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A case study of catalytic carbon-carbon σ-bond homolysis is presented. The coordination of a redox-active Lewis acid catalyst reduces the bond-dissociation free energies of adjacent carbon-carbon σ-bonds, and this complexation-induced bond-weakening is used to effect reversible carbon-carbon bond homolysis. Stereochemical isomerization of 1,2-disubstituted cyclopropanes was investigated as a model reaction with a ruthenium (III/II) redox couple adopted for bond weakening. Results from our mechanistic investigation into the stereospecificity of the isomerization reaction are consistent with selective complexation-induced carbon-carbon bond homolysis. The ΔG‡ of catalyzed and uncatalyzed reactions were estimated to be 14.4 and 40.0 kcal/mol, respectively with the computational method, (U)PBE0-D3/def2-TZVPP-SMD(toluene)//(U)B3LYP-D3/def2-SVP. We report this work as the first catalytic example where the complexation-induced bond-weakening effect is quantified through transition state analysis.

N-heterocyclic carbenes (NHCs) have been widely utilized for the formation of self-assembled monolayers (SAMs) on various surfaces. The main methodologies for preparation of NHCs-based SAMs either requires inert atmosphere and strong base for deprotonation of imidazolium precursors or the use of specifically-synthesized precursors such as NHC(H)[HCO3] salts or NHC-CO2 adducts. Herein, we demonstrate an electrochemical approach for surface-anchoring of NHCs which overcomes the need for dry environment, addition of exogenous strong base or restricting synthetic steps. In the electrochemical deposition, water reduction reaction is used to generate high concentration of hydroxide ions in proximity to a metal electrode. Imidazolium cations were deprotonated by hydroxide ions, leading to carbenes formation that self-assembled on the electrode's surface. SAMs of NO2-functionalized NHCs and dimethyl-benzimidazole were electrochemically deposited on Au films. SAMs of NHCs were also electrochemically deposited on Pt, Pd and Ag films, demonstrating the wide metal scope of this deposition technique.

Difluoromethylene-containing compounds have attracted substantial research interest over the past decades for their ability to mimic biological functions of traditional functional groups while providing a wide variety of pharmacological benefits bestowed by the C-F bond. We report a novel strategy to access RCF2Br-containing heterocycles by regio- and enantioselective bromocyclization of difluoroalkenes enabled by chiral anion phase-transfer catalysis. The utility of this methodology was highlighted through a synthesis of an analogue of efavirenz, a drug used for treating HIV. Additionally, the synthetic versatility of the CF2Br intermediates was showcased through functionalization to a variety of enantioenriched α,α-difluoromethylene-containing products.

Herein, we report on the photoredox-initiated gold-mediated C(sp2)-CF3 and C(sp2)-N coupling reactions. By adopting gold as a platform for probing metallaphotoredox catalysis, we demonstrate that cationic gold(III) complexes are the key intermediates of the C-C and C-N coupling reactions. The high-valent gold(III) intermediates are accessed by virtue of photoredox catalysis through a radical chain process. In addition, the bond-forming step of the coupling reactions is the reductive elimination from cationic gold(III) intermediates, which is supported by isolation and crystallographic characterization of key Au(III) intermediates.

Catalytic nanoparticles are heterogeneous in their nature and even within the simplest particle various surface sites exist and influence the catalytic reactivity. Thus, detailed chemical information at the nanoscale is essential for understanding how surface properties and reaction conditions direct the reactivity of different surface sites of catalytic nanoparticles. In this work, hydroxyl-functionalized N-heterocyclic carbene molecules (NHCs) were anchored to the surface of Pt particles and utilized as chemical markers to detect reactivity variations between different surface sites under liquid and gas phase oxidizing conditions. Differences in the chemical reactivity of surface-anchored NHCs were identified using synchrotron-radiation-based infrared nanospectroscopy with a spatial resolution of 20 nanometers. By conducting IR nanospectroscopy measurements, along with complementary spatially averaged IR and X-ray spectroscopy measurements, we identified that enhanced reactivity occurred on the particles periphery under both gas and liquid phase oxidizing conditions. Under gas phase reaction conditions the NHCs hydroxyl functional groups underwent preferential oxidization to the acid along the perimeter of the particle. Exposure of the sample to harsher, liquid phase oxidizing conditions induced modification of the NHCs, which was mostly identified at the particles periphery. Analysis of X-ray absorption spectroscopy measurements revealed that exposure of the sample to oxidizing conditions induced aromatization of the NHCs, presumably due to oxidative dehydrogenation reaction, along with reorientation of the NHCs from perpendicular to parallel to the Pt surface. These results, based on single particle measurements, demonstrate the high reactivity of surface sites that are located at the nanoparticles periphery and the influence of reaction conditions on site-dependent reactivity.

