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Catalysis stands as an indispensable cornerstone of modern society, underpinning the production of over 80% of manufactured goods and driving over 90% of industrial chemical processes. As the demand for more efficient and sustainable processes grows, better catalysts are needed. Understanding the working principles of catalysts is key, and over the last 50 years, surface-enhanced Raman Spectroscopy (SERS) has become essential. Discovered in 1974, SERS has evolved into a mature and powerful analytical tool, transforming the way in which we detect molecules across disciplines. In catalysis, SERS has enabled insights into dynamic surface phenomena, facilitating the monitoring of the catalystmore » structure, adsorbate interactions, and reaction kinetics at very high spatial and temporal resolutions. This review explores the achievements as well as the future potential of SERS in the field of catalysis and energy conversion, thereby highlighting its role in advancing these critical areas of research.« less

The application of two-photon excitation (TPE) in the study of light-responsive materials holds immense potential due to its deeper penetration and reduced photodamage. Despite these benefits, TPE has been underutilised in the investigation of the photoinduced spin crossover (SCO) phenomenon. Here, we employ TPE to delve into the out-of-equilibrium dynamics of a SCO Fe^II dimer of the form [Fe^II(HL)₂]₂(BF₄)₄·2MeCN (HL = 3,5-bis{6-(2,2'-bipyridyl)}pyrazole). Optical transient absorption (OTA) spectroscopy in solution proves that the same dynamics take place under both one-photon excitation (OPE) and TPE. The results show the emergence of the photoinduced high spin state in less than 2 ps andmore » with a lifetime of 147 ns. Time-resolved photocrystallography (TRXRD) reveals a single molecular reorganisation within the first 500 ps following TPE. Additionally, variable temperature single crystal X-ray diffraction (VTSCXRD) and magnetic susceptibility measurements confirm that the thermal transition is silenced by the solvent. While the results of the OTA and TRXRD utilising TPE are intriguing, the high pump fluencies required to excite enough metal centres to the high spin state may impair its practical application. Nonetheless, this study sheds light on the potential of TPE for the investigation of the out-of-equilibrium dynamics of SCO complexes.« less

Nanoparticles, exhibiting functionally relevant structural heterogeneity, are at the forefront of cutting-edge research. Now, high-throughput single-particle imaging (SPI) with X-ray free-electron lasers (XFELs) creates opportunities for recovering the shape distributions of millions of particles that exhibit functionally relevant structural heterogeneity. To realize this potential, three challenges have to be overcome: (1) simultaneous parametrization of structural variability in real and reciprocal spaces; (2) efficiently inferring the latent parameters of each SPI measurement; (3) scaling up comparisons between 10⁵ structural models and 10⁶ XFEL-SPI measurements. Here, we describe how we overcame these three challenges to resolve the nonequilibrium shape distributions within millionsmore » of gold nanoparticles imaged at the European XFEL. These shape distributions allowed us to quantify the degree of asymmetry in these particles, discover a relatively stable “shape envelope” among nanoparticles, discern finite-size effects related to shape-controlling surfactants, and extrapolate nanoparticles’ shapes to their idealized thermodynamic limit. Ultimately, these demonstrations show that XFEL SPI can help transform nanoparticle shape characterization from anecdotally interesting to statistically meaningful.« less

One of the outstanding analytical problems in X-ray single-particle imaging (SPI) is the classification of structural heterogeneity, which is especially difficult given the low signal-to-noise ratios of individual patterns and the fact that even identical objects can yield patterns that vary greatly when orientation is taken into consideration. Proposed here are two methods which explicitly account for this orientation-induced variation and can robustly determine the structural landscape of a sample ensemble. The first, termed common-line principal component analysis (PCA), provides a rough classification which is essentially parameter free and can be run automatically on any SPI dataset. The second method,more » utilizing variation auto-encoders (VAEs), can generate 3D structures of the objects at any point in the structural landscape. Both these methods are implemented in combination with the noise-tolerant expand–maximize–compress (EMC) algorithm and its utility is demonstrated by applying it to an experimental dataset from gold nanoparticles with only a few thousand photons per pattern. Both discrete structural classes and continuous deformations are recovered. These developments diverge from previous approaches of extracting reproducible subsets of patterns from a dataset and open up the possibility of moving beyond the study of homogeneous sample sets to addressing open questions on topics such as nanocrystal growth and dynamics, as well as phase transitions which have not been externally triggered.« less