Thermodynamic Origin of the Photostability of the Two-Dimensional Perovskite PEA2Pb(I1-x Br x )4.

The two-dimensional (2D) mixed halide perovskite PEA2Pb(I1-x Br x )4 exhibits high phase stability under illumination as compared to the three-dimensional (3D) counterpart MAPb(I1-x Br x )3. We explain this difference using a thermodynamic theory that considers the sum of a compositional and a photocarrier free energy. Ab initio calculations show that the improved compositional phase stability of the 2D perovskite is caused by a preferred I-Br distribution, leading to a much lower critical temperature for halide segregation in the dark than for the 3D perovskite. Moreover, a smaller increase of the band gap with Br concentration x and a markedly shorter photocarrier lifetime in the 2D perovskite reduce the driving force for phase segregation under illumination, enhancing the photostability.

Effect of Light-Induced Halide Segregation on the Performance of Mixed-Halide Perovskite Solar Cells.

Light-induced halide segregation hampers obtaining stable wide-band-gap solar cells based on mixed iodide-bromide perovskites. So far, the effect of prolonged illumination on the performance of mixed-halide perovskite solar cells has not been studied in detail. It is often assumed that halide segregation leads to a loss of open-circuit voltage. By simultaneously recording changes in photoluminescence and solar cell performance under prolonged illumination, we demonstrate that cells instead deteriorate by a loss of short-circuit current density and that the open-circuit voltage is less affected. The concurrent red shift, increased lifetime, and higher quantum yield of photoluminescence point to the formation of relatively emissive iodide-rich domains under illumination. Kinetic Monte Carlo simulations provide an atomistic insight into their formation via exchange of bromide and iodide, mediated by halide vacancies. Localization of photogenerated charge carriers in low-energy iodide-rich domains and subsequent recombination cause reduced photocurrent and red-shifted photoluminescence. The loss in photovoltaic performance is diminished by partially replacing organic cations by cesium ions. Ultrasensitive photocurrent spectroscopy shows that cesium ions result in a lower density of sub-band-gap defects and suppress defect growth under illumination. These defects are expected to play a role in the development and recovery of light-induced compositional changes.

Unified theory for light-induced halide segregation in mixed halide perovskites.

Mixed halide perovskites that are thermodynamically stable in the dark demix under illumination. This is problematic for their application in solar cells. We present a unified thermodynamic theory for this light-induced halide segregation that is based on a free energy lowering of photocarriers funnelling to a nucleated phase with different halide composition and lower band gap than the parent phase. We apply the theory to a sequence of mixed iodine-bromine perovskites. The spinodals separating metastable and unstable regions in the composition-temperature phase diagrams only slightly change under illumination, while light-induced binodals separating stable and metastable regions appear signalling the nucleation of a low-band gap iodine-rich phase. We find that the threshold photocarrier density for halide segregation is governed by the band gap difference of the parent and iodine-rich phase. Partial replacement of organic cations by cesium reduces this difference and therefore has a stabilizing effect.

A deep-learning approach to realizing functionality in nanoelectronic devices.

Many nanoscale devices require precise optimization to function. Tuning them to the desired operation regime becomes increasingly difficult and time-consuming when the number of terminals and couplings grows. Imperfections and device-to-device variations hinder optimization that uses physics-based models. Deep neural networks (DNNs) can model various complex physical phenomena but, so far, are mainly used as predictive tools. Here, we propose a generic deep-learning approach to efficiently optimize complex, multi-terminal nanoelectronic devices for desired functionality. We demonstrate our approach for realizing functionality in a disordered network of dopant atoms in silicon. We model the input-output characteristics of the device with a DNN, and subsequently optimize control parameters in the DNN model through gradient descent to realize various classification tasks. When the corresponding control settings are applied to the physical device, the resulting functionality is as predicted by the DNN model. We expect our approach to contribute to fast, in situ optimization of complex (quantum) nanoelectronic devices.

High energy acceptor states strongly enhance exciton transfer between metal organic phosphorescent dyes.

Exciton management in organic light-emitting diodes (OLEDs) is vital for improving efficiency, reducing device aging, and creating new device architectures. In particular in white OLEDs, exothermic Förster-type exciton transfer, e.g. from blue to red emitters, plays a crucial role. It is known that a small exothermicity partially overcomes the spectral Stokes shift, enhancing the fraction of resonant donor-acceptor pair states and thus the Förster transfer rate. We demonstrate here a second enhancement mechanism, setting in when the exothermicity exceeds the Stokes shift: transfer to multiple higher-lying electronically excited states of the acceptor molecules. Using a recently developed computational method we evaluate the Förster transfer rate for 84 different donor-acceptor pairs of phosphorescent emitters. As a result of the enhancement the Förster radius tends to increase with increasing exothermicity, from around 1 nm to almost 4 nm. The enhancement becomes particularly strong when the excited states have a large spin-singlet character.

