Search for: All records

Ferro‐rotational (FR) materials, renowned for their distinctive material functionalities, present challenges in the growth of homo‐FR crystals (i.e., single FR domain). This study explores a cost‐effective approach to growing homo‐FR helimagnetic RbFe(SO₄)₂(RFSO) crystals by lowering the crystal growth temperature below theT_FRthreshold using the high‐pressure hydrothermal method. Through polarized neutron diffraction experiments, it is observed that nearly 86% of RFSO crystals consist of a homo‐FR domain. Notably, RFSO displays remarkable stability in the FR phase, with an exceptionally highT_FRof ≈573 K. Furthermore, RFSO exhibits a chiral helical magnetic structure with switchable ferroelectric polarization below 4 K. Importantly, external electric fields can induce a single magnetic domain state and manipulate its magnetic chirality. The findings suggest that the search for new FR magnets with outstanding material properties should consider magnetic sulfates as promising candidates.

 

Moiré magnetism featured by stacking engineered atomic registry and lattice interactions has recently emerged as an appealing quantum state of matter at the forefront of condensed matter physics research. Nanoscale imaging of moiré magnets is highly desirable and serves as a prerequisite to investigate a broad range of intriguing physics underlying the interplay between topology, electronic correlations, and unconventional nanomagnetism. Here we report spin defect-based wide-field imaging of magnetic domains and spin fluctuations in twisted double trilayer (tDT) chromium triiodide CrI₃. We explicitly show that intrinsic moiré domains of opposite magnetizations appear over arrays of moiré supercells in low-twist-angle tDT CrI₃. In contrast, spin fluctuations measured in tDT CrI₃manifest little spatial variations on the same mesoscopic length scale due to the dominant driving force of intralayer exchange interaction. Our results enrich the current understanding of exotic magnetic phases sustained by moiré magnetism and highlight the opportunities provided by quantum spin sensors in probing microscopic spin related phenomena on two-dimensional flatland.

 

After graphene was first exfoliated in 2004, research worldwide has focused on discovering and exploiting its distinctive electronic, mechanical, and structural properties. Application of the efficacious methodology used to fabricate graphene, mechanical exfoliation followed by optical microscopy inspection, to other analogous bulk materials has resulted in many more two-dimensional (2D) atomic crystals. Despite their fascinating physical properties, manual identification of 2D atomic crystals has the clear drawback of low-throughput and hence is impractical for any scale-up applications of 2D samples. To combat this, recent integration of high-performance machine-learning techniques, usually deep learning algorithms because of their impressive object recognition abilities, with optical microscopy have been used to accelerate and automate this traditional flake identification process. However, deep learning methods require immense datasets and rely on uninterpretable and complicated algorithms for predictions. Conversely, tree-based machine-learning algorithms represent highly transparent and accessible models. We investigate these tree-based algorithms, with features that mimic color contrast, for automating the manual inspection process of exfoliated 2D materials (e.g., MoSe₂). We examine their performance in comparison to ResNet, a famous Convolutional Neural Network (CNN), in terms of accuracy and the physical nature of their decision-making process. We find that the decision trees, gradient boosted decision trees, and random forests utilize physical aspects of the images to successfully identify 2D atomic crystals without suffering from extreme overfitting and high training dataset demands. We also employ a post-hoc study that identifies the sub-regions CNNs rely on for classification and find that they regularly utilize physically insignificant image attributes when correctly identifying thin materials.

 

Abstract As described in the Introduction, we became interested in the existing literature for the crystallization behavior of (±)-[Co(en) 3 ]I 3 ·H 2 O and the absolute configuration of its enantiomers because of our project on the historical sequence of chemical studies leading Werner to formulate his Theory of Coordination Chemistry. In so doing, we discovered a number of interesting facts, including the possibility that the published “ Pbca ” structure of the (±)-[Co(en) 3 ]I 3 ·H 2 O was incorrect, and that it really crystallizes as a kryptoracemate in space group P 2 1 2 1 2 1 . Other equally interesting facts concerning the crystallization behavior of [Co(en) 3 ]I 3 ·H 2 O are detailed below, together with an explanation why P laton incorrectly selects, in this case, the space group Pbca instead of the correct choice, P 2 1 2 1 2 1 . As for the Flack parameter, (±)-[Co(en) 3 ]I 3 ·H 2 O provides an example long sought by Flack himself – a challenging case, differing from the norm. For that purpose, data sets (for the pure enantiomer and for the racemate) were collected at 100 K with R -factors of 4.24 and 2.82%, respectively, which are ideal for such a test. The fact that Pbca is unacceptable in this case is documented by the results of Second-Harmonic Generation experiments. CCDC nos: 1562401 for compound (I) and 1562403 for compound (II).