping rates to evaluate the importance of dynamic disorder for charge transport. We hope that our findings will significantly improve the accuracy of computational methods used to predict application-relevant materials properties of organic semiconductors and thus make these methods applicable for virtual materials design.

Computing Charging and Polarization Energies of Small Organic Molecules Embedded into Amorphous Materials with Quantum Accuracy.

The ionization potential, electron affinity, and cation/anion polarization energies (IP, EA, P(+), P(-)) of organic molecules determine injection barriers, charge carriers balance, doping efficiency, and light outcoupling in organic electronics devices, such as organic light-emitting diodes (OLEDs). Computing IP and EA of isolated molecules is a common task for quantum chemistry methods. However, once molecules are embedded in an amorphous organic matrix, IP and EA values change, and accurate predictions become challenging. Here, we present a revised quantum embedding method [Friederich et al. J. Chem. Theory Comput. 2014, 10 (9), 3720-3725] that accurately predicts the dielectric permittivity and ionization potentials in three test materials, NPB, TCTA, and C60, and allows straightforward interpretation of their nature. The method paves the way toward reliable virtual screening of amorphous organic semiconductors with targeted IP/EA, polarization energies, and relative dielectric permittivity.

De Novo Calculation of the Charge Carrier Mobility in Amorphous Small Molecule Organic Semiconductors.

Organic semiconductors (OSC) are key components in applications such as organic photovoltaics, organic sensors, transistors and organic light emitting diodes (OLED). OSC devices, especially OLEDs, often consist of multiple layers comprising one or more species of organic molecules. The unique properties of each molecular species and their interaction determine charge transport in OSCs-a key factor for device performance. The small charge carrier mobility of OSCs compared to inorganic semiconductors remains a major limitation of OSC device performance. Virtual design can support experimental R&D towards accelerated R&D of OSC compounds with improved charge transport. Here we benchmark a de novo multiscale workflow to compute the charge carrier mobility solely on the basis of the molecular structure: We generate virtual models of OSC thin films with atomistic resolution, compute the electronic structure of molecules in the thin films using a quantum embedding procedure and simulate charge transport with kinetic Monte-Carlo protocol. We show that for 15 common amorphous OSC the computed zero-field and field-dependent mobility are in good agreement with experimental data, proving this approach to be an effective virtual design tool for OSC materials and devices.

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.

Disorder compensation controls doping efficiency in organic semiconductors.

Conductivity doping of inorganic and organic semiconductors enables a fantastic variety of highly-efficient electronic devices. While well understood for inorganic materials, the mechanism of doping-induced conductivity and Fermi level shift in organic semiconductors remains elusive. In microscopic simulations with full treatment of many-body Coulomb effects, we reproduce the Fermi level shift in agreement with experimental observations. We find that the additional disorder introduced by doping can actually compensate the intrinsic disorder of the material, such that the total disorder remains constant or is even reduced at doping molar ratios relevant to experiment. In addition to the established dependence of the doping-induced states on the Coulomb interaction in the ionized host-dopant pair, we find that the position of the Fermi level and electrical conductivity is controlled by disorder compensation. By providing a quantitative model for doping in organic semiconductors we enable the predictive design of more efficient redox pairs.

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.

In Situ Electron Driven Carbon Nanopillar-Fullerene Transformation through Cr Atom Mediation.

The promise of sp2 nanomaterials remains immense, and ways to strategically combine and manipulate these nanostructures will further enhance their potential as well as advance nanotechnology as a whole. The scale of these structures requires precision at the atomic scale. In this sense electron microscopes are attractive as they offer both atomic imaging and a means to structurally modify structures. Here we show how Cr atoms can be used as physical linkers to connect carbon nanotubes and fullerenes to graphene. Crucially, while under electron irradiation, the Cr atoms can drive transformations such as catalytic healing of a hole in graphene with simultaneous transformation of a single wall carbon nanotube into a fullerene. The atomic resolution of the electron microscopy along with density functional theory based total energy calculations provide insight into the dynamic transformations of Cr atom linkers. The work augments the potential of transmission electron microscopes as nanolaboratories.

The modular approach enables a fully ab initio simulation of the contacts between 3D and 2D materials.

Up to now, the electrical properties of the contacts between 3D metals and 2D materials have never been computed at a fully ab initio level due to the huge number of atomic orbitals involved in a current path from an electrode to a pristine 2D material. As a result, there are still numerous open questions and controversial theories on the electrical properties of systems with 3D/2D interfaces-for example, the current path and the contact length scalability. Our work provides a first-principles solution to this long-standing problem with the use of the modular approach, a method which rigorously combines a Green function formalism with the density functional theory (DFT) for this particular contact type. The modular approach is a general approach valid for any 3D/2D contact. As an example, we apply it to the most investigated among 3D/2D contacts-metal/graphene contacts-and show its abilities and consistency by comparison with existing experimental data. As it is applicable to any 3D/2D interface, the modular approach allows the engineering of 3D/2D contacts with the pre-defined electrical properties.

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.