Solid oxide fuel cells (SOFC) are highly efficient energy conversion device, but its high operating temperature (800∼1000 °C) restricts industrial commercialization. Reducing the operating temperature to <800 °C could broaden the selection of materials, improve the reliability of the system, and lower the operating cost. However, traditional perovskite cathode could not both attain the high catalytic activity towards the oxygen reduction reaction and good durability at medium and low temperature range. In contrast to the conventional perovskites, Ruddlesden–Popper perovskites exhibit fast oxygen surface exchange kinetic and excellent stability at medium and low temperatures, and excel both in oxide-conducting fuel cells (O-SOFC) and proton-conducting fuel cells (H-SOFC). In this paper, we try to relate its prominent performance with the crystal structure, main physical properties, and transport mechanism of oxygen ions and protons. We also summarize the current strategy in improving its application in O-SOFC and H-SOFC. Finally, we discuss the challenges and outlook for the future development of RP perovskites in SOFC.

Optical-matter interactions and photon scattering in a sub-wavelength space are of great interest in many applications, such as nanopore-based gene sequencing and molecule characterization. Previous studies show that spatial distribution features of the scattering photon states are highly sensitive to the dielectric and structural properties of the nanopore array and matter contained on or within them, as a result of the complex optical-matter interaction in a confined system. In this paper, we report a method for shape characterization of subwavelength nanowells using photon state spatial distribution spectra in the scattering near field. Far-field parametric images of the near-field optical scattering from sub-wavelength nanowell arrays on a SiN substrate were obtained experimentally. Finite-difference time-domain simulations were used to interpret the experimental results. The rich features of the parametric images originating from the interaction of the photons and the nanowells were analyzed to recover the size of the nanowells. Experiments on nanoholes modified with Shp2 proteins were also performed. Results show that the scattering distribution of modified nanoholes exhibits significant differences compared to empty nanoholes. This work highlights the potential of utilizing the photon status scattering of nanowells for molecular characterization or other virus detection applications.

The polarization states of scattered photons can be used to map or image the anisotropic features of a nanostructure. However, the scattering strength depends heavily on the refractivity contrast in the near field under measurement, which limits the imaging sensitivity for viral particles which have little refractivity contrast with their nano-ambientes. In this paper, we show the photon scattering signal strength can be magnified by introducing a more abrupt change of refractivity at the virus particle using antibody-conjugated gold nanoparticles (AuNPs), allowing the presence of such viruses to be detected. Using two different deep learning methods to minimize scattering noise, the photon states scattering signal of a AuNPs ligated virus is enhanced significantly compared to that of a bare virus particle. This is confirmed by Finite Difference Time Domain (FDTD) numerical simulations. The sensitivity of the polarization state scattering spectra from a virus-gold particle doublet is 5.4 times higher than that of a conventional microscope image.

The polarization parametric indirect microscopic imaging (PIMI) method, which employs a polarization-modulated incidence illumination and fitting the far-field variation of polarization states of scattered photons, is capable of direct identification of subdiffraction-scale structures and substances, such as virus particles. However, in the present strategy, the optical elements that collect the scattered photons are nearly fixed above the sample, making the collected information relatively limited, as the side-scattering photons are not fully utilized. To address this problem, we propose a multiperspective PIMI imaging method to maximize the collection of scattering photons from different spatial directions, which can obtain more information of optical anisotropy among particles. As a proof-of-concept study, virus detection using such a method is performed theoretically and experimentally. Results reveal that the virus particles can be detected and determined more distinctly thanks to the set of PIMI images from different spatial angles, showing notable superiority to the previous scheme, where only a plane PIMI image is derived from a fixed spatial direction. With the capability of acquiring more characteristics of the samples, the proposed multiperspective PIMI method can be applied in many fields, such as morphological characterization and biosensing.

Komagataeibacter xylinus (K. xylinus) has been used for a long time as one of the main cellulose producers among bacterium. In order to gain a better understanding of the physiological and biochemical mechanisms of cellulose production, an efficient and noninvasive visualization method is highly demanded to monitor the morphological changes of K. xylinus during each stage of its development. In this study, a polarization parametric indirect microscopic imaging (PIMI) technique was applied to image the morphology variations of K. xylinus. The optical field with precisely controlled polarization status was incident on the sample and far-field images of the sample were taken under different illumination polarization. In the calculated parametric images, sub-diffraction features related to the morphology details of the K. xylinus were visualized with high contrast and spatial resolution, which is typically irresolvable in conventional microscopic images. Finite-difference time-domain simulations verified the visualized scattering distributions in PIMI imaging results. We believe these pieces of evidence proved the possibility of developing a platform for characterizing the structures and morphological changes of cells in the cultivating process.