Decarbonising ceramic manufacturing : a techno-economic analysis of energy efficient sintering technologies in the functional materials sector

The rising cost of energy and concerns about the environmental impact of manufacturing processes have necessitated the need for more efficient and sustainable manufacturing. The ceramic industry is an energy intensive industrial sector and consequently the potential to improve energy efficiency is huge, particularly through the introduction of modern sintering technologies. Although several energy efficient sintering processes have been developed, there is no comprehensive techno-economic analysis which compares and contrasts these techniques. This paper presents a critical review and analysis of a number of sintering techniques and compares them with the recently developed cold sintering process (CSP), including mode of operation, sintering mechanism, typical heating rates, duration of sintering, energy consumption profile and energy saving potential, limitations, key challenges for further development and current research efforts. By using a figure of merit, pounds per tonne of CO2 saved (£/tCO2-eq), which links initial capital investment with energy savings, within a framework derived from ranking principles such as marginal abatement cost curves and Pareto optimisation, we have demonstrated that under the scenarios considered for 3 separate functional oxides ZnO, PZT and BaTiO3, CSP is the most economically attractive sintering option, indicating lower capital costs and best return on investment as well as considerable energy and emission savings. Although the current work establishes the viability of CSP as a competitive and sustainable alternative to other sintering techniques, the transition from laboratory to industry of CSP will require hugely different facilities and instrumentation as well as relevant property/performance validation to realise its full potential

Perovskite solar cells: An integrated hybrid lifecycle assessment and review in comparison with other photovoltaic technologies

Solar cells are considered as one of the prominent sources of renewable energy suitable for large-scale adoption in a carbon-constrained world and can contribute to reduced reliance on energy imports, whilst improving the security of energy supply. A new arrival in the family of solar cells technologies is the organic-inorganic halide perovskite. The major thrust for endorsing these new solar cells pertains to their potential as an economically and environmentally viable option to traditional silicon-based technology. To verify this assertion, this paper presents a critical review of some existing photovoltaic (PV) technologies in comparison with perovskite-structured solar cells (PSCs), including material and performance parameters, production processes and manufacturing complexity, economics, key technological challenges for further developments and current research efforts. At present, there is limited environmental assessment of PSCs and consequently, a methodologically robust and environmentally expansive lifecycle supply chain assessment of two types of PSC modules A and B is also undertaken within the context of other PV technologies, to assess their potential for environmentally friendly innovation in the energy sector. Module A is based on MAPbX3 perovskite structure while module B is based on CsFAPbX3 with improved stability, reproducibility and high performance efficiency. The main outcomes, presented along with sensitivity analysis, show that PSCs offer more environmentally friendly and sustainable option, with the least energy payback period, as compared to other PV technologies. The review and analysis presented provide valuable insight and guidance in identifying pathways and windows of opportunity for future PV designs towards cleaner and sustainable energy production

Comparison of nutritional values of wheat (Triticum aestivum) and acha (Digitaria exilis) grains

This study determined the proximate composition, mineral content and phytochemical screening of wheat (Triticum aestivum) and acha (Digitaria exilis) grains obtained from Garki market, Federal Capital Territory (FCT) Abuja in order to compare the nutritional and medicinal values of the two grains. The results obtained from the proximate analysis of wheat and acha respectively is as follows: moisture content (9.33 ± 0.57% and 10.9 ± 0.05%), ash (1.16 ± 0.28% and 1.16 ± 0.28%), crude fibre (9.83 ± 0.28% and 15.33 ± 0.57%), crude protein (5.76 ± 1.23% and 3.35 ± 1.13%), lipid (1.5 ± 0.70% and 1.00 ± 0%), carbohydrates (72.29 ± 0.72% and 68.46 ± 1.33%), energy value (3.2582 and 2.9432kcal/100mg). The mineral analysis showed that the amount of Fe, K and Mg were higher in acha compared to wheat and Na, Ca, Zn and Pb are higher in wheat compared to acha. Cr was not detected in both samples. The phytochemical screening revealed the presence of carbohydrate, flavonoids and cardiac glycoside in the two samples. Saponin were present in only wheat, whereas alkaloids are present in only acha. However, phenolics, tannins, terpenes and steroids were absent in the two samples. The result of this study has revealed that both samples are rich sources of carbohydrate, crude fibres and essential mineral. In addition, the phytochemical analysis result shows that these cereals are potential sources of therapeutic agents which can help to lower the risk of several diseases.Keywords: Acha, Nutritional values, Mineral content, Wheat, Phytochemical

Finite element and multivariate random forests modelling for stress shield attenuation in customized hip implants

