Purpose This manuscript describes the experience of two institutions in commissioning the new HalcyonTM platform. Its purpose is to: (a) validate the pre‐defined beam data, (b) compare relevant commissioning data acquired independently by two separate institutions, and (c) report on any significant differences in commissioning between the Halcyon linear accelerator and other medical linear accelerators. Methods Extensive beam measurements, testing of mechanical and imaging systems, including the multi‐leaf collimator (MLC), were performed at the two institutions independently. The results were compared with published recommendations as well. When changes in standard practice were necessitated by the design of the new system, the efficacy of such changes was evaluated as compared to published approaches (guidelines or vendor documentation). Results Given the proper choice of detectors, good agreement was found between the respective experimental data and the treatment planning system calculations, and between independent measurements by the two institutions. MLC testing, MV imaging, and mechanical system showed unique characteristics that are different from the traditional C‐arm linacs. Although the same methodologies and physics equipment can generally be used for commissioning the Halcyon, some adaptation of previous practices and development of new methods were also necessary. Conclusions We have shown that the vendor pre‐loaded data agree well with the independent measured ones during the commission process. This verifies that a data validation instead of a full‐data commissioning process may be a more efficient approach for the Halcyon. Measurement results could be used as a reference for future Halcyon users.

who kindly allowed us to use their new data on yields and runoffs under no-till, and tirelessly advised us in many details. We thank Christian Eriksson for competent statistical analyses of crop yield data, Hannu J. Mikkola for helpful comments, and Eirik Romstad for insightful advice.

Application of membrane technologies in biorefinery processes has been studied for some time. The heterogenous nature of biorefinery steams, however, results in unideal performance of membrane systems and considerable fouling of membranes, which is decreasing the efficiency of separation. As a part of BioSPRINT project, this study focuses on application of separating monomeric sugars from the hemicelluloses fraction of lignocellulosic biomass, where pressure-driven nanofiltration with several diafiltration stages has been proposed for the separation task. Diafiltration is required to overcome the decreased separation efficiency when the retentate concentrations and viscosity increases. A lumped parameter dynamical model of the diafiltration plant is applied. The key model parameters are identified from experimental data from a laboratory membrane unit to reflect the considered biorefinery process. The model is then simulated to study the sensitivity of the uncertain model parameters (related to membrane fouling, solute concentrations, viscosity, and mass transfer coefficients) to the diafiltration plant performance (product purity, operation time). The model is implemented in the MATLAB®/Simulink environment. The simulation results are expected to identify potential sources of scale-up challenges in biorefinery-related membrane applications. The developed dynamic model also allows to investigate different operational strategies of diafiltration plants in the future.

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