Asymmetric Chiral-at-Rhodium Catalysis Driven by Visible Light or Electricity

Driving asymmetric catalysis with visible light or electricity is of significant value because they represent ‘green’ and sustainable methods to synthesize non-racemic chiral molecules and in addition offer ample opportunities for chemists to discover new mechanistic scenarios and invent previously unknown transformations. However, steering the reaction course of photo- and/or electrochemically generated reactive intermediates in a stereocontrolled and catalytic fashion is very challenging. This thesis presents novel applications of previously in the Meggers group developed chiral-at-metal rhodium complexes to the areas of asymmetric photocatalysis and asymmetric electrosynthesis. 1) A bis-cyclometalated chiral-at-metal rhodium complex (designated as RhS) in combination with the photoredox catalyst [Ru(bpy)3](PF6)2 enables visible-light-activated asymmetric α-amination and α-alkylation of 2-acyl imidazoles with aryl azides or α-diazo carboxylic esters as radical precursors, respectively (Chapter 3.1). As the first utilization of these reagents for photoinduced asymmetric catalysis, this novel proton- and redox-neutral transformations feature the advantage of leaving molecular N2 as the sole by-product and provide yields of up to 99% as well as excellent enantioselectivities of up to >99% ee with broad functional group compatibility. 2) A bis-cyclometalated chiral-at-metal rhodium complex (designated as RhO) is demonstrated to catalyze stereocontrolled chemistry of photo-generated radicals and at the same time an enantioselective sulfonyl radical addition to alkenes (Chapter 3.2). Specifically, employing Hantzsch ester as photoredox mediator, rhodium bound β-enolate carbon-centered radicals are generated by a selective photoinduced single electron reduction and then trapped by allyl sulfones in a highly stereocontrolled fashion, providing radical allylation products with up to 97% ee. The hereby formed sulfonyl radicals are utilized through an enantioselective radical addition to form enantioenriched sulfones, which minimizes waste generation. 3) A simple and robust catalysis scheme that only relies on a single bis-cyclometalated rhodium catalyst (RhS) is introduced to achieve the stereocontrol of bond forming reactions directly from an electronically excited state. This is showcased by an intermolecular [2+2] photocycloaddition of enones with alkenes, which provides a wide range of cyclobutanes with up to >99% ee and up to >20:1 d.r. (Chapter 3.3). The catalyst/substrate complexation enhances visible-light-absorption, achieves selective direct photoexcitation, and enables stereocontrolled direct bond formation from the photoexcited state. All reactive intermediates remain bound to the chiral catalyst thereby providing a robust catalytic scheme (no exclusion of air necessary) with excellent stereoinduction. This strategy is further applied to a previously elusive visible-light-induced [2+3] photocycloaddition of acceptor-substituted alkenes with vinyl azides (Chapter 3.4). A wide range of complex 1-pyrrolines are obtained as single diastereoisomers and with up to >99% ee using a simple reaction setup and mild reaction conditions. This work expands the scope of stereocontrolled direct bond formation from photoexcited states which was previously limited to [2+2] photocycloadditions. 4) The chiral-at-metal complex RhS is shown to catalyze visible-light-activated catalytic asymmetric [3+2] photocycloadditions between acyl cyclopropanes and alkenes or alkynes, which provide access to cyclopentanes and cyclopentenes, respectively, in 63-99% yields and with excellent enantioselectivities of up to >99% ee (Chapter 3.5). Coordination of the cyclopropane with the chiral catalyst generates the visible-light-absorbing complex, lowers the reduction potential of the cyclopropane, and provides the asymmetric induction and overall stereocontrol. Enabled by a mild single electron transfer reduction of directly photoexcited catalyst/substrate complexes, the scope of asymmetric photocycloadditions is extended to simple mono-acceptor-substituted cyclopropanes with the synthesis of previously inaccessible enantioenhanced cyclopentane and cyclopentene derivatives. 5) A versatile electricity driven chiral-at-rhodium Lewis acid catalysis is disclosed (Chapter 3.6). Powered by an electric current, the oxidative cross coupling of 2-acyl imidazoles with silyl enol ethers provides a sustainable avenue to synthetically useful non-racemic 1,4-dicarbonyls, including products bearing all-carbon quaternary stereocenters. A chiral-at-rhodium complex (RhS or a sterically more demanding derivative) activates a substrate towards facile anodic oxidation by raising the highest occupied molecular orbital upon enolate formation, which enables mild redox conditions, high chemo- and enantioselectivities (up to >99% ee), and a broad substrate scope. This thesis demonstrates the robustness and versatility of bis-cyclometalated rhodium-based Lewis acids by developing several mechanistically diverse and synthetically attractive asymmetric catalysis schemes. These chiral-at-rhodium Lewis acids are among the most powerful catalysts to address the long-standing challenge of stereocontrol in photochemical and electrochemical reactions

