Unravelling Morphological and Topological Energy Contributions of Metal Nanoparticles

Metal nanoparticles (NPs) are ubiquitous in many fields, from nanotechnology to heterogeneous catalysis, with properties differing from those of single-crystal surfaces and bulks. A key aspect is the size-dependent evolution of NP properties toward the bulk limit, including the adoption of different NP shapes, which may bias the NP stability based on the NP size. Herein, the stability of different Pdn NPs (n = 10–1504 atoms) considering a myriad of shapes is investigated by first-principles energy optimisation, leading to the determination that icosahedron shapes are the most stable up to a size of ca. 4 nm. In NPs larger than that size, truncated octahedron shapes become more stable, yet a presence of larger {001} facets than the Wulff construction is forecasted due to their increased stability, compared with (001) single-crystal surfaces, and the lower stability of {111} facets, compared with (111) single-crystal surfaces. The NP cohesive energy breakdown in terms of coordination numbers is found to be an excellent quantitative tool of the stability assessment, with mean absolute errors of solely 0.01 eV·atom−1, while a geometry breakdown allows only for a qualitative stability screening.

Using new computer based techniques to optimise energy consumption in agricultural land levelling

Land levelling is one of the most energy-demanding steps in soil preparation. There are many limiting factors for a specific land levelling operation, such as fertile topsoil conservation, limited allowed slope, specific cut to fill ratio, etc. These limitations make optimisation problems of land levelling even more complicated. In this research, three computational and evolutionary methods including ICA, PSO, GA along with MLS were utilised as optimisation methods to minimise the soil cut and fill volumes and to determine the preferred levelling plane. The results indicated that ICA had the most efficient solution for the energy optimisation in the land levelling among the other investigated methods by saving 29% (17 GJ) of the total energy consumption compared with MLS. This study deals with optimising the energy consumption during land levelling projects using new computer-based techniques and compares them to the MLS method as a benchmark. All in all, ICA, PSO, and GA performed much better than MLS by saving 29, 17, and 10% of the total energy consumption in their best model (number 1 models), respectively. Nonetheless, with these great capacities for saving energy in developing countries, unfortunately, the lack of education and excess subsidies on fossil fuels nullify these potentials.

Biogas, Solar and Geothermal Energy—The Way to A Net-Zero Energy Wastewater Treatment Plant–A Case Study

Wastewater treatment plants designed to meet the requirements of discharging wastewater to a receiving water body are often not energy optimised. Energy requirements for conventional activated sludge wastewater treatment plants are estimated to range from 0.30 to 1.2 kWh/m3, with the highest values achieved using the nitrification process. This article describes the energy optimisation process of the wastewater treatment plant in Gubin (Poland) designed for 90 000 PE (population equivalent) using renewable energy sources: solar, biogas, and geothermal. At the analysed wastewater treatment plant electricity consumption for treating 1 m3 of wastewater was 0.679 kWh in 2020. The combined production of electricity and heat from biogas, the production of electricity in a photovoltaic system, and heat recovery in a geothermal process make it possible to obtain a surplus of heat in relation to its demand in the wastewater treatment plant, and to cover the demand for electricity, with the possibility of also selling it to the power grid.

Edge HVAC Analytics

Integrating data analytics, optimisation and dynamic control to support energy services has seen significant interest in recent years. Larger appliances used in an industry context are now provided with Internet of Things (IoT)-based interfaces that can be remotely monitored, with some also provided with actuation interfaces. The combined use of IoT and edge computing enables connectivity between energy systems and infrastructure, providing the means to implement both energy efficiency/optimisation and cost reduction strategies. We investigate the economic implications of harnessing IoT and edge/cloud technologies to support energy management for HVAC (Heating, Ventilation and Air Conditioning) systems in buildings. In particular, we evaluate the cost savings for building operations through energy optimisation. We use a real use case for energy optimisation as identified in the EU “Sporte2” project (focusing on the energy optimisation of sports facilities) and explore several scenarios in relation to costs and energy optimisation.

Identifying Energy Extraction Optimisation Strategies of Actinobacillus succinogenes

A. succinogenes is well known for utilising various catabolic pathways. A multitude of batch fermentation studies confirm flux shifts in the catabolism as time proceeds. It has also been shown that continuous cultures exhibit flux variation as a function of dilution rate. This indicates a direct influence of the external environment on the proteome of the organism. In this work, ATP production efficiency was explored to evaluate the extent of bio-available energy on the production behaviour of A. succinogenes. It was found that the microbe successively utilised its most-to-least efficient energy extraction pathways, providing evidence of an energy optimisation survival strategy. Moreover, data from this study suggest a pyruvate overflow mechanism as a means to throttle acetic and formic acid production, indicating a scenario in which the external concentration of these acids play a role in the energy extraction capabilities of the organism. Data also indicates a fleeting regime where A. succinogenes utilises an oxidised environment to its advantage for ATP production. Here it is postulated that the energy gain and excretion cost of catabolites coupled to the changing environment is a likely mechanism responsible for the proteome alteration and its ensuing carbon flux variation. This offers valuable insights into the microbe’s metabolic logic gates, providing a foundation to understand how to exploit the system.