Ballistic Phonons in Ultrathin Nanowires.

According to Fourier's law, a temperature difference across a material results in a linear temperature profile and a thermal conductance that decreases inversely proportional to the system length. These are the hallmarks of diffusive heat flow. Here, we report heat flow in ultrathin (25 nm) GaP nanowires in the absence of a temperature gradient within the wire and find that the heat conductance is independent of wire length. These observations deviate from Fourier's law and are direct proof of ballistic heat flow, persisting for wire lengths up to at least 15 µm at room temperature. When doubling the wire diameter, a remarkably sudden transition to diffusive heat flow is observed. The ballistic heat flow in the ultrathin wires can be modeled within Landauer's formalism by ballistic phonons with an extraordinarily long mean free path.

Classification with a disordered dopant-atom network in silicon.

Classification is an important task at which both biological and artificial neural networks excel1,2. In machine learning, nonlinear projection into a high-dimensional feature space can make data linearly separable3,4, simplifying the classification of complex features. Such nonlinear projections are computationally expensive in conventional computers. A promising approach is to exploit physical materials systems that perform this nonlinear projection intrinsically, because of their high computational density5, inherent parallelism and energy efficiency6,7. However, existing approaches either rely on the systems' time dynamics, which requires sequential data processing and therefore hinders parallel computation5,6,8, or employ large materials systems that are difficult to scale up7. Here we use a parallel, nanoscale approach inspired by filters in the brain1 and artificial neural networks2 to perform nonlinear classification and feature extraction. We exploit the nonlinearity of hopping conduction9-11 through an electrically tunable network of boron dopant atoms in silicon, reconfiguring the network through artificial evolution to realize different computational functions. We first solve the canonical two-input binary classification problem, realizing all Boolean logic gates12 up to room temperature, demonstrating nonlinear classification with the nanomaterial system. We then evolve our dopant network to realize feature filters2 that can perform four-input binary classification on the Modified National Institute of Standards and Technology handwritten digit database. Implementation of our material-based filters substantially improves the classification accuracy over that of a linear classifier directly applied to the original data13. Our results establish a paradigm of silicon-based electronics for small-footprint and energy-efficient computation14.

Stabilizing Lead-Free All-Inorganic Tin Halide Perovskites by Ion Exchange.

Because of its thermal stability, lead-free composition, and nearly ideal optical and electronic properties, the orthorhombic CsSnI3 perovskite is considered promising as a light absorber for lead-free all-inorganic perovskite solar cells. However, the susceptibility of this three-dimensional perovskite toward oxidation in air has limited the development of solar cells based on this material. Here, we report the findings of a computational study which identifies promising Rb y Cs1-y Sn(Br x I1-x )3 perovskites for solar cell applications, prepared by substituting cations (Rb for Cs) and anions (Br for I) in CsSnI3. We show the evolution of the material electronic structure as well as its thermal and structural stabilities upon gradual substitution. Importantly, we demonstrate how the unwanted yellow phase can be suppressed by substituting Br for I in CsSn(Br x I1-x )3 with x ≥ 1/3. We predict that substitution of Rb for Cs results in a highly homogeneous solid solution and therefore an improved film quality and applicability in solar cell devices.

Interstitial Occupancy by Extrinsic Alkali Cations in Perovskites and Its Impact on Ion Migration.

Recent success in achieving highly stable Rb-containing organolead halide perovskites has indicated the possibility of incorporating small monovalent cations, which cannot fit in the lead-halide cage with an appropriate tolerance factor, into the perovskite lattice while maintaining a pure stable "black" phase. In this study, through a combined experimental and theoretical investigation by density functional theory (DFT) calculations on the incorporation of extrinsic alkali cations (Rb+ , K+ , Na+ , and Li+ ) in perovskite materials, the size-dependent interstitial occupancy of these cations in the perovskite lattice is unambiguously revealed. Interestingly, DFT calculations predict the increased ion migration barriers in the lattice after the interstitial occupancy. To verify this prediction, ion migration behavior is characterized through hysteresis analysis of solar cells, electrical poling, temperature-dependent conductivity, and time-dependent photoluminescence measurements. The results collectively point to the suppression of ion migration after lattice interstitial occupancy by extrinsic alkali cations. The findings of this study provide new material design principles to manipulate the structural and ionic properties of multication perovskite materials.

