The National Physical Laboratory (NPL) is the UK's National Measurement Institute, and is a world-leading centre of excellence in developing and applying the most accurate measurement standards, science and technology available. As the UK’s national standards laboratory, NPL underpins the national measurements system, ensuring consistency and traceability of measurements throughout the UK. NPL offers a unique range of measurement services, contract research, consultancy and training services. Other areas of expertise include the design and characterisation of engineering materials and mathematical software, especially its application to measurement and instrumentation.

Three groups within NPL will contribute to HyMet: Electronic and Magnetic Materials; Data Science; National Centre of Excellence in Mass Spectroscopy Imaging (NiCE-MSI).

NPL will provide the management and overall technical coordination of the project, led by Dr Fernando Castro.

The Electronic and Magnetic Materials group has established expertise in the characterisation of nanoscale materials and electronic devices, with a focus on materials for energy applications. This expertise will be applied to the development of reference materials and calibration methods for nanomaterials using advanced modes of Scanning Probe Microscopy and optical spectroscopy. Existing facilities for in situ testing and monitoring of novel photovoltaic devices will be extended to allow simultaneous multi-parametric measurements that will be used to identify key parameters for predicting aging of devices using hybrid metrology methods.

The Mass Spectroscopy Imaging group is a National Centre of Excellence, with world-leading expertise in 3D Secondary Ion Mass Spectrometry. This unique capability will be applied to novel photovoltaics, providing chemical information that will be combined with electrical characterisation and device performance data sets.

The Data Science group has expertise in modelling, data analysis, and uncertainty evaluation which will be used in HyMet to develop new methods for data fusion and hybrid modelling that will be demonstrated using experimental data acquired from multi-parameter measurements.