Active Energy Harvesting from Microbial Fuel Cells at the Maximum Power Point without Using Resistors

Microbial fuel cell (MFC) technology offers a sustainable approach to harvest electricity from biodegradable materials. Energy production from MFCs has been demonstrated using external resistors or charge pumps, but such methods can only dissipate energy through heat or receive electrons passively from the MFC without any controllability. This study developed a new approach and system that can actively extract energy from MFC reactors at any operating point without using any resistors, especially at the peak power point to maximize energy production. Results show that power harvesting from a recirculating-flow MFC can be well maintained by the maximum power point circuit (MPPC) at its peak power point, while a charge pump was not able to change operating point due to current limitation. Within 18-h test, the energy gained from the MPPC was 76.8 J, 76 times higher than the charge pump (1.0 J) that was commonly used in MFC studies. Both conditions resulted in similar organic removal, but the Coulombic efficiency obtained from the MPPC was 21 times higher than that of the charge pump. Different numbers of capacitors could be used in the MPPC for various energy storage requirements and power supply, and the energy conversion efficiency of the MPPC was further characterized to identify key factors for system improvement. This active energy harvesting approach provides a new perspective for energy harvesting that can maximize MFC energy generation and system controllability

Towards Synthetic Light-in-Flight

We present a method for the computational synthesis of a shaped, synthetic light pulse from interferometric measurements under CW illumination. The pulse can be manipulated to travel through a captured scene, demonstrating synthetic light-in-flight video

Experimentally Realizing Convolution Processing in the Photonic Synthetic Frequency Dimension

Convolution is an essential operation in signal and image processing and consumes most of the computing power in convolutional neural networks. Photonic convolution has the promise of addressing computational bottlenecks and outperforming electronic implementations. Performing photonic convolution in the synthetic frequency dimension, which harnesses the dynamics of light in the spectral degrees of freedom for photons, can lead to highly compact devices. Here we experimentally realize convolution operations in the synthetic frequency dimension. Using a modulated ring resonator, we synthesize arbitrary convolution kernels using a pre-determined modulation waveform with high accuracy. We demonstrate the convolution computation between input frequency combs and synthesized kernels. We also introduce the idea of an additive offset to broaden the kinds of kernels that can be implemented experimentally when the modulation strength is limited. Our work demonstrate the use of synthetic frequency dimension to efficiently encode data and implement computation tasks, leading to a compact and scalable photonic computation architecture

Additional file 5 of Analysis of differential membrane proteins related to matrix stiffness-mediated metformin resistance in hepatocellular carcinoma cells

Additional file 5: Figure S2. Six typical expression patterns reflect the increase degree of membrane proteins. iTRAQ tags 113, 114, 115, 116, 117 and 118 represent NC-L, NC-M, NC-H, Met-L, Met-M and Met-H, respectively

Additional file 1 of Analysis of differential membrane proteins related to matrix stiffness-mediated metformin resistance in hepatocellular carcinoma cells

Additional file 1: Table S1. Ingredients of polyacrylamide gel substrates with variable stiffness

Additional file 4 of Analysis of differential membrane proteins related to matrix stiffness-mediated metformin resistance in hepatocellular carcinoma cells

Additional file 4: Table S3. Differential membrane proteins and membrane associated proteins

Additional file 3 of Analysis of differential membrane proteins related to matrix stiffness-mediated metformin resistance in hepatocellular carcinoma cells

Additional file 3: Table S2. A list of all identified proteins

Additional file 2 of Analysis of differential membrane proteins related to matrix stiffness-mediated metformin resistance in hepatocellular carcinoma cells

Additional file 2: Figure S1. Efficiency and quality identification of membrane protein extraction. (A) The approximate location and range of membrane protein molecules performed by polyacrylamide gel electrophoresis with Coomassie brilliant blue staining. (B)(i, ii) Western blot were performed on the six groups of membrane proteins and cytoplasmic proteins

Additional file 6 of Analysis of differential membrane proteins related to matrix stiffness-mediated metformin resistance in hepatocellular carcinoma cells

Additional file 6: Figure S3. Six typical expression patterns reflect the decrease degree of membrane proteins. iTRAQ tags 113, 114, 115, 116, 117 and 118 represent NC-L, NC-M, NC-H, Met-L, Met-M and Met-H, respectively

Selective Catalytic Hydrodechlorination of 1,2-Dichloroethane to Ethylene over Ni–Rh Nanoparticle Catalysts Supported on γ‑Al₂O₃

Ni catalysts decorated with trace Rh supported on γ-Al2O3 were prepared by the co-impregnation method. To obtain the Ni–Rh nanoparticles with different nanostructures and chemical compositions, bimetallic catalysts with varied Ni/Rh molar ratios were prepared. For comparison, monometallic Ni/γ-Al2O3 and Rh/γ-Al2O3 catalysts were also prepared by the impregnation method. The selective gas phase catalytic hydrodechlorination of 1,2-dichloroethane to ethylene was used to evaluate catalytic performances of the catalysts. The catalysts were characterized by X-ray diffraction, N2 adsorption, X-ray photoelectron spectroscopy, H2 temperature-programmed reduction, transmission electron microscopy–energy-dispersive X-ray, and CO chemisorption. It was found that the introduction of Rh to Ni catalyst facilitated the generation of spillover hydrogen which could enhance the ability of the Ni catalyst for H2 activation. In bimetallic catalysts, there was an intimate interaction between Ni and Rh, and isolated Rh sites were formed due to the dilution effect of Ni. Accordingly, compared with the monometallic Ni catalyst for gas phase catalytic hydrodechlorination of 1,2-dichloroethane, the bimetallic Ni–Rh(800)/γ-Al2O3 catalyst exhibited markedly higher 1,2-dichloroethane conversion (37%) and comparable selectivity to ethylene (95%). The findings in this study indicate that Ni–Rh/γ-Al2O3 with trace Rh can be used as a promising catalyst for highly effective and selective catalytic hydrodechlorination of chlorinated hydrocarbons