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Climate change is arguably the greatest environmental challenge facing humankind in the twenty-first century. The United Nations Framework Convention on Climate Change (UNFCCC) facilitates multilateral action to combat climate change and its impacts on humanity and ecosystems. To make decisions on climate change mitigation and adaptation, the UNFCCC requires systematic observations of the global climate system.The objective of the ESA’s climate programme, currently delivered via the Climate Change Initiative (CCI), is to realise the full potential of the long-term, global-scale, satellite earth observation archive that ESA and its Member States have established over the last 35 years, as a significant and timely contribution to the climate data record required by the UNFCCC.Since 2010, the programme has contributed to a rapidly expanding body of scientific knowledge on >22 Essential Climate Variables (ECVs), through the production of Climate Data Records (CDRs). Although varying across geophysical parameters, ESA CDRs follow community-driven data standards, facilitating inter- and cross-ECV research of the climate system.In this work, we highlight the use of artificial intelligence (AI) in the context of the ESA CCI. AI has played a pivotal role in the production and analysis of these Climate Data Records. Eleven CCI projects - Greenhouse Gases (GHG), Aerosols, Clouds, Fire, Ocean Colour, Sea Level, Soil Moisture, High Resolution Landcover, Biomass, Permafrost, and Sea Surface Salinity - have applied AI in their data record production and research or have identified specific AI usage for their research roadmaps.The use of AI in these CCI projects is varied, for example - GHG CCI algorithms using random forest machine learning techniques; Aerosol CCI algorithms to retrieve dust aerosol optical depth from thermal infrared spectra; Fire CCI algorithms to detect burned areas. Moreover, the ESA climate community has identified climate science gaps in context to ECVs with the potential for meaningful advancement through AI.We specifically focus on showcasing the use of AI for data homogenization and super-resolution of ESA CