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AbstractHerein, we present ultrasmall delafossite‐type Mg‐doped CuCrO2 nanocrystals prepared by using hydrothermal synthesis and their first application as photocathodes in efficient p‐type dye‐sensitized solar cells. The short‐circuit current density (Jsc) is notably increased by approximately 27 % owing to the decreased crystallite size and the enhanced optical transmittance associated with Mg doping of the CuCrO2 nanocrystalline sample. An open‐circuit voltage (Voc) of 201 mV, Jsc of 1.51 mA cm−2, fill factor of 0.449, and overall photoconversion efficiency of 0.132 % have been achieved with the CuCr0.9Mg0.1O2 dye photocathode sensitized with the P1 dye under optimized conditions. This efficiency is nearly three times higher than that of the NiO‐based reference device, which is attributed to the largely improved Voc and Jsc. The augmentation of Voc and Jsc can be attributed to the lower valance band position and the faster hole diffusion coefficient of CuCr0.9Mg0.1O2 compared to those of the NiO reference, respectively, which leads to a higher hole collection efficiency.

Deregulated energy markets were founded on the Merchant Power Producer, a stand-alone generator that sold its production to the spot and short-term forward markets, underpinned by long-dated project finance. The initial enthusiasm that existed for investment in existing and new merchant power plant capacity shortly after power system deregulation has progressively dissipated, following an excess entry result. In this article, we demonstrate why this has become a global trend. Using debt-sizing parameters typically used by project banks, we model a benchmark plant, then re-simulate its performance using live energy market price data and find that such financings are no longer feasible in the absence of long-term Power Purchase Agreements.

In order to maximize the Pt utilization in catalysts and improve catalytic processes, we report a convenient strategy for preparation of Pt3Co with Pt-skin structured bimetallic nanocatalysts directly supported on porous graphitic carbon. Notably, the thickness of the Pt-skin is only 1–2 atomic layers, about 0.5 nm. Surprisingly, the bimetallic nanocatalysts composed of Pt3Co with Pt-skin are first used as ethanol electro-catalysts, with the mass activity of 0.79 mA μgPt–1, which is a 250% enhancement compared with commercial Pt/C (0.32 mA μgPt–1). On the basis of the results of electrochemical in situ Fourier transform infrared spectroscopy (FTIRS) and density functional theory (DFT), a new ethanol electro-oxidation enhancement mechanism is proposed in which Pt3Co with Pt-skin promotes partial oxidation of ethanol over C–C bond cleavage, thereby resulting in higher CH3COOH production than CO2 production.

Exhaust hoods are commonly used to capture all emissions from stationary combustion systems that are open to the environment, such as residential heaters or stoves. For experimental purposes, emissions are sampled at one, or more, discrete locations downstream in the exhaust duct. Point-wise measurements in the duct are often taken with the assumption that the emissions are homogeneously distributed across the duct cross-section, because the flow is turbulent and therefore believed to be thoroughly mixed. However, the length of such systems is rarely sufficient to ensure fully-developed flow, and the actual homogeneity is seldom assessed. In the present work the mixing within the duct is investigated by simulating the emissions distribution within various hood and duct configurations. The simulations include a straight duct with and without baffles and two different exhaust hood configurations, namely at the Stove Testing Lab at Lawrence Berkeley National Laboratory (LBNL) and at the University of Adelaide that meet standard requirements. The air flow in the ducts was simulated using Reynolds-averaged (RANS) turbulence modelling, with carbon monoxide (CO) as a representative combustion product, injected at three locations in the straight duct and two locations (centre and side) in the exhaust hoods. Simulations predict that, in isolation, neither a straight duct without baffles, nor a hood with a 90° elbow followed by a straight duct without baffles, provide sufficient mixing to achieve a near uniform distribution of CO at the sampling locations. However, simulations show that adequate mixing of dilution air and CO is achieved with baffles-induced flow detachment and recirculation, not from turbulent mixing in the straight section of the duct itself. The simulations also suggest that elbows, baffles, expansions or other geometrical features are needed to induce thorough mixing. For example, in the Stove Testing Lab at LBNL, flow disturbance is induced by an expansion into a larger diameter straight duct immediately downstream of the hood and the 90° elbow. Although these two systems demonstrate sufficient mixing of CO within the exhaust, the RANS simulations in this study suggest that other systems relying solely on mixing within a specified duct length (viz. 8–12 diameters) may not be sufficient. Refereed/Peer-reviewed

