The widespread use of nanostructures and nanomaterials has opened up a whole new realm of challenges in thermal management, but also leads to possibilities for energy conversion, storage, and generation, in addition to numerous other technological applications. At the microscale and below, standard thermal measurement techniques reach their limits, and several novel methods have been developed to overcome these limitations. Among the most recent, contactless photothermal methods have been widely used and have proved their advantages in terms of versatility, temporal and spatial resolution, and even sensitivity in some situations. Among them, thermoreflectance and Raman thermometry have been used to measure the thermal properties from bulk materials to thin films, multilayers, suspended structures, and nanomaterials. This Tutorial presents the principles of these two techniques and some of their most common implementations. It expands to more advanced systems for spatial mapping and for probing of non-Fourier thermal transport. Finally, this paper concludes with discussing the limitations and perspectives of these techniques and future directions in nanoscale thermometry.

In organic electronics, thermal management is a challenge, as most organic materials conduct heat poorly. As these devices become smaller, thermal transport is increasingly limited by organic–inorganic interfaces, for example that between a metal and a polymer. However, the mechanisms of heat transport at these interfaces are not well understood. In this work, we compare three types of metal–polymer interfaces. Polymethyl methacrylate (PMMA) films of different thicknesses (1–15 nm) were spin-coated on silicon substrates and covered with an 80 nm gold film either directly, or over an interface layer of 2 nm of an adhesion promoting metal—either titanium or nickel. We use the frequency-domain thermoreflectance (FDTR) technique to measure the effective thermal conductivity of the polymer film and then extract the metal–polymer thermal boundary conductance (TBC) with a thermal resistance circuit model. We found that the titanium layer increased the TBC by a factor of 2, from 59 × 10⁶ W·m⁻²·K⁻¹ to 115 × 10⁶ W·m⁻²·K⁻¹, while the nickel layer increased TBC to 139 × 10⁶ W·m⁻²·K⁻¹. These results shed light on possible strategies to improve heat transport in organic electronic systems.

This article presents a dataset for a Norwegian industrial medium voltage (MV) and low voltage (LV) electric power distribution grid with load time series. The raw dataset was collected in collaboration with the Norwegian distribution grid company (DSO1) Norgesnett as part of a pilot project in the Norwegian research centre CINELDI and was later anonymized and simplified into a secondary dataset, presented here. The load dataset comprises over three years of measurements of hourly load demand from 45 grid customers in the time period 2019-03-01 to 2022-03-16, collected from smart meters installed with the customers. The grid data comprises 2 radials of the distribution grid, collected from the network information system of the DSO. The data was anonymized and simplified. The dataset can be used for stochastic load modelling, analysing the grid's need for flexibility and power flow analyses for grid planning purposes.

The thermal imaging of surfaces with microscale spatial resolution over micro-sized areas remains a challenging and time-consuming task. Surface thermal imaging is a very important characterization tool in mechanical engineering, microelectronics, chemical process engineering, optics, microfluidics, and biochemistry processing, among others. Within the realm of electronic circuits, this technique has significant potential for investigating hot spots, power densities, and monitoring heat distributions in complementary metal–oxide–semiconductor (CMOS) platforms. We present a new technique for remote non-invasive, contactless thermal field mapping using synchrotron radiation-based Fourier-transform infrared microspectroscopy. We demonstrate a spatial resolution better than 10 um over areas on the order of 12,000 um² measured in a polymeric thin film on top of CaF₂ substrates. Thermal images were obtained from infrared spectra of poly(methyl methacrylate) thin films heated with a wire. The temperature dependence of the collected infrared spectra was analyzed via linear regression and machine learning algorithms, namely random forest and k-nearest neighbor algorithms. This approach speeds up signal analysis and allows for the generation of hyperspectral temperature maps. The results here highlight the potential of infrared absorbance to serve as a remote method for the quantitative determination of heat distribution, thermal properties, and the existence of hot spots, with implications in CMOS technologies and other electronic devices.

Traditional power grid planning is based on passive measures such as reinforcing the grid and using present value to compare different grid development plans. However, this approach does not accurately describe the real options value of using active measures, such as energy storage or demand-side load shifting, for postponing grid reinforcement through a “wait-and-see” approach to handle uncertainty in long-term load growth. However, the value of using active measures may come at the price of reducing the security margins in grid operation. This leads to an increased risk of problems during grid operation, and this risk must be weighed against the value of using active measures. This paper presents a methodology for quantifying both the value and risk (or price) of real options related to grid development strategies using active measures, providing grid planners with more comprehensive information about the advantages and disadvantages. The methodology is demonstrated using an illustrative and simple case for a medium voltage reference distribution system, where flexibility from local energy communities is considered as an example of an active measure. The case study illustrates how some risk-taking is required to realize the value from using active measures.

The bidirectional 3$\omega$ method is an electrothermal technique that is commonly used to obtain the thermal conductivity of materials such as liquids, biological samples, and pastes. In this work, an epoxy-based adhesive was filled with monodisperse 10 μm polymethyl methacrylate spheres coated with silver thin films (AgPS), such that a metallic network that dominated the thermal transport was formed through the composite. The bidirectional 3$\omega$ method was used to obtain the thermal conductivity of the conductive adhesive at different volume fractions of AgPS. For 50 vol.% AgPS, corresponding to 3.4 vol.% silver, the thermal conductivity was $2.03\pm 0.21$ W m⁻¹ K⁻¹. The results show that the thermal conductivity is strongly correlated with the AgPS volume fraction, while maintaining a volume fraction of silver far below the commercial silver paste, which has typical filler fractions of 40 vol.% silver. The results of this work were compared to thermal measurements of the same material by other techniques, and advantages and disadvantages of the methods were finally discussed.