Primary total hip replacement surgery has an undisputable reputation as a widely successful orthopaedic operation, but it is beset by a phenomenon known as stress shielding. The cause of stress shielding is multifaceted. However, its reduction is reported to be hinged on the optimal design of prosthetic implants. Yet, to date, the design of a hip implant profile that behaves biomechanically similar to the natural physiological load-bearing zones of the femur remains an open problem. Along this vein, this paper instantiates an inquiry into the development of a framework that couples the capability of the finite element analysis (FEA) with that of machine learning methods toward the discovery of optimal design parameters for a customized hip implant. First, premised on the properties of a commercial normal-stem hip implant, a baseline computer-aided design (CAD) parametric model was created. From the baseline CAD model, a database of 120 hip implant profiles is established from the perturbation of the lateral edge, lateral angle, and the ratio of the radial cross-sectional areas of the implant. Next, the validation of the developed finite element procedure was conducted on a healthy intact femur and detailed numerical simulations were undertaken to assess the stress shielding (SS) attributes of all hip implants in the established database. The ensuing stress and strain data from the FEA is then deployed to ward a data-driven inverse model based on the random forests machine learning algorithm. Results-wise, the validation of the static analysis on the intact femur yielded von Mises stresses that matched those reported in published studies. Moreover, other results from the FEA revealed that a rectangular cross-sectioned hip implant resulted in the highest SS in the four zones of the proximal femoral compared to the trapezoidal cross-sectioned implant. Further, the inverse RF model exhibited excellent predictive capability and was subsequently employed towards the retrieval of the optimal geometric parameters that will manifest minimal stress shielding effect

Development of surrogate predictive models for the nonlinear elasto-plastic response of medium density fibreboard-based sandwich structures

Medium-density fibreboard (MDF) belongs to a class of engineered wood products facilitating efficient use of wood wastes. For this class of materials, the development of predictive models is crucial for the simulation of their responses under mechanical loads. In this study, samples of sandwich structures based on MDF as the skins and a mushroom-based foam as the core are fabricated and tested under edgewise compression tests. Results from the tests support the idea that increasing the thickness of the skins strengthens the response of the sandwich structure against buckling failure, but also revealed that thicker skins are susceptible to complex failure modes. Towards data-driven constitutive modelling of the nonlinear elastic-plastic response of this bio-based structure, predictive models premised on feedforward backpropagation neural network (FFNN), cascade-forward backpropagation neural network (CFNN), and generalized regression neural network (GRNN) were developed. Performance of the models was assessed via error criteria that include the coefficient of determination (R2), root mean squared error (RMSE) and mean absolute error (MAE). Results from the models indicate that CFNN with 15 hidden neurons under the Levenberg-Marquardt backpropagation training algorithm outperformed FFNN and GRNN models, with R2=1.0, RMSE=0.0030 and MAE=0.0019

Techno-environmental analysis of material substitution in thermoelectric modules: non-oxide (bismuth telluride alloys) vs. oxide-based (lanthanum-doped strontium titanate and calcium cobaltite) materials

Due to high toxicity, thermal instability at high temperature, low availability, and the high cost of raw metallic alloys such as Bi2Te3 for thermoelectric (TE) applications, there has been a drive to develop earth-abundant and eco-benign TE materials suitable for high-temperature applications. Oxide-based TEs have lately been touted to satisfy these criteria, but a lifecycle assessment (LCA) and energy payback period (EPBP) assessment of both classes of materials have not been conducted. This paper presents a comparative LCA of two laboratory-based TE modules namely, non-oxide n-type selenium-doped Bi2Te3 and p-type antimony-doped Bi2Te3 (Module A) versus oxide-based n-type lanthanum-doped SrTiO3 and p-type layered Ca3Co4O9 (Module B). Electrical energy consumption (EEC) during fabrication constitutes the largest impact for both modules, even under a decarbonised grid scenario, although Module B has an overall lower EEC. Nonetheless, for Module A, the use of tellurium and antimony exhibited noticeable environmental toxicity impacts, but smaller compared to EEC. The rare earth elements contained in the n-type component of Module B, showed negligible environmental toxicity impact, but those from its p-type component is noticeably high due to the presence of cobalt oxide. Computations of performance characteristics based on the material configurations of both modules showed that Module A yielded a higher power output compared to Module B, and as the power output increases, the EPBP becomes almost identical for both modules, underscoring its integral role to EEC offsetting. Key challenges, therefore, once EEC is diminished for large-scale applications are raw materials availability and cost, alongside performance

Barriers to climate change adaptation: evidence from northeast Ghana in the context of a systematic literature review

Despite the international significance attached to climate change adaptation, there remains a lack of understanding of the barriers that impede the effective implementation of adaptation strategies by households across sub-Saharan Africa (SSA). Better understanding of the vulnerability of agriculture-dependent households to climate variability requires exploration of the barriers that constrain the implementation of adaptation strategies. This paper uses case studies from northeast Ghana and a systematic literature review to assess the barriers that restrict effective implementation of climate adaptations in SSA. Results suggest that households are constrained by financial barriers, socio-cultural barriers, institutional barriers, technological barriers and a lack of information on climate change characteristics. We examine how the various barriers interact at different levels to influence the adaptation process. Findings highlight that the development of early warning systems, effective communication of climate information and an understanding of the local context within which adaptations take place, are necessary pre-requisites to enhance climate adaptations and rural livelihoods. Households need to be supported through the provision of micro-credit schemes, community empowerment and extension initiatives aimed at enhancing social networks within farming communities in order to reduce their vulnerability to the adverse impacts of climate change and variability