TRPV4, TRPC1, and TRPP2 assemble to form a flow-sensitive heteromeric channel

Transient receptor potential (TRP) channels, a superfamily of ion channels, can be divided into 7 subfamilies, including TRPV, TRPC, TRPP, and 4 others. Functional TRP channels are tetrameric complexes consisting of 4 pore-forming subunits. The purpose of this study was to explore the heteromerization of TRP subunits crossing different TRP subfamilies. Two-step coimmunoprecipitation (co-IP) and fluorescence resonance energy transfer (FRET) were used to determine the interaction of the different TRP subunits. Patch-clamp and cytosolic Ca2+ measurements were used to determine the functional role of the ion channels in flow conditions. The analysis demonstrated the formation of a heteromeric TRPV4-C1-P2 complex in primary cultured rat mesenteric artery endothelial cells (MAECs) and HEK293 cells that were cotransfected with TRPV4, TRPC1, and TRPP2. In functional experiments, pore-dead mutants for each of these 3 TRP isoforms nearly abolished the flow-induced cation currents and Ca2+ increase, suggesting that all 3 TRPs contribute to the ion permeation pore of the channels. We identified the first heteromeric TRP channels composed of subunits from 3 different TRP subfamilies. Functionally, this heteromeric TRPV4- C1-P2 channel mediates the flow-induced Ca2+ increase in native vascular endothelial cells.-Du, J., Ma, X., Shen, B., Huang, Y., Birnbaumer, L., Yao, X. TRPV4, TRPC1, and TRPP2 assemble to form a flowsensitive heteromeric channel.Fil: Du, Juan. Chinese University Of Hong Kong; Hong Kong. Anhui Medical University; ChinaFil: Ma, Xin. Chinese University Of Hong Kong; Hong KongFil: Shen, Bing. Chinese University Of Hong Kong; Hong Kong. Anhui Medical University; ChinaFil: Huang, Yu. Chinese University Of Hong Kong; Hong KongFil: Birnbaumer, Lutz. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. National Institutes of Health; Estados UnidosFil: Yao, Xiaoqiang. Chinese University Of Hong Kong; Hong Kon

Design and Control of the "TransBoat": A Transformable Unmanned Surface Vehicle for Overwater Construction

This paper presents the TransBoat, a novel omnidirectional unmanned surface vehicle (USV) with a magnetbased docking system for overwater construction with wave disturbances. This is the first such USV that can build overwater structures by transporting modules. The TransBoat incorporates two features designed to reject wave disturbances. First, the TransBoat's expandable body structure can actively transform from a mono-hull into a multi-hull for stabilization in turbulent environments by extending its four outrigger hulls. Second, a real-time nonlinear model predictive control (NMPC) scheme is proposed for all shapes of the TransBoat to enhance its maneuverability and resist disturbance to its movement, based on a nonlinear dynamic model. An experimental approach is proposed to identify the parameters of the dynamic model, and a subsequent trajectory tracking test validates the dynamics, NMPC controller and system mobility. Further, docking experiments identify improved performance in the expanded form of the TransBoat compared with the contracted form, including an increased success rate (of ~ 10%) and reduced docking time (of ~ 40 s on average). Finally, a bridge construction test verifies our system design and the NMPC control method

Research on Low Frequency Noise Caused by Beat Vibration of Rotary Compressor

The discontinuity of low frequency noise caused by beat frequency vibration of rotary compressor is studied in this paper. Based on beat frequency theoretical analysis, a finite element model is established to simulate the electromagnetic harmonics. And the contributions of various compressor motor designs to beat frequency vibration are investigated, so the motor optimization design schemes are obtained. The tests show that the method proposed in the paper is effective to improve low frequency noise of the compressor

Vision Transformer with Super Token Sampling

Vision transformer has achieved impressive performance for many vision tasks. However, it may suffer from high redundancy in capturing local features for shallow layers. Local self-attention or early-stage convolutions are thus utilized, which sacrifice the capacity to capture long-range dependency. A challenge then arises: can we access efficient and effective global context modeling at the early stages of a neural network? To address this issue, we draw inspiration from the design of superpixels, which reduces the number of image primitives in subsequent processing, and introduce super tokens into vision transformer. Super tokens attempt to provide a semantically meaningful tessellation of visual content, thus reducing the token number in self-attention as well as preserving global modeling. Specifically, we propose a simple yet strong super token attention (STA) mechanism with three steps: the first samples super tokens from visual tokens via sparse association learning, the second performs self-attention on super tokens, and the last maps them back to the original token space. STA decomposes vanilla global attention into multiplications of a sparse association map and a low-dimensional attention, leading to high efficiency in capturing global dependencies. Based on STA, we develop a hierarchical vision transformer. Extensive experiments demonstrate its strong performance on various vision tasks. In particular, without any extra training data or label, it achieves 86.4% top-1 accuracy on ImageNet-1K with less than 100M parameters. It also achieves 53.9 box AP and 46.8 mask AP on the COCO detection task, and 51.9 mIOU on the ADE20K semantic segmentation task. Code will be released at https://github.com/hhb072/SViT.Comment: 12 pages, 4 figures, 8 table

SOSR: Source-Free Image Super-Resolution with Wavelet Augmentation Transformer

Real-world images taken by different cameras with different degradation kernels often result in a cross-device domain gap in image super-resolution. A prevalent attempt to this issue is unsupervised domain adaptation (UDA) that needs to access source data. Considering privacy policies or transmission restrictions of data in many practical applications, we propose a SOurce-free image Super-Resolution framework (SOSR) to address this issue, i.e., adapt a model pre-trained on labeled source data to a target domain with only unlabeled target data. SOSR leverages the source model to generate refined pseudo-labels for teacher-student learning. To better utilize the pseudo-labels, this paper proposes a novel wavelet-based augmentation method, named Wavelet Augmentation Transformer (WAT), which can be flexibly incorporated with existing networks, to implicitly produce useful augmented data. WAT learns low-frequency information of varying levels across diverse samples, which is aggregated efficiently via deformable attention. Furthermore, an uncertainty-aware self-training mechanism is proposed to improve the accuracy of pseudo-labels, with inaccurate predictions being rectified by uncertainty estimation. To acquire better SR results and avoid overfitting pseudo-labels, several regularization losses are proposed to constrain the frequency information between target LR and SR images. Experiments show that without accessing source data, SOSR achieves superior results to the state-of-the-art UDA methods.Comment: 15 pages, 9 figures, 10 table