This paper describes an open data set of 3,053 energy meters from 1,636 non-residential buildings with a range of two full years (2016 and 2017) at an hourly frequency (17,544 measurements per meter resulting in approximately 53.6 million measurements). These meters were collected from 19 sites across North America and Europe, with one or more meters per building measuring whole building electrical, heating and cooling water, steam, and solar energy as well as water and irrigation meters. Part of these data was used in the Great Energy Predictor III (GEPIII) competition hosted by the American Society of Heating, Refrigeration, and Air-Conditioning Engineers (ASHRAE) in October-December 2019. GEPIII was a machine learning competition for long-term prediction with an application to measurement and verification. This paper describes the process of data collection, cleaning, and convergence of time-series meter data, the meta-data about the buildings, and complementary weather data. This data set can be used for further prediction benchmarking and prototyping as well as anomaly detection, energy analysis, and building type classification.

High-entropy alloy (HEA) nanoparticles are promising catalyst candidates for the acidic oxygen evolution reaction (OER). Herein, we report the synthesis of IrFeCoNiCu-HEA nanoparticles on a carbon paper substrate via a microwave-assisted shock synthesis method. Under OER conditions in 0.1 M HClO₄, the HEA nanoparticles exhibit excellent activity with an overpotential of ∼302 mV measured at 10 mA cm^-2 and improved stability over 12 h of operation compared to the monometallic Ir counterpart. Importantly, an active Ir-rich shell layer with nanodomain features was observed to form on the surface of IrFeCoNiCu-HEA nanoparticles immediately after undergoing electrochemical activation, mainly due to the dissolution of the constituent 3d metals. The core of the particles was able to preserve the characteristic homogeneous single-phase HEA structure without significant phase separation or elemental segregation. This work illustrates that under acidic operating conditions, the near-surface structure of HEA nanoparticles is susceptible to a certain degree of structural dynamics.