11Metal nanoclusters consist of a few to few hundreds of atoms, and exhibit attractive molecular 12 properties such as ultrasmall size, discrete energy levels and strong fluorescence. Although 13 patterning of these clusters down to the microscale or nanoscale could lead to 14 applications such as high-density data storage, it has been reported only for inorganic 15matrices. Here we demonstrate the first submicron-scale mask-free patterning of fluorescent 16 silver nanoclusters in an organic matrix. The nanoclusters were produced by direct 17 laser writing in poly(methacrylic acid) thin films, and exhibit a broadband emission at visible 18 wavelengths with photostability that is superior to Rhodamine 6G dye. This fabrication 19 method could open new opportunities for applications in nanophotonics like imaging, 20 labeling, and metal ion sensing. We foresee that this method can be further applied to prepare 21 other metal nanoclusters embedded in compositionally different polymer matrices. 22 KEYWORDS 24Optical lithography, metal nanoclusters, photoluminescence, photobleaching, photostability, 25 polymer 26

Positron annihilation spectroscopy was used to study GaAsN/GaAs epilayers. GaAsN layers were found to contain Ga vacancies in defect complexes. The density of the vacancy complexes increases rapidly to the order of 10 18 cm Ϫ3 with increasing N composition and decreases after annealing at 700°C. The anticorrelation of the vacancy concentration and the integrated photoluminescence intensity suggests that the Ga vacancy complexes act as nonradiative recombination centers.

A central research area in nonlinear science is the study of instabilities that drive extreme events. Unfortunately, techniques for measuring such phenomena often provide only partial characterisation. For example, real-time studies of instabilities in nonlinear optics frequently use only spectral data, limiting knowledge of associated temporal properties. Here, we show how machine learning can overcome this restriction to study time-domain properties of optical fibre modulation instability based only on spectral intensity measurements. Specifically, a supervised neural network is trained to correlate the spectral and temporal properties of modulation instability using simulations, and then applied to analyse high dynamic range experimental spectra to yield the probability distribution for the highest temporal peaks in the instability field. We also use unsupervised learning to classify noisy modulation instability spectra into subsets associated with distinct temporal dynamic structures. These results open novel perspectives in all systems exhibiting instability where direct time-domain observations are difficult.

A quantitative and simultaneous measurement of K, KCl, and KOH vapors from a burning fuel sample combusted in a single particle reactor was performed using collinear photofragmentation and atomic absorption spectroscopy (CPFAAS) with a time resolution of 0.2 s. The previously presented CPFAAS technique was extended in this work to cover two consecutive fragmentation pulses for the photofragmentation of KCl and KOH. The spectral overlapping of the fragmentation spectra of KCl and KOH is discussed, and a linear equation system for the correction of the spectral interference is introduced. The detection limits for KCl, KOH, and K with the presented measurement arrangement and with 1 cm sample length were 0.5, 0.1, and 0.001 parts per million, respectively. The experimental setup was applied to analyze K, KCl, and KOH release from 10 mg spruce bark samples combusted at the temperatures of 850, 950, and 1050 °C with 10% of O2. The combustion experiments provided data on the form of K vapors and their release during different combustion phases and at different temperatures. The measured release histories agreed with earlier studies of K release. The simultaneous direct measurement of atomic K, KCl, and KOH will help in the impact of both the form of K in the biomass and fuel variables, such as particle size, on the release of K from biomass fuels.

An ultrasonic particle concentrator based on a standing-wave hemispherical resonator is combined with confocal laser-scanning fluorescence detection. The goal is to perform ultrasensitive biomedical analysis by concentration of biologically active microspheres. The standing-wave resonator consists of a 4 MHz focusing ultrasonic transducer combined with the optically transparent plastic bottom of a disposable 96-well microplate platform. The ultrasonic particle concentrator collects suspended microspheres into dense, single-layer aggregates at well-defined positions in the sample vessel of the microplate, and the fluorescence from the aggregates is detected by the confocal laser-scanning system. The biochemical properties of the system are investigated using a microsphere-based human thyroid stimulating hormone assay.