Accurate and efficient band gap predictions of metal halide perovskites using the DFT-1/2 method: GW accuracy with DFT expense.

The outstanding optoelectronics and photovoltaic properties of metal halide perovskites, including high carrier motilities, low carrier recombination rates, and the tunable spectral absorption range are attributed to the unique electronic properties of these materials. While DFT provides reliable structures and stabilities of perovskites, it performs poorly in electronic structure prediction. The relativistic GW approximation has been demonstrated to be able to capture electronic structure accurately, but at an extremely high computational cost. Here we report efficient and accurate band gap calculations of halide metal perovskites by using the approximate quasiparticle DFT-1/2 method. Using AMX3 (A = CH3NH3, CH2NHCH2, Cs; M = Pb, Sn, X = I, Br, Cl) as demonstration, the influence of the crystal structure (cubic, tetragonal or orthorhombic), variation of ions (different A, M and X) and relativistic effects on the electronic structure are systematically studied and compared with experimental results. Our results show that the DFT-1/2 method yields accurate band gaps with the precision of the GW method with no more computational cost than standard DFT. This opens the possibility of accurate electronic structure prediction of sophisticated halide perovskite structures and new materials design for lead-free materials.

Charge transport in nanoscale vertical organic semiconductor pillar devices.

We report charge transport measurements in nanoscale vertical pillar structures incorporating ultrathin layers of the organic semiconductor poly(3-hexylthiophene) (P3HT). P3HT layers with thickness down to 5 nm are gently top-contacted using wedging transfer, yielding highly reproducible, robust nanoscale junctions carrying high current densities (up to 106 A/m2). Current-voltage data modeling demonstrates excellent hole injection. This work opens up the pathway towards nanoscale, ultrashort-channel organic transistors for high-frequency and high-current-density operation.

Molecular-scale simulation of electroluminescence in a multilayer white organic light-emitting diode.

In multilayer white organic light-emitting diodes the electronic processes in the various layers--injection and motion of charges as well as generation, diffusion and radiative decay of excitons--should be concerted such that efficient, stable and colour-balanced electroluminescence can occur. Here we show that it is feasible to carry out Monte Carlo simulations including all of these molecular-scale processes for a hybrid multilayer organic light-emitting diode combining red and green phosphorescent layers with a blue fluorescent layer. The simulated current density and emission profile are shown to agree well with experiment. The experimental emission profile was obtained with nanometre resolution from the measured angle- and polarization-dependent emission spectra. The simulations elucidate the crucial role of exciton transfer from green to red and the efficiency loss due to excitons generated in the interlayer between the green and blue layers. The perpendicular and lateral confinement of the exciton generation to regions of molecular-scale dimensions revealed by this study demonstrate the necessity of molecular-scale instead of conventional continuum simulation.

Operational stability of organic field-effect transistors.

Organic field-effect transistors (OFETs) are considered in technological applications for which low cost or mechanical flexibility are crucial factors. The environmental stability of the organic semiconductors used in OFETs has improved to a level that is now sufficient for commercialization. However, serious problems remain with the stability of OFETs under operation. The causes for this have remained elusive for many years. Surface potentiometry together with theoretical modeling provide new insights into the mechanisms limiting the operational stability. These indicate that redox reactions involving water are involved in an exchange of mobile charges in the semiconductor with protons in the gate dielectric. This mechanism elucidates the established key role of water and leads in a natural way to a universal "stress function", describing the stretched exponential-like time dependence ubiquitously observed. Further study is needed to determine the generality of the mechanism and the role of other mechanisms.

Spin in organics: a new route to spintronics.

New developments in the nascent field of organic spintronics are discussed. Two classes of phenomena can be discerned. In hybrid organic spin valves (OSVs), an organic semiconducting film is sandwiched between two ferromagnetic (FM) thin films, aiming at magnetoresistive effects as a function of the relative alignment of the respective magnetization directions. Alternatively, organic magnetoresistance (OMAR) is achieved without any FM components, and is an intrinsic property of the organic semiconductor material. Some of the exciting characteristics of OMAR, in both electrical conductance and photoconductance, are presented. A systematic, combined experimental-theoretical study of sign changes between positive and negative magnetoresistance is shown to provide important insight about the underlying mechanisms of OMAR. A simple explanation of experimental observations is obtained by combining a 'spin-blocking' mechanism, an essential ingredient in the recently proposed bipolaron model, with specific features of the device physics of space charge limited current devices in the bipolar regime. Finally, we discuss possible links between the physics relevant for OMAR and that for OSVs. More specifically, weak hyperfine fields from the hydrogen atoms in organic materials are thought to be crucial for a proper understanding of both types of phenomena.