The efficient operation and interaction of autonomous robots play crucial roles in various fields, e.g., security, environmental monitoring, and disaster response. For these purposes, processing large volumes of sensor data and sharing data between robots is essential; however, processing such large data in an on-device environment for robots results in substantial computational resource demands, causing high battery consumption and heat issues. Thus, this study addresses challenges related to processing large volumes of sensor data and the lack of dynamic object information sharing among autonomous robots and other mobility systems. To this end, we propose an Edge-Driving Robotics Platform (EDRP) and a Local Dynamic Map Platform (LDMP) based on 5G mobile edge computing and Kubernetes. The proposed EDRP implements the functions of autonomous robots based on a microservice architecture and offloads these functions to an edge cloud computing environment. The LDMP collects and shares information about dynamic objects based on the ETSI TR 103 324 standard, ensuring cooperation among robots in a cluster and compatibility with various Cooperative-Intelligent Transport System (C-ITS) components. The feasibility of operating a large-scale autonomous robot offloading system was verified in experimental scenarios involving robot autonomy, dynamic object collection, and distribution by integrating real-world robots with an edge computing–based offloading platform. Experimental results confirmed the potential of dynamic object collection and dynamic object information sharing with C-ITS environment components based on LDMP. [ABSTRACT FROM AUTHOR]

Since initial reports, cross-coupling technologies employing photoredox catalysts to access novel reactivity have developed with increasing pace. In this Outlook, prominent examples from the recent literature are organized on the basis of the elementary transformation enabled by photoredox catalysis and are discussed in the context of relevant historical precedent in stoichiometric organometallic chemistry. This treatment allows mechanistic similarities inherent to odd-electron transition metal reactivity to be generalized to a set of lessons for future reaction development.

A dual photoredox and gold-catalysed cross-coupling reaction of alkynyltrimethylsilanes and aryldiazonium tetrafluoroborates is described. The reaction proceeds through visible-light mediated oxidative addition of aryldiazoniums, transmetalation of alkynyltrimethylsilanes and aryl-alkynyl reductive elimination. Exclusive selectivity for silyl-substituted alkynes is observed, with no reactivity observed for terminal alkynes.

A dual photoredox and gold-catalysed cross-coupling reaction of alkynyltrimethylsilanes and aryldiazonium tetrafluoroborates is described. The reaction proceeds through visible-light mediated oxidative addition of aryldiazoniums, transmetalation of alkynyltrimethylsilanes and aryl-alkynyl reductive elimination. Exclusive selectivity for silyl-substituted alkynes is observed, with no reactivity observed for terminal alkynes.

This study critically examined the effectiveness of English medium instruction (EMI) policy within the context of Korean higher education, putting a special focus on its implementation strategy. The data for this study were mainly drawn from student opinion surveys and focus group interviews conducted by the CTL (Center for Teaching and Learning) at KU. The research teams also carried out supplementary interviews with both professors and students. The results indicate that, although the EMI policy seems to have produced, in general, positive outcomes (i.e., with the overall satisfaction level with EMI or its overall effectiveness in improving students' English proficiency), the compulsory enforcement of EMI without regard to students'/instructors' language proficiency, the lack of a much-needed support system and appropriate instructors to conduct EMI classes, and the unilateral implementation of EMI across academic disciplines have brought about a number of side effects. Based on these findings, the study recommends for future EMI policy implementation (1) a more flexible approach, considering students' language proficiency and career plans and the characteristics of various academic disciplines and (2) more thorough preparation to implement the EMI policy (i.e., examination of the human and financial resources available for the institution concerned).

Background: Considering the limited accessibility of amyloid position emission tomography (PET) in patients with dementia, we proposed a deep learning (DL)-based amyloid PET positivity classification model from PET images with 2-deoxy-2-[fluorine-18]fluoro-D-glucose (2-[18F]FDG). Methods: We used 2-[18F]FDG PET datasets from the Alzheimer's Disease Neuroimaging Initiative and Korean Brain Aging Study for the Early diagnosis and prediction of Alzheimer's disease for model development. Moreover, we used an independent dataset from another hospital. A 2.5-D deep learning architecture was constructed using 291 submodules and three axes images as the input. We conducted the voxel-wise analysis to assess the regions with substantial differences in glucose metabolism between the amyloid PET-positive and PET-negative participants. This facilitated an understanding of the deep model classification. In addition, we compared these regions with the classification probability from the submodules. Results: There were 686 out of 1433 (47.9%) and 50 out of 100 (50%) amyloid PET-positive participants in the training and internal validation datasets and the external validation datasets, respectively. With 50 times iterations of model training and validation, the model achieved an AUC of 0.811 (95% confidence interval (CI) of 0.803–0.819) and 0.798 (95% CI, 0.789–0.807) on the internal and external validation datasets, respectively. The area under the curve (AUC) was 0.860 when tested with the model with the highest value (0.864) on the external validation dataset. Moreover, it had 75.0% accuracy, 76.0% sensitivity, 74.0% specificity, and 75.0% F1-score. We found an overlap between the regions within the default mode network, thus generating high classification values. Conclusion: The proposed model based on the 2-[18F]FDG PET imaging data and a DL framework might successfully classify amyloid PET positivity in clinical practice, without performing amyloid PET, which have limited accessibility. [ABSTRACT FROM AUTHOR]