Chromium alloys are being considered for next-generation concentrated solar power applications operating > 800 °C. Cr offers advantages in melting point, cost, and oxidation resistance. However, improvements in mechanical performance are needed. Here, Cr-based body-centred-cubic (bcc) alloys of the type Cr(Fe)-NiAl are investigated, leading to ‘bcc-superalloys’ comprising a bcc-Cr(Fe) matrix (β) strengthened by ordered-bcc NiAl intermetallic precipitates (β’), with iron additions to tailor the precipitate volume fraction and mechanical properties at high temperatures. Computational design using CALculation of PHAse Diagram (CALPHAD) predicts that Fe increases the solubility of Ni and Al, increasing precipitate volume fraction, which is validated experimentally. Nano-scale, highly-coherent B2-NiAl precipitates with lattice misfit ∼ 0.1% are formed in the Cr(Fe) matrix. The Cr(Fe)-NiAl A2-B2 alloys show remarkably low coarsening rate (∼102 nm3/h at 1000 °C), outperforming ferritic-superalloys, cobalt- and nickel-based superalloys. Low interfacial energies of ∼ 40/20 mJ/m2 at 1000/1200 °C are determined based on the coarsening kinetics. The low coarsening rates are principally attributed to the low solubility of Ni and Al in the Cr matrix. The alloys show high compressive yield strength of ∼320 MPa at 1000 °C. The Fe-modified alloy exhibits resistance to age softening, related to the low coarsening rate as well as the relatively stable Orowan strengthening as a function of precipitate radius. Microstructure tailoring with Fe additions offers a new design route to improve the balance of properties in “Cr-superalloys”, accelerating their development as a new class of high-temperature materials.

Kan Ma, Thomas Blackburn, Johan P. Magnussen, Michael Kerbstadt, Pedro A. Ferreir´os, Tatu Pinomaa, Christina Hofer, David G. Hopkinson, Sarah J. Day, Paul A.J. Bagot, Michael P. Moody, Mathias C. Galetz, Alexander J. Knowles.

Acta Materialia Journal
July 26, 2023

The accumulation of soiling on photovoltaic modules, and on the mirrors of concentrating solar power systems cause non-negligible energy loss with economic consequences. These can be mitigated, or even prevented, through appropriate actions if the magnitude of soiling is known. Particle counting analysis is a common procedure to characterize soiling as it can be easily performed on micrographs of glass coupons or solar devices that have been exposed to the environment. Soiling studies have typically assumed that particle counting produces invariant and inter-institution consistent results. However, particle size distribution analysis is affected by the operator and the utilized methodology. The results of a round-robin study are presented in this work to explore and elucidate the uncertainty related to particle counting and its effect on the characterization of the soiling of glass surfaces used in solar energy conversion systems. An international group of soiling experts analysed the same 8 micrographs using the same open-source ImageJ software package. The variation in the particle analyses results were investigated to identify specimen characteristics with the lowest coefficient of variation and the least uncertainty among the various operators. The mean particle diameter showed the lowest variance among the investigated characteristics , whereas the number of particles exhibited the largest variation. Additional parameters, such as the fractional area coverage and the distribution’s skewness, yielded an intermediate variance. These results can provide useful information on optical and microscope-based soiling monitoring and characterization.

Greg P. Smestad, Cody Anderson, Michael E. Cholette, Pavan Fuke, Ahmed Amine Hachicha, Anil Kottantharayil, Klemens Ilse, Mounia Karim, Muhammad Zahid Khan, Herbert Merkle, David C. Miller, Jimmy M. Newkirk, Giovanni Picotti, Florian Wiesinger, Guido Willers, Leonardo Micheli.

Solar Energy Materials and Solar Cells Journal
July 4, 2023

The performance of advanced materials for extreme environments is underpinned by their microstructure, such as the size and distribution of nano- to micro-sized reinforcing phase(s). Chromium-based superalloys are a recently proposed alternative to conventional face-centred-cubic superalloys for high-temperature applications, e.g., Concentrated Solar Power. Their development requires the determination of precipitate volume fraction and size distribution using Electron Microscopy (EM), as these properties are crucial for the thermal stability and mechanical properties of chromium superalloys. Traditional approaches to EM image processing utilise filtering with a fixed contrast threshold, leads to weak robustness to background noise and poor generalisability to different materials. It also requires an enormous amount of time for manual object measurements on large datasets. Efficient and accurate object detection and segmentation are therefore highly desired to accelerate the development of novel materials like chromium-based superalloys. To address these bottlenecks, based on YOLOv5 and SegFormer structures, this study proposes an end-to-end, two-stage deep learning scheme, DT-SegNet, to perform object detection and segmentation for EM images. The proposed approach can thus benefit from the training efficiency of CNNs at the detection stage (i.e., a small number of training images required) and the accuracy of the ViT at the segmentation stage. Extensive numerical experiments demonstrate that the proposed DT-SegNet significantly outperforms the state-of-the-art segmentation tools offered by Weka and ilastik regarding a large number of metrics, including accuracy, precision, recall and F1-score. This model forms a useful tool to aid alloy development microstructure examinations, and offers significant advantages to address the large datasets associated with highthroughput alloy development approaches.

Zeyu Xia, Kan Ma, Sibo Cheng, Thomas Blackburn, Ziling Peng, Kewei Zhu, Weihang Zhang, Dunhui Xiao, Alexander J Knowles and
Rossella Arcucci

PCCP Journal
May 26, 2023

A deep-black Cu, Mn, Fe- pigment with a spinel structure was employed to coat standard proppants in order to improve long term solar absorptance. The coating process was performed by high-energy, high-speed mixing of proppants and small quantities of spinel powders in a resonant acoustic mixer. A continuous powder coating is achieved by electrostatic attraction between the proppant surface and the coating particles. Consolidation and strong attachment of the coating is achieved by the subsequent sintering beyond the spinel melting temperature. Chemical reaction and bonding between spinel coating and proppant lead to the incorporation of Al, Mg and Ti into the spinel structure. Coated bauxite proppants exhibit a significantly improved, long-term stable solar absorption accompanied by a promising abrasion resistance. The presented coating methodology is considered to be scalable to industrial production.

Gözde Alkan, Peter Mechnich and Johannes Pernpeintner
Coatings Journal
May 31th, 2022

This article is a first of a series of informative papers aiming at disseminating the main achievements of COMPASsCO₂ project to a wide audience, in order to increase awareness on sustainable energy technologies and highlight the efforts of both research and industry for the transition to a carbon neutral energy mix in Europe. It summarises the activities conducted in the first 18 months of implementation (November 2020 – April 2022), and the main accomplishments, with a specific focus on the development and testing of novel materials.