The control of the physical, chemical, and electronic properties of laser-induced graphene (LIG) is crucial in the fabrication of flexible electronic devices. However, the optimization of LIG production is time-consuming and costly. Here, we demonstrate state-of-the-art automated parameter tuning techniques using Bayesian optimization to advance rapid singlestep laser patterning and structuring capabilities with a view to fabricate graphene-based electronic devices. In particular, a large search space of parameters for LIG explored efficiently. As a result, high-quality LIG patterns exhibiting high Raman G/D ratios at least a factor of four larger than those found in the literature were achieved within 50 optimization iterations in which the laser power, irradiation time, pressure and type of gas were optimized. Human-interpretable conclusions may be derived from our machine learning model to aid our understanding of the underlying mechanism for substrate-dependent LIG growth, e.g. highquality graphene patterns are obtained at low and high gas pressures for quartz and polyimide, respectively. Our Bayesian optimization search method allows for an efficient experimental design that is independent of the experience and skills of individual researchers, while reducing experimental time and cost and accelerating materials research.

Hydrogenation of CO2 to hydrocarbons is one of the crucial technologies to address the energy deficit and increasing environmental pollution. In this work, we have synthesized and systematically studied the influence of composition and nanostructure of a Fe‐based, carbon‐coated core–shell nanocatalyst. The synthesis method offered good control over the thickness of the carbon coating in the core–shell catalyst, which in turn controlled the chemical composition of the core. The results emphasized an optimal amount of Fe3O4, Fe5C2 in the core and partially graphitized carbon in the shell for a high catalytic activity in the conversion of CO2 at atmospheric pressure with higher selectivity to C2‐C4 olefins.

Abstract. An automorphism α of a group G is said to be central if α commutes with every inner automorphism of G. We construct a family of non-special finite p-groups having abelian automorphism groups. These groups provide counterexamples to a conjecture of A. Mahalanobis [Israel J. Math., 165 (2008), 161 -187]. We also construct a family of finite p-groups having non-abelian automorphism groups and all automorphisms central. This solves a problem of I. Malinowska [Advances in group theory, Aracne Editrice, Rome 2002, 111-127].

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