Johannes Müller

Four-dimensional scanning transmission electron microscopy (4DSTEM) is a powerful diffraction-based technique to investigate electron-transparent samples, probing local crystallinity, orientation, strain, and many more properties [ 1]. Furthermore, various open source Python packages exist to analyze 4D-STEM datasets, for instance LiberTEM, py4DSTEM, and pyxem [ 2-4].

Ptychography is a computational imaging technique that has risen in popularity in the x-ray and electron microscopy communities in the past half decade. One of the reasons for this success is the development of new high performance electron detectors with increased dynamic range and readout speed, both of which are necessary for a successful application of this technique. Despite the advances made in computing power, processing the recorded data remains a challenging task, and the growth in data rate has made the size of the resulting datasets a bottleneck for the whole process. Here we present an investigation into lossy compression methods for electron diffraction patterns that retain the necessary information for ptychographic reconstructions, yet lead to a decrease in data set size by three or four orders of magnitude. We apply several compression methods to both simulated and experimental data - all with promising results.

4D scanning transmission electron microscopy (4D‐STEM) is a powerful method for characterizing electron‐transparent samples with down to sub‐Ångstrom spatial resolution. 4D‐STEM can reveal local crystallinity, orientation, grain size, strain, and many more sample properties by rastering a convergent electron beam over a sample area and acquiring a transmission diffraction pattern (DP) at each scan position. These patterns are rich in information about the atomic structure of the probed volume, making this technique a potent tool to characterize even inhomogeneous samples. 4D‐STEM can also be used in scanning electron microscopes (SEMs) by placing an electron‐sensitive camera below the sample. 4D‐STEM‐in‐SEMs is ideally suited to characterize 2D materials and 2D‐like van der Waals heterostructures (vdWH) due to their inherent thickness of a few nanometers. The lower accelerating voltage of SEMs leads to strong scattering even from monolayers. The large field of view and down to sub‐nm spatial resolution of SEMs are ideal to map properties of the different constituents of 2D‐like vdWH by probing their combined sample volume. A unique 4D‐STEM‐in‐SEM system is applied to reveal the single crystallinity of MoS₂ exfoliated with gold‐mediation as well as the crystal orientation and coverage of both components of a C60/MoS₂ vdWH are determined.

Semiconducting carbon nitride polymers are used in metal‐free photocatalysts and in opto‐electronic devices. Conventionally, they are obtained using thermal and ionothermal syntheses in inscrutable, closed systems and therefore, their condensation behavior is poorly understood. Here, the synthetic protocols and properties are compared for two types of carbon nitride materials – 2D layered poly(triazine imide) (PTI) and hydrogen‐bonded melem hydrate – obtained from three low‐melting salt eutectics taken from the systematic series of the alkali metal halides: LiCl/KCl, LiBr/KBr, and LiI/KI. The size of the anion plays a significant role in the formation process of the condensed carbon nitride polymers, and it suggests a strong templating effect. The smaller anions (chloride and bromide) become incorporated into triazine (C₃N₃)‐based PTI frameworks. The larger iodide does not stabilize the formation of a triazine‐based polymer, but instead it leads to the formation of the heptazine (C₆N₇)‐based hydrogen‐bonded melem hydrate as the main crystalline phase. Melem hydrate, obtained as single‐crystalline powders, was compared with PTI in photocatalytic hydrogen evolution from water and in an OLED device. Further, the emergence of each carbon nitride species from its corresponding salt eutectic was rationalized via density functional theory calculations. This study highlights the possibilities to further tailor the properties of eutectic salt melts for ionothermal synthesis of organic functional materials.

We present a method that lowers the dose required for a ptychographic reconstruction by adaptively scanning the specimen, thereby providing the required spatial information redundancy in the regions of highest importance. The proposed method is built upon a deep learning model that is trained by reinforcement learning (RL), using prior knowledge of the specimen structure from training data sets. We show that equivalent low-dose experiments using adaptive scanning outperform conventional ptychography experiments in terms of reconstruction resolution.

Poly(triazine imide) (PTI) is a highly crystalline semiconductor, and though no techniques exist that enable synthesis of macroscopic monolayers of PTI, it is possible to study it in thin layer device applications that are compatible with its polycrystalline, nanoscale morphology. We find that the by‐product of conventional PTI synthesis is a C−C carbon‐rich phase that is detrimental for charge transport and photoluminescence. An optimized synthetic protocol yields a PTI material with an increased quantum yield, enabled photocurrent and electroluminescence. We report that protonation of the PTI structure happens preferentially at the pyridinic N atoms of the triazine rings, is accompanied by exfoliation of PTI layers, and contributes to increases in quantum yield and exciton lifetimes. This study describes structure–property relationships in PTI that link the nature of defects, their formation, and how to avoid them with the optical and electronic performance of PTI. On the basis of our findings, we create an OLED prototype with PTI as the active, metal‐free material.

Poly(triazinimid) (PTI) ist ein hochkristalliner organischer Halbleiter. Obwohl es keine Techniken gibt, die die Synthese makroskopischer Monolagen von PTI ermöglichen, ist es möglich, das kristalline Pulver in Dünnfilme zu verarbeiten und über die Eigenschaften des polykristallinen Materials zu lernen. Wir fanden, dass das Nebenprodukt der herkömmlichen PTI‐Synthese eine kohlenstoffreiche C‐C‐Phase ist, die für den Ladungstransport und die Photolumineszenz von Nachteil ist. Eine optimierte Synthese führt zu einem PTI‐Material mit erhöhter Quantenausbeute, Photostrom und Elektrolumineszenz. Die Protonierung der PTI‐Struktur erfolgt bevorzugt an den Pyridin‐N‐Atomen der Triazin‐Ringe und geht womöglich mit einer Exfolierung der PTI‐Schichten einher, was sich durch die Erhöhung der Quantenausbeute und der Exzitonenlebensdauer zeigt. Struktur‐Eigenschafts‐Beziehungen in PTI werden beschrieben, die die Art der Defekte, ihre Bildung und ihre Vermeidung mit der optischen und elektronischen Leistung von PTI verbinden. Auf der Grundlage unserer Erkenntnisse präparieren wir eine OLED mit PTI als aktivem, metallfreiem Material.

Increasing demands for new computer architectures may require embedded non-volatile memories as for example in-memory computing. Ferroelectric field-effect transistors (FeFETs) add further advantages besides their outstanding properties due to the availability of both n-type and p-type transistors. The latter favor a different channel materials, like SiGe, due to the low hole mobility in silicon. In this article, we demonstrate the integration of ferroelectric hafnium oxide on SiGe as well as working p-type FeFETs, possessing a large memory window of about 1.1 V and low variability. Such architectures were co-integrated into a standard high-k metal gate (HKMG) CMOS platform. Furthermore, we report on the impact of annealing temperature on the interface and ferroelectric layer, which appears to be universal for SiGe and Si substrates. Here, a growth of the interface layer during annealing at higher temperatures was observed as well as a reduction of the wake-up effect for the ferroelectric layer.