Double perovskite Cs2AgBiBr6 radiation sensor: synthesis and characterization of single crystals

Single crystals of lead-free halide double perovskite Cs2AgBiBr6 sensor material manifest a remarkable potential for application in radiation detection and imaging. In this study, the purity and crystallinity of solution-grown Cs2AgBiBr6 single crystals with cubic Fm$$\overline{3}$$ 3 ¯ m symmetry have been corroborated by powder XRD measurements, while the single crystal XRD patterns reveal the dominant {111} lattice planes parallel to the sample surfaces. A wider range of lower resistivity values (106–109 Ωcm) was obtained from the I-V measurements compared to the 1.55 × 109–6.65 × 1010 Ωcm values from the van der Pauw method, which is typically higher for the Ag than for the carbon paint electrodes. Charge-carrier mobility values estimated from the SCLC method for the carbon paint-Cs2AgBiBr6 (1.90–4.82 cm2V−1 s−1) and the Ag-Cs2AgBiBr6 (0.58–4.54 cm2V−1 s−1) including the density of trap states (109–1010 cm−3) are comparable. Similar values of 1.89 cm2V−1 s−1 and 2.36 cm2V−1 s−1 are derived from the Hall effect measurements for a sample with carbon and Ag electrodes, respectively. The key electrical parameters including the X-ray photoresponse measurements indicate that the Cs2AgBiBr6 samples synthesized in this study satisfy requirements for radiation sensors. Graphical abstract

Phase Segregation via Etching-Induced Cation Migration in CoSx-ZnS Nanoarchitectures for Solar Hydrogen Evolution

Low charge carrier mobility limits the development of highly efficient semiconductor-based photocatalysis. Heterointerface engineering is a promising approach to spatially separate the photoexcited charge carriers and thus enhance photocatalytic activity....

Structural insights into Lewis acid and F4TCNQ doped conjugated polymers by solid-state magnetic resonance spectroscopy

Molecular doping strategies facilitate orders of magnitudes enhancements in the charge carrier mobility of organic semiconductors (OSCs). Understanding the mechanisms of different doping strategies for OSCs and molecular-level constraints on...

Special Issue: Perovskite Nanostructures: From Material Design to Applications

In the past decade, perovskite materials have attracted great scientific and technological interest due to their interesting opto-electronic properties. Nanostructuring of the perovskites, due to their reduced dimensions are advantageous in offering large surface area, controlled transport and charge carrier mobility, strong absorption and photoluminescence, and confinement effects. These features, together with the unique tunability in composition, shape, and functionalities in addition to the ability to form efficient, low-cost, and light-active structures make the perovskite nanostructures efficient functional components for multiple applications, ranging from photovoltaics and batteries to lasing and light-emitting diodes. The purpose of this Special Issue is to give an overview of the latest experimental findings concerning the tunability in composition, shape, functionalities, growth conditions, and synthesis procedures of perovskite structures and to identify the critical parameters for producing materials with functional characteristics.

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.

Revisiting the chevrel phase: Impact of dispersion corrections on the properties of Mo6S8 for cathode applications

While the Mo6S8 chevrel phase is frequently used as cathode material in Mg--ion batteries, theoretical studies on this material are comparatively scarce. The particular structure of the Mo6S8 phase, with rather loosely connected cluster entities, points to the important role of dispersion forces in this material. However, so far this aspect has been completely neglected in the discussion of Mo6S8 as cathode material for mono- and multivalent-ion batteries. In this work we therefore have studied the impact of dispersion forces on stability and kinetics of Mo6S8 intercalation compounds. For this purpose, a series of charge carriers (Li, Na, K, Mg, Ca, Zn, Al) has been investigated. Interestingly, dispersion forces are observed to only slightly affect the lattice spacing of the chevrel phase, nevertheless having a significant impact on insertion voltage and in particular on the charge carrier mobility in the material. Moreover, upon varying the charge carriers in the chevrel phase, their diffusion barriers are observed to scale linearly with the ion size, almost independent of the charge of the considered ions. This indicates a rather unique and geometry dominated diffusion mechanism in the chevrel phase. The consequences of these findings for the ion mobility in the chevrel phase will be carefully discussed.

Advanced Development of Sustainable PECVD Semitransparent Photovoltaics: A Review

Energy is the driving force behind the upcoming industrial revolution, characterized by connected devices and objects that will be perpetually supplied with energy. Moreover, the global massive energy consumption increase requires appropriate measures, such as the development of novel and improved renewable energy technologies for connecting remote areas to the grid. Considering the current prominent market share of unsustainable energy generation sources, inexhaustible and clean solar energy resources offer tremendous opportunities that, if optimally exploited, might considerably help to lessen the ever-growing pressure experienced on the grid nowadays. The R&D drive to develop and produce socio-economically viable solar cell technologies is currently realigning itself to manufacture advanced thin films deposition techniques for Photovoltaic solar cells. Typically, the quest for the wide space needed to deploy PV systems has driven scientists to design multifunctional nanostructured materials for semitransparent solar cells (STSCs) technologies that can fit in available household environmental and architectural spaces. Specifically, Plasma Enhanced Chemical Vapor Deposition (PECVD) technique demonstrated the ability to produce highly transparent coatings with the desired charge carrier mobility. The aim of the present article is to review the latest semi-transparent PV technologies that were impactful during the past decade with special emphasis on PECVD-related technologies. We finally draw some key recommendations for further technological improvements and sustainability.

Reorganization energies of flexible organic molecules as a challenging target for machine learning enhanced virtual screening

The molecular reorganization energy $\lambda$ strongly influences the charge carrier mobility of organic semiconductors and is therefore an important target for molecular design. Machine learning (ML) models generally have the potential to strongly accelerate this design process (e.g. in virtual screening studies) by providing fast and accurate estimates of molecular properties. While such models are well established for simple properties (e.g. the atomization energy), $\lambda$ poses a significant challenge in this context. In this paper, we address the questions of how ML models for $\lambda$ can be improved and what their benefit is in high-throughput virtual screening (HTVS) studies. We find that, while improved predictive accuracy can be obtained relative to a semiempirical baseline model, the improvement in molecular discovery is somewhat marginal. In particular, the ML enhanced screenings are more effective in identifying promising candidates but lead to a less diverse sample. We further use substructure analysis to derive a general design rule for organic molecules with low $\lambda$ from the HTVS results.