The feasibility of reliably generating bioenergy from forest biomass waste is intimately linked to supply chain and production processing costs. These costs are, at least in part, directly related to assumptions about the reliability and cost-efficiency of the machinery used along the forestry bioenergy supply chain. Although mechanization in forestry operations has advanced in the last 20 years, it is evident that challenges remain in relation to production capability, standardization of wood quality, and supply guarantee from forestry resources because of the age and reliability of the machinery. An important component in sustainable bioenergy from biomass supply chains will be confidence in consistent production costs linked to guarantees about harvest and haulage machinery reliability. In this context, this paper examines the issue of machinery maintenance and advances in machine learning and big data analysis that are contributing to improved intelligent prediction that is aiding supply chain reliability in bioenergy from woody biomass. The concept of “Industry 4.0” refers to the integration of numerous technologies and business processes that are transforming many aspects of conventional industries. In the realm of machinery maintenance, the dramatic increase in the capacity to dynamically collect, collate, and analyze data inputs including maintenance archive data, sensor-based monitoring, and external environmental and contextual variables. Big data analytics offers the potential to enhance the identification and prediction of maintenance (PdM) requirements. Given that estimates of costs associated with machinery maintenance vary between 20% and 60% of the overall costs, the need to find ways to better mitigate these costs is important. While PdM has been shown to help, it is noticeable that to-date there has been limited assessment of the impacts of external factors such as weather condition, operator experiences and/or operator fatigue on maintenance costs, and in turn the accuracy of maintenance predictions. While some researchers argue these data are captured by sensors on machinery components, this remains to be proven and efforts to enhance weighted calibrations for these external factors may further contribute to improving the prediction accuracy of remaining useful life (RUL) of machinery. This paper reviews and analyzes underlying assumptions embedded in different types of data used in maintenance regimes and assesses their quality and their current utility for predictive maintenance in forestry. The paper also describes an approach to building ‘intelligent’ predictive maintenance for forestry by incorporating external variables data into the computational maintenance model. Based on these insights, the paper presents a model for an intelligent predictive maintenance system (IPdM) for forestry and a method for its implementation and evaluation in the field.

Abstract New exogenous cis,cis-muconic acid biosynthetic pathway genes were expressed in Saccharomyces cerevisiae. The xylose isomerase gene from Bacteroides valgutus and pentose phosphate pathway genes from S. cerevisiae were overexpressed in the yeast strain. The strain was further modified by the overexpression of gene Aro1 (with a stop codon of AroE) and a feedback-resistant Aro4opt mutant gene from S. cerevisiae. Under oxygen-limited conditions, it produced 65 mg/L cis,cis-muconic acid from xylose. Co-fermentation of 88 g/L glucose and 50 g/L xylose generated 54 g/L ethanol and 248 mg/L cis,cis-muconic acid. Under aerobic conditions, muconic acid titer reached 424 mg/L. With the supplement of 1 g/L catechol, 1286 mg/L muconic acid was produced. Fermentation of an oil palm empty fruit bunch hydrolysate resulted in 31.3 g/L ethanol and 53.4 mg/L muconic acid. This is the first report on the production of muconic acid from lignocellulosic biomass hydrolysate using a recombinant xylose-fermenting yeast.

This article demonstrates how a cultural reading of consumption that focuses on the meaning and materiality of domestic indoor microclimates can contribute to conceptual developments in the field of practice theory that refocus attention on cultural patterns, including prevailing norms and prescriptions regarding indoor temperature and thermal comfort. Drawing on evidence collected during a research-led change initiative that encouraged people to reduce energy use in the home by lowering indoor temperature to 18°C, we deploy the heuristic device of “indoor microclimate as artifact” to show how the manifestation of this new artifact initiated significant changes in everyday practices that revolve around heating. We observe that these changes may also spill over into the public sphere – from home to workplace. By making the microclimate a tangible and visible thing, we describe how people appropriate and appreciate this new object of consumption, what it says about different bodies in diverse and bounded spaces, and what the artifact as a commodity reveals about broader systems of heating and energy provision, and associated actors. Due to the increasing spread of central heating and the growing importance of complex technological devices to monitor and control indoor temperature, heating is no longer a practice in and of itself for many urban dwellers in Europe. However, when people appropriate the indoor microclimate, new heating-related practices emerge that can lead to energy sufficiency. We thus argue that by deliberately “materializing” domestic indoor microclimate as part of a change initiative, more sustainable forms of energy use can be made to matter.

Abstract Concerning both the activity and stability of the promising solar-driven Ta3N5-based photoanodes for photoelectrochemical water splitting, the strategy for simultaneously promoting charge separation, enhancing catalytic activity and also improving the resistance to self-oxidation is highly desirable and actively pursued. In this study, a novel dual co-catalyst shell consisting of a continuous CoPi layer at the bottom and many non-continuous Co(OH)2 islands at the top of the CoPi layer is designed to meet the strict requirements for efficient Ta3N5 photoanodes. As a result of the synergistic effects of such a shell in collectively addressing the concerns, the constructed photoanode of CoPi/Co(OH)2-Ta3N5 nanorod arrays show the remarkably enhanced photoelectrochemical water splitting performance compared with the photoanodes with single co-catalyst. The results demonstrated in this study are expected to shed some light on constructing efficient photoelectrodes of the light absorbers that have wide absorption range but low resistance to self-oxidation.