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In recent years, significant efforts have been directed toward adapting modern neural network architectures for tabular data. However, despite their larger number of parameters and longer training and inference times, these models often…
Solar irradiance forecasts can be dynamic and unreliable due to changing weather conditions. Near the Arctic circle, this also translates into a distinct set of further challenges. This work is forecasting solar irradiance with Norwegian…
This study presents novel predictive models using Graph Neural Networks (GNNs) for simulating thermal dynamics in Laser Powder Bed Fusion (L-PBF) processes. By developing and validating Single-Laser GNN (SL-GNN) and Multi-Laser GNN (ML-GNN)…
Photovoltaics (PV) are widely used to harvest solar energy, an important form of renewable energy. Photovoltaic arrays consist of multiple solar panels constructed from solar cells. Solar cells in the field are vulnerable to various…
We present describe a new computer code that solves the radiative transfer problem on multi-resolution grids. If the cloud model is from an MHD simulation on a regular cartesian grid, criteria based for example on local density or velocity…
Single-junction photovoltaic cells are considered to be efficient solar energy converters, but even ideal cells cannot exceed the their fundamental thermodynamic efficiency limit, first analysed by Shockley and Queisser (SQ). For moderated…
Low-light image enhancement (LLIE) aims to improve the visibility of images captured in poorly lit environments. Prevalent event-based solutions primarily utilize events triggered by motion, i.e., ''motion events'' to strengthen only the…
Solar irradiance clustering can enhance solar power capacity planning and help improve forecasting models by identifying similar irradiance patterns influenced by seasonal and weather changes. In this study, we adopt an efficient two-level…
Electricity grid's resiliency and climate change strongly impact one another due to an array of technical and policy-related decisions that impact both. This paper introduces a physics-informed machine learning-based framework to enhance…
Partial shading in photovoltaic modules is an important reliability and performance concern for all photovoltaic technologies. In this paper, we show how cell geometry can be used as a design variable for improved performance and resilience…
Global and regional climate model projections are useful for gauging future patterns of climate variables, including solar radiation, but data from these models is often too coarse to assess local impacts. Within the context of solar…
While transient photoluminescence measurements are a very popular tool to monitor the charge-carrier dynamics in the field of halide perovskite photovoltaics, interpretation of data obtained on multilayer samples is highly challenging due…
Context. Extreme ultraviolet (EUV) late-phase (ELP) flares exhibit a second peak in warm coronal emissions minutes to hours after the main peak of the flare. This phase is all but negligible, and it is still poorly understood what role it…
This paper presents a tunable liquid lens (TLL)-assisted indoor mobile visible light communication system. To mitigate performance degradation caused by user mobility and random receiver orientation, an electrowetting cuboid TLL is used at…
Photovoltaic (PV) power forecasting in edge-enabled grids requires balancing forecasting accuracy, robustness under weather-driven distribution shifts, and strict latency constraints. Existing models work well under normal conditions but…
Despite the success of machine learning (ML) in surrogate modeling, its use in radiation dose assessment is limited by safety-critical constraints, scarce training-ready data, and challenges in selecting suitable architectures for…
Drones have become indispensable assets during human-made and natural disasters, offering damage assessment, aid delivery, and communication restoration capabilities. However, most drones rely on batteries that require frequent recharging,…
We test our knowledge of the atomic opacity in the solar UV spectrum. Using the atomic data compiled in Paper I from modern, publicly available, databases, we perform calculations that are confronted with space-based observations of the…
This work presents a set of optimal machine learning (ML) models to represent the temporal degradation suffered by the power conversion efficiency (PCE) of polymeric organic solar cells (OSCs) with a multilayer structure…
Halide perovskites have emerged as promising candidates for high-performance solar cells. This study investigates the temperature-dependent optoelectronic properties of mixed-cation mixed-halide perovskite solar cells using…