Intercalation in 2D transition metal chalcogenides: interlayer engineering and applications

Intercalation is basically a process of putting one or multiple guest elements in the van der Waals (vdW) gaps of a parent crystal in a reversible way. Two-dimensional (2D) materials showed great promise for different intercalant species ranging from organic molecules to ions. Apart from graphene, the most studied 2D materials are the transition metal di-chalcogenides (TMDs). The intercalation in TMDs has reinvented the strategies beyond graphene in 2D structure in material science, materials engineering, chemistry, and physics. This review deals with the possible mechanism as well as the window that intercalation can open for compact and ultrathin device technology. Modulation of the physicochemical properties in the intercalated TMDs has been thoroughly reviewed. Finally, the device performance, especially energy storage and energy harvesting devices, has been evaluated, and specific issues have been chalked out that need attention for future development.

Pushing the boundaries of lithium battery research with atomistic modelling on different scales

Computational modelling is a vital tool in the research of batteries and their component materials. Atomistic models are key to building truly physics-based models of batteries and form the foundation of the multiscale modelling chain, leading to more robust and predictive models. These models can be applied to fundamental research questions with high predictive accuracy. For example, they can be used to predict new behaviour not currently accessible by experiment, for reasons of cost, safety, or throughput. Atomistic models are useful for quantifying and evaluating trends in experimental data, explaining structure-property relationships, and informing materials design strategies and libraries. In this review, we showcase the most prominent atomistic modelling methods and their application to electrode materials, liquid and solid electrolyte materials, and their interfaces, highlighting the diverse range of battery properties that can be investigated. Furthermore, we link atomistic modelling to experimental data and higher scale models such as continuum and control models. We also provide a critical discussion on the outlook of these materials and the main challenges for future battery research.

A systematic review of life cycle assessment of hydrogen for road transport use

This study conducted a systematic literature review of the technical aspects and methodological choices in life cycle assessment (LCA) studies of using hydrogen for road transport. More than 70 scientific papers published during 2000–2021 were reviewed, in which more than 350 case studies of use of hydrogen in the automotive sector were found. Only some studies used hybrid LCA and energetic input-output LCA, whereas most studies addressed attributional process-based LCA. A categorization based on the life cycle scope distinguished case studies that addressed the well-to-tank (WTT), well-to-wheel (WTW), and complete life cycle approaches. Furthermore, based on the hydrogen production process, these case studies were classified into four categories: thermochemical, electrochemical, thermal-electrochemical, and biochemical. Moreover, based on the hydrogen production site, the case studies were classified as centralized, on-site, and on-board. The fuel cell vehicle passenger car was the most commonly used vehicle. The functional unit for the WTT studies was mostly mass or energy, and vehicle distance for the WTW and complete life cycle studies. Global warming potential (GWP) and energy consumption were the most influential categories. Apart from the GREET (Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation) model and the Intergovernmental Panel on Climate Change for assessing the GWP, the Centrum voor Milieukunde Leiden method was most widely used in other impact categories. Most of the articles under review were comparative LCA studies on different hydrogen pathways and powertrains. The findings provide baseline data not only for large-scale applications, but also for improving the efficiency of hydrogen use in road transport.

Metrics for Assessing the Economic Impacts of Power Sector Climate and Clean Electricity Policies

Modeling tools are increasingly used to inform and evaluate proposed power sector climate and clean electricity policies such as renewable portfolio and clean electricity standards, carbon pricing, emissions caps, and tax incentives. However, claims about economic and environmental impacts often lack transparency and may be based on incomplete metrics that can obscure differences in policy design. This paper examines model-based metrics used to assess the economic efficiency impacts of prospective electric sector policies. The appropriateness of alternative metrics varies by context, model, audience, and application, depending on the prioritization of comprehensiveness, measurability, transparency, and credible precision. This paper provides guidance for the modeling community on calculating and communicating cost metrics and for consumers of model outputs on interpreting these economic indicators. Using an illustrative example of clean electricity standards in the U.S. power sector, model outputs highlight strengths and limitations of different cost metrics. Transformations of power systems with lower-carbon resources and zero-marginal-cost generation may entail shifts in when and where system costs are incurred, and given how these changes may not be appropriated reflected in metrics that were commonly reported in the past such as wholesale energy prices, showing a decomposition of system costs across standard reporting categories could be a more robust reporting practice. Ultimately, providing better metrics is only one element in a portfolio of transparency-related practices, and although it is insufficient by itself, such reporting can help to move dialogues in more productive directions and encourage better modeling practices.