Automatic Identification of Crystal Structures and Interfaces via Artificial-Intelligence-based Electron Microscopy

Characterizing crystal structures and interfaces down to the atomic level is an important step for designing advanced materials. Modern electron microscopy routinely achieves atomic resolution and is capable to resolve complex arrangements of atoms with picometer precision. Here, we present AI-STEM, an automatic, artificial-intelligence based method, for accurately identifying key characteristics from atomic-resolution scanning transmission electron microscopy (STEM) images of polycrystalline materials. The method is based on a Bayesian convolutional neural network (BNN) that is trained only on simulated images. AI-STEM automatically and accurately identifies crystal structure, lattice orientation, and location of interface regions in synthetic and experimental images. The model is trained on cubic and hexagonal crystal structures, yielding classifications and uncertainty estimates, while no explicit information on structural patterns at the interfaces is included during training. This work combines principles from probabilistic modeling, deep learning, and information theory, enabling automatic analysis of experimental, atomic-resolution images.Comment: Code (https://github.com/AndreasLeitherer/ai4stem) and data (https://doi.org/10.5281/zenodo.7756516) are available for public use. The manuscript contains 32 pages (10 pages main text, 15 pages for Methods & References & 5 Figures & 1 Table, as well as 7 pages Supplementary Information), including 5 main figures and 6 supplementary figure

Electronic Structural Origin of the Catalytic Activity Trend of Transition Metals for Electrochemical Nitrogen Reduction

As an alternative to the conventional Haber–Bosch process for NH₃ synthesis that operates under harsh conditions, an electrochemical process has recently been pursued. Here, using a joint experiment–density functional calculation approach, we determine the activity trend of four transition metals (TMs) (Fe, Ru, Rh, and Pd) for N₂ reduction to NH₃: Fe > Ru > Pd > Rh, where the protonation step of *N₂ to form *N₂H (* indicates surface sites) is a potential determining step (PDS). The activity trend of the electrocatalysts is determined by the ability of the adsorbate (*N₂) over the catalyst surfaces to easily obtain electrons at the PDS with an assumption of a scaling relationship between the activation energy barrier and the free energy difference. In electronic structures, the ability can be estimated by the energy difference between the lowest unoccupied molecular orbital (LUMO) of the adsorbed N₂ on the TM surfaces and the fermi energy (E_F). For early TMs (e.g., Sc and Ti) where the PDS is *NH protonation reaction to form *NH₂, the activity of the TMs can be similarly explained with an electronic structural feature that is the energy difference between the LUMO of the *NH and the E_F. Based on the origin, we additionally consider 10 TMs (Ni, Cr, Mn, Co, Cu, Mo, Ag, W, Pt, and Au) and then determine the activity trend of the total 16 diverse TMs for NH₃ synthesis. We expect that this work could pave the way to novel alloy catalysts with a high activity for electrochemical NH₃ synthesis

Dissimilar anisotropy of electron versus hole bulk transport in anatase TiO2: Implications for photocatalysis

Recent studies on crystal facet manipulation of anatase TiO2 in photocatalysis have revealed that reduction and oxidation reactions preferably occur on (100)/(101) and (001) facets, respectively; however, a fundamental understanding of their origin is lacking. Here, as a result of first-principles calculations, we suggest that a dissimilar trend in the anisotropy of electron vs hole bulk transport in anatase TiO2 can be a dominant underlying mechanism for the difference in photochemical activity. Photoexcited electrons and holes are driven to different facets, i.e., electrons on (100)/(101) and holes on (001), leading to the observed preference for either reduction or oxidation. This trend of electrons vs holes found in pure TiO2 applies even for cases where a variety of dopants or defects is introduced.clos

Welfare Genome Project: A Participatory Korean Personal Genome Project With Free Health Check-Up and Genetic Report Followed by Counseling.

The Welfare Genome Project (WGP) provided 1,000 healthy Korean volunteers with detailed genetic and health reports to test the social perception of integrating personal genetic and healthcare data at a large-scale. WGP was launched in 2016 in the Ulsan Metropolitan City as the first large-scale genome project with public participation in Korea. The project produced a set of genetic materials, genotype information, clinical data, and lifestyle survey answers from participants aged 20-96. As compensation, the participants received a free general health check-up on 110 clinical traits, accompanied by a genetic report of their genotypes followed by genetic counseling. In a follow-up survey, 91.0% of the participants indicated that their genetic reports motivated them to improve their health. Overall, WGP expanded not only the general awareness of genomics, DNA sequencing technologies, bioinformatics, and bioethics regulations among all the parties involved, but also the general public's understanding of how genome projects can indirectly benefit their health and lifestyle management. WGP established a data construction framework for not only scientific research but also the welfare of participants. In the future, the WGP framework can help lay the groundwork for a new personalized healthcare system that is seamlessly integrated with existing public medical infrastructure

A test of the submentalizing hypothesis : apes' performance in a false belief task inanimate control

Financial support came from Ministry of Education, Culture, Sports, Science and Technology (K-CONNEX to FK), Japan Society for Promotion of Science (KAKENHI 26885040, 16K21108 to FK), JSPS (KAKENHI 26245069, 24000001 to SH), and European Research Council (Synergy grant 609819 SOMICS to JC).Much debate concerns whether any nonhuman animals share with humans the ability to infer others' mental states, such as desires and beliefs. In a recent eye-tracking false-belief task, we showed that great apes correctly anticipated that a human actor would search for a goal object where he had last seen it, even though the apes themselves knew that it was no longer there. In response, Heyes proposed that apes' looking behavior was guided not by social cognitive mechanisms but rather domain-general cueing effects, and suggested the use of inanimate controls to test this alternative submentalizing hypothesis. In the present study, we implemented the suggested inanimate control of our previous false-belief task. Apes attended well to key events but showed markedly fewer anticipatory looks and no significant tendency to look to the correct location. We thus found no evidence that submentalizing was responsible for apes' anticipatory looks in our false-belief task.Publisher PDFPeer reviewe

Polygenic risk score validation using Korean genomes of 265 early-onset acute myocardial infarction patients and 636 healthy controls

Background The polygenic risk score (PRS) developed for coronary artery disease (CAD) is known to be effective for classifying patients with CAD and predicting subsequent events. However, the PRS was developed mainly based on the analysis of Caucasian genomes and has not been validated for East Asians. We aimed to evaluate the PRS in the genomes of Korean early-onset AMI patients (n = 265, age <= 50 years) following PCI and controls (n = 636) to examine whether the PRS improves risk prediction beyond conventional risk factors. Results The odds ratio of the PRS was 1.83 (95% confidence interval [CI]: 1.69-1.99) for early-onset AMI patients compared with the controls. For the classification of patients, the area under the curve (AUC) for the combined model with the six conventional risk factors (diabetes mellitus, family history of CAD, hypertension, body mass index, hypercholesterolemia, and current smoking) and PRS was 0.92 (95% CI: 0.90-0.94) while that for the six conventional risk factors was 0.91 (95% CI: 0.85-0.93). Although the AUC for PRS alone was 0.65 (95% CI: 0.61-0.69), adding the PRS to the six conventional risk factors significantly improved the accuracy of the prediction model (P = 0.015). Patients with the upper 50% of PRS showed a higher frequency of repeat revascularization (hazard ratio = 2.19, 95% CI: 1.47-3.26) than the others. Conclusions The PRS using 265 early-onset AMI genomes showed improvement in the identification of patients in the Korean population and showed potential for genomic screening in early life to complement conventional risk prediction