Extreme sensitivity of circular dichroism to long-range excitonic couplings in helical supramolecular assemblies.

Circular dichroism (CD) spectroscopy is an ideal tool for studying the self-assembly of helical supramolecular assemblies since it is very sensitive to extended excitonic couplings between chiral chromophores. We show that the CD spectrum retains its high sensitivity to long-range interactions even in the presence of extreme disorder and strong interaction with vibrations when excitations are mainly localized on individual molecules. We derive a universal expression for the first moment of the CD spectrum of helical assemblies in terms of a modulated sum over excitonic couplings, which is independent of the strength of the energetic disorder, the spatial correlation of the disorder, and the strength of the interaction with vibrations. This demonstrates that excitonic couplings can be directly extracted from experimental CD spectra without having information about the energetic disorder and vibrational interactions. We apply our results to helical assemblies of functionalized chiral oligo(p-phenylenevinylene) molecules and show that existing theoretical values for the excitonic couplings should be adapted in order to obtain agreement with the experimental CD spectrum.

Monolayer coverage and channel length set the mobility in self-assembled monolayer field-effect transistors.

The mobility of self-assembled monolayer field-effect transistors (SAMFETs) traditionally decreases dramatically with increasing channel length. Recently, however, SAMFETs using liquid-crystalline molecules have been shown to have bulk-like mobilities that are virtually independent of channel length. Here, we reconcile these scaling relations by showing that the mobility in liquid crystalline SAMFETs depends exponentially on the channel length only when the monolayer is incomplete. We explain this dependence both numerically and analytically, and show that charge transport is not affected by carrier injection, grain boundaries or conducting island size. At partial coverage, that is when the monolayer is incomplete, liquid-crystalline SAMFETs thus form a unique model system to study size-dependent conductance originating from charge percolation in two dimensions.

Optical spectra and stokes shift in double-stranded helical supramolecular assemblies.

We study the photoluminescence from helical MOPV4 aggregates using a model that includes excitonic coupling, exciton-phonon coupling, and spatially correlated disorder in the chromophore transition energies. The helical aggregates consist of stacked dimers of MOPV4 chromophores. We have modeled these helical stacks as double-stranded aggregates, allowing us to investigate the effect of correlated disorder within the dimers on emission. We have studied the dependence of the Stokes shift, the emission line widths, and the ratio of the 0-0 to 0-1 emission peaks on the aggregate size and disorder. Our findings show that this peak ratio is quite insensitive to the aggregate size if the latter exceeds the coherence length of the emitting exciton. This makes this ratio a reliable probe for both disorder and the coherence length of the emitting exciton. We have found only a weak dependence of this peak ratio on the degree of correlation between the transition energies within each dimer, whereas such correlation has a large effect on the aggregate-size-dependent Stokes shift. By comparison with experiment, we have estimated the coherence length of the emitting exciton to be only one lattice spacing along the stacking direction. From our analysis of the Stokes shift we conclude that the exciton diffusion length is in the range 6-13 nm.

Photoluminescence spectra of self-assembling helical supramolecular assemblies: a theoretical study.

The reversible assembly of helical supramolecular polymers of chiral molecular building blocks is known to be governed by the interplay between mass action and the competition between weakly and strongly bound states of these building blocks. The highly co-operative transition from free monomers at high temperatures to long helical aggregates at low temperatures can be monitored by photoluminescence spectroscopy that probes the energetically lowest-lying optical excitations in the assemblies. In order to provide the interpretation of obtained spectroscopic data with a firm theoretical basis, we present a comprehensive model that combines a statistical theory of the equilibrium polymerization with a quantum-mechanical theory that not only accounts for the conformational properties of the assemblies but also describes the impact of correlated energetic disorder stemming from deformations within the chromophores and their interaction with solvent molecules. The theoretical predictions are compared to fluorescence spectra of chiral oligo(p-phenylene-vinylene) molecules in the solvent dodecane and we find them to qualitatively describe the red-shift of the main fluorescence peak and its decreasing intensity upon aggregation.