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ALBA is facing an important development towards ALBA II that represents a big step in its performances and will have a significant impact on the future characterization capabilities offered to the scientific community.
Catalysis will be one of the scientific areas where ALBA II will be focused. Catalytic processes are of the utmost importance in order to overcome the challenges regarding climate change and energy demand that are critical for the future of our society. Therefore, it is mandatory that all those techniques that can help us to unveil the mechanisms of catalytic reactions and understand the reactivity and selectivity of catalysts are prioritized, optimized and improved. Synchrotron characterization techniques are one of the tools that allow obtaining valuable information of the materials/samples of interest. Because of this, the application of synchrotron instrumentation for catalytic studies has experienced a dramatic increase during the last decades with special emphasis on the development of in situ/operando capabilities together with the increment of the potentiality offered by data analytics.
The workshop entitled “Present and future perspective of catalysis in ALBA II” aims to define the path to follow from the current tools for catalytic research that ALBA offers to the ones that ALBA II should provide, considering the trends in catalysis within the next decades. The goal is to offer within ALBA II a set of state-of-the-art synchrotron characterization techniques to investigate the design, preparation and optimization of catalysts before, after or during the reactions of interest or at any stage of their synthesis. Special attention should be placed on:
Role of synchrotron techniques answering to challenges in catalysis in the next years
Approach and strategy for combination of synchrotron and laboratory techniques/facilities: sample environments, TEM instrumentation, operando experiments combined with complementary techniques (e.g. XAS/DRIFT/MS).
Data collection and analysis strategy: time resolved and modulated experiments, high throughput data collection, data science (statistical analysis, machine learning, etc.), theoretical calculations
Knowledge transfer and implementation of synergies with industry