Highly active, structurally disordered CoFe2O4/CoO electrocatalysts are synthesized by pulsed laser fragmentation in liquid (PLFL) of a commercial CoFe2O4 powder dispersed in water. A partial transformation of the CoFe2O4 educt to CoO is observed and proposed to be a thermal decomposition process induced by the picosecond pulsed laser irradiation. The overpotential in the OER in aqueous alkaline media at 10 mA cm−2 is reduced by 23% compared to the educt down to 0.32 V with a Tafel slope of 71 mV dec−1. Importantly, the catalytic activity is systematically adjustable by the number of PLFL treatment cycles. The occurrence of thermal melting and decomposition during one PLFL cycle is verified by modelling the laser beam energy distribution within the irradiated colloid volume and comparing the by single particles absorbed part to threshold energies. Thermal decomposition leads to a massive reduction in particle size and crystal transformations towards crystalline CoO and amorphous CoFe2O4. Subsequently, thermal melting forms multi-phase spherical and network-like particles. Additionally, Fe-based layered double hydroxides at higher process cycle repetitions emerge as a byproduct. The results show that PLFL is a promising method that allows modification of the structural order in oxides and thus access to catalytically interesting materials.

Like other 2D materials, the boron-based borophene exhibits interesting structural and electronic properties. While borophene is typically prepared by molecular beam epitaxy, we report here on an alternative way of synthesizing large single-phase borophene domains by segregation-enhanced epitaxy. X-ray photoelectron spectroscopy shows that borazine dosing at 1100 °C onto Ir(111) yields a boron-rich surface without traces of nitrogen. At high temperatures, the borazine thermally decomposes, nitrogen desorbs, and boron diffuses into the substrate. Using time-of-flight secondary ion mass spectrometry, we show that during cooldown the subsurface boron segregates back to the surface where it forms borophene. In this case, electron diffraction reveals a (6 × 2) reconstructed borophene χ6-polymorph, and scanning tunneling spectroscopy suggests a Dirac-like behavior. Studying the kinetics of borophene formation in low energy electron microscopy shows that surface steps are bunched during the borophene formation, resulting in elongated and extended borophene domains with exceptional structural order.

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Free-electron lasers providing ultra-short high-brightness pulses of X-ray radiation have great potential for a wide impact on science, and are a critical element for unravelling the structural dynamics of matter. To fully harness this potential, we must accurately know the X-ray properties: intensity, spectrum and temporal profile. Owing to the inherent fluctuations in free-electron lasers, this mandates a full characterization of the properties for each and every pulse. While diagnostics of these properties exist, they are often invasive and many cannot operate at a high-repetition rate. Here, we present a technique for circumventing this limitation. Employing a machine learning strategy, we can accurately predict X-ray properties for every shot using only parameters that are easily recorded at high-repetition rate, by training a model on a small set of fully diagnosed pulses. This opens the door to fully realizing the promise of next-generation high-repetition rate X-ray lasers.