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This article is composed of three independent commentaries about the state of Integrated, Coordinated, Open, Networked (ICON) principles (Goldman, et al., 2021b, https://doi.org/10.1029/2021EO153180) in Earth and Space Science Informatics (ESSI) and includes discussion on the opportunities and challenges of adopting them. Each commentary focuses on a different topic: (Section 2) Global collaboration, cyberinfrastructure, and data sharing; (Section 3) Machine learning for multiscale modeling; (Section 4) Aerial and satellite remote sensing for advancing Earth system model development by integrating field and ancillary data. ESSI addresses data management practices, computation and analysis, and hardware and software infrastructure. Our role in ICON science therefore involves collaborative work to assess, design, implement, and promote practices and tools that enable effective data management, discovery, integration, and reuse for interdisciplinary work in Earth and space science disciplines. Networks of diverse people with expertise across Earth, space, and data science disciplines are essential for efficient and ethical exchanges of findable, accessible, interoperable, and reusable (FAIR) research products and practices. Our challenge is then to coordinate the development of standards, curation practices, and tools that enable integrating and reusing multiple data types, software, multi‐scale models, and machine learning approaches across disciplines in a way that is as open and/or FAIR as ethically possible. This is a major endeavor that could greatly increase the pace and potential of interdisciplinary scientific discovery. Plain Language Summary: We present commentaries on the state of "Integrated, Coordinated, Open, Networked (ICON) principles" in Earth and Space Science Informatics. ICON principles are meant to improve the research experience for all. Ultimately, data standardized according to community conventions and formats lead to more effective and efficient collaboration, data discovery, integration, and analyses. Data standards, tools, and machine learning developed using ICON principles enhance our understanding of Earth processes. Using ICON principles improves model results and efficacy, fosters interdisciplinary research, and provides a framework by which non‐experts can confidently contribute volunteered data and findings. Standardized data also provides reliable common resources to help train and benchmark machine learning algorithms. When networked communities work together to standardize and share data openly, the resulting web of research products is more readily findable, accessible, interoperable, and reusable. Ongoing support is crucial to develop and sustain the people, systems, and tools necessary to embrace ICON principles in Earth and Space Science Informatics now and in the future. Key Points: Networks across communities, with Coordinated data and information modeling practices, improve scientific outcomes for all involvedIntegrated, Coordinated, and Open data requires sustainable support to create and maintain infrastructure for interdisciplinary NetworksIntegrated and Coordinated use of data in machine learning calls for Open benchmark datasets shared across Networks for improved outcomes [ABSTRACT FROM AUTHOR]

IrO2/Pt catalysts (at different concentrations) were synthesized by incipient wetness technique and characterized by XRD, XRF, and SEM. Water electrolysis/fuel cell performances were evaluated in a 5 cm2 single cell under Unitized Regenerative Fuel Cell (URFC) configuration. The IrO2/Pt composition of 14/86 showed the highest performance for water electrolysis and the lowest one as fuel cell. It is derived that for fuel cell operation an excess of Pt favours the oxygen reduction process whereas IrO2 promotes oxygen evolution. From the present results, it appears that the diffusion characteristics and the reaction rate in fuel cell mode are significantly lower than in the electrolyser mode. This requires the enhancement of the gas diffusion properties of the electrodes and the catalytic properties for cathode operation in fuel cells. [ABSTRACT FROM AUTHOR]