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Abstract: Disorder in organic semiconductors (OSCs) plays a determining role in energy transport properties underpinning optoelectronic device performance [1]. Both energetic disorder native to perfect crystals as well as deviations from crystalline order control transport properties [2,3]. Alongside crystallographic defects like stacking faults and grain boundaries, dislocations that distort molecular packing can introduce exciton- or charge-carrier traps that significantly hamper intermolecular energy transport [4]. Electron microscopy has been a mainstay for probing these crystallographic defects in inorganic semiconductors. Recent progress in atomically resolved electron microscopy has enabled imaging of individual defects in hybrid perovskites [5]. But while hybrid perovskites show structural degradation on the order of <200 e–Å-2 before [6], small molecule OSCs may undergo comparable loss of structure under exposures <30 e–Å-2 [7,8]. Methods that enable the crystallographic analysis of dislocations in beam-sensitive OSCs are therefore a necessary first step to establish their performance effects. A dislocation is described crystallographically in terms of a displacement vector in the lattice, termed a Burgers vector b. Most attempts to characterize dislocations in organic molecular crystals have relied on techniques at low spatial resolution, including etch pit imaging [9] and scanning probe techniques [10]. These approaches are unable to directly record the crystallography of dislocations or access the nanometre spatial resolution required to isolate individual defects. In contrast, electron microscopy combines the necessary spatial resolution to image the dislocation line as well as the crystallographic detail from electron diffraction to retrieve the Burgers vector. Typically, such an analysis is carried out by many repeated electron beam exposures and sample rotations aimed at identifying the crystal planes associated with a diffraction vector g that are not distorted by the dislocation, a so-called ‘invisibility criterion’ at g.b = 0. Here, we advance this approach for OSCs to carry out unambiguous analysis of the dislocation Burgers vector and type (screw, edge, or mixed) using four-dimensional scanning transmission electron microscopy (4D-STEM) now in a single exposure at a fluence of ~10 e–Å-2. Thin films of p-terphenyl and anthracene were prepared by solution crystallization as a set of benchmark organic optoelectronic materials [11]. On transfer to a lacey carbon support film for electron microscopy, the draping of the OSC crystals on the support film introduces a small amount of sample bending. This bending defines a set of diffraction conditions that produce ribbons of bright intensity running across images of the film referred to as bend contours. These bend contours exhibit an abrupt shift or break on crossing dislocations unless they satisfy the invisibility criterion. Our 4D-STEM approach specifically supports simultaneous analysis of many lattice planes approximately parallel to the crystal direction perpendicular to the film, i.e. [001] for p-terphenyl and [101] for anthracene. Plotting and fitting the magnitude of breaks in the bend contours as a function of the corresponding diffraction vectors (g) for each plane determines the Burgers vector. For instance, this analysis establishes mixed-type b = [010] dislocations in p-terphenyl and anthracene. These generalizable methods make an analysis of the Burgers vectors of dislocations in beam-sensitive OSC films a routine process. The capability to measure the character and type of dislocations will provide experimental input for models of distortions at these structural defects and enables assessing methods for inhibiting dislocation formation during crystal growth and reducing or removing their deleterious contributions to device performance.

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Abstract: Single-atom catalytic sites may have existed in all supported transition metal catalysts since their first application. Yet, interest in the design of single-atom heterogeneous catalysts (SACs) only really grew when advances in transmission electron microscopy (TEM) permitted direct confirmation of metal site isolation. While atomic-resolution imaging remains a central characterization tool, poor statistical significance, reproducibility, and interoperability limit its scope for deriving robust characteristics about these frontier catalytic materials. Here, we introduce a customized deep-learning method for automated atom detection in image analysis, a rate-limiting step toward high-throughput TEM. Platinum atoms stabilized on a functionalized carbon support with a challenging irregular three-dimensional morphology serve as a practically relevant test system with promising scope in thermo- and electrochemical applications. The model detects over 20,000 atomic positions for the statistical analysis of important properties for establishing structure–performance relations over nanostructured catalysts, like the surface density, proximity, clustering extent, and dispersion uniformity of supported metal species. Good performance obtained on direct application of the model to an iron SAC based on carbon nitride demonstrates its generalizability for single-atom detection on carbon-related materials. The approach establishes a route to integrate artificial intelligence into routine TEM workflows. It accelerates image processing times by orders of magnitude and reduces human bias by providing an uncertainty analysis that is not readily quantifiable in manual atom identification, improving standardization and scalability.

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Abstract: There is currently substantial interest in stabilizing the simple ternary FAPbI3 perovskite because of its near-optimal band gap and superior thermal stability compared to methylammonium-based materials.1 The key challenge of FAPbI3 is the thermodynamic instability of the polymorph required for efficient light harvesting. Without additives, the black photoactive α-polymorph is only stable above ca. 160°C. At room temperature, it is metastable and rapidly transitions to the non-perovskite yellow polymorph. The stabilization of the black polymorph at room temperature can be achieved, for example, by adding a small amount of the pernicious MA through use of methylammonium chloride (in conjunction with formamidinium formate),2 methylammonium thiocyanate,3 or methylammonium formate.4 We have developed a new stabilization strategy which does not involve the addition of MA.5 Instead, it uses a surface-templating agent (EDTA) which modifies the material without incorporating into the structure. We use a combination of scanning electron diffraction (SED) and nuclear magnetic resonance spectroscopies (NMR, NQR) to identify the atomic-level mechanism of action of EDTA in this role. We find that it templates the structure by inducing a small octahedral tilt, only resolvable with local characterization techniques, and imparts remarkable phase stability by arresting transitions to low-dimensional polymorphs. This octahedral tilt engineering strategy is remarkably universal, and we show that it is the intrinsic stabilization mechanism in the state-of-the-art FA-rich mixed-cation materials.