This study reports for the first time the use of a red-emitting AIEgen, i.e. TPE-AC, for the realization of efficient luminescent solar concentrators (LSCs) based on poly(methyl methacrylate) (PMMA) and polycarbonate (PC) thin films (25 ± 5 μm). TPE-AC is an AIEgen with D–A features that absorbs visible light in the range between 400 and 550 nm and emits fluorescence peaked at 600–620 nm, with a maximum quantum yield (QY) of 50% when dispersed (0.1–1.5 wt%) in PMMA and PC matrices. QY and lifetime investigations demonstrated that fluorescence quenching occurred with varying the TPE-AC concentration, even if the optical features were still significant even at the highest fluorophore content. Study of the LSCs’ performances yielded worthy optical efficiencies of 6.7% for the TPE-AC/PC systems due to their superior light harvesting features and the compatibility of the AIEgen within the PC matrix

High dielectric contrast polymer dielectric mirrors are used to recycle non-absorbed photons in organic luminescent solar concentrators. A 10% increase in the concentrator optical efficiency is found and retained upon doubling its size paving the way to lightweight and cheap building integrated photovoltaic systems.

We present a processing method, based on the multivariate curve resolution approach (MCR), to denoise 2D solid-state NMR spectra, yielding a substantial S/N ratio increase while preserving the lineshapes and relative signal intensities. These spectral features are particularly important in the quantification of silicon species, where sensitivity is limited by the low natural abundance of the 29 Si nuclei and by the dilution of the intrinsic protons of silica, but can be of interest also when dealing with other intermediate-to-low receptivity nuclei. This method also offers the possibility of coprocessing multiple 2D spectra that have the signals at the same frequencies but with different intensities (e.g.: as a result of a variation in the mixing time). The processing can be carried out on the time-domain data, thus preserving the possibility of applying further processing to the data. As a demonstration, we have applied Cadzow denoising on the MCR-processed FIDs, achieving a further increase in the S/N ratio and more effective denoising also on the transients at longer indirect evolution times. We have applied the combined denoising on a set of experimental data from a lysozyme–silica composite.