Multi-energy networks facilitate the interactions of multiple energy carriers such as electricity, heat, cooling, and natural gas for manifold benefits in the construction and operation of energy systems. They also provide a unified platform to integrate and utilize various advanced energy technologies such as renewables, cogeneration, power-to-X, electric vehicles, and energy storage. The problem scale of multi-energy networks is increasing rapidly with the accelerated expansion and integration of regional and urban energy systems. For these reasons, the analysis and optimization of multi-energy networks are faced with significant challenges. New methods are urgently required to address the basic computational challenges in multi-energy networks such as the multi-temporal-spatial scales, nonlinearity, uncertainty, combinatorial property of mixed continuous and discrete variables, and the solving of large-scale systems in a multi-stakeholder context. This special issue mainly covers papers on the computational theories and methods that can be applied in multi-energy networks. The aim is to present a state-of-the-art collection of innovative models, algorithms, approaches, and tools for the control, operation, design, simulation, and analysis of multi-energy networks. The special issue provides an opportunity for researchers and practicing engineers to share their latest discoveries and best practices in these areas.

To achieve an effective design of additively manufacturable Ni superalloys with decent service performance, a hybrid computational design model has been developed, where the strategy to tailor local elemental segregations was integrated within a scheme of minimizing the cracking susceptibility. More specifically, the phase boundary of primary NbC / γ matrix was introduced into the design routine to tune the spatial distribution of critical solutes at an atomic scale, thereby inhibiting the formation of borides and segregation-induced cracking. Based on the output of the design, new grades of Ni superalloy have been developed with excellent additive manufacturability, as confirmed by the robustness of printing parameters in fabricating low-defect-density samples. The capability of the phase boundaries to evenly distribute boron atoms was validated experimentally, and the cracking induced by uncontrolled boron segregation at grain boundaries was effectively prevented. The newly designed alloys showed good tensile properties and decent oxidation resistance at different service temperatures, which are comparable to those of conventionally produced superalloys. The finding that phase boundaries can be employed to prevent undesirable clustering of boron atoms can be extended to manipulate the distributions of other critical elements, which provides a new path for designing novel Ni superalloys with balanced printability and mechanical properties.

Malodor is regarded as a very significant nuisance, 2nd only to noise pollution, in the developed world. It directly impacts people's health and wellbeing. The prevention of odor build-up is a key property for both interior textiles and active sportswear. Traditional approaches for odor elimination rely on textile surface treatment. However, the role of intrinsic morphology and chemical composition of fibers in odor elimination has not been taken into account. In this study, the adsorption characteristics and mechanisms of three common types of fibers (wool, cotton and nylon) for two typical odors of acetic acid and ammonia were systematically investigated through kinetic modelling, the inverse gas chromatography (IGC) technique, and density functional theory (DFT) calculations. Both acetic acid and ammonia adsorption onto fibers followed a pseudo-second-order kinetic model. Among all the tested fibers, wool showed the highest adsorption ability towards both acetic acid and ammonia. The adsorption behaviors of cotton and nylon were explored based on quantitative measurement of surface Lewis acid-base properties using the IGC technique. These findings were further corroborated by DFT calculations via the interactions between fibers and the adsorbed odor. This study provides a new insight into odor adsorption onto commonly used fibers and their interactions, which is a key step in developing fibrous materials for odor control, including body odor and indoor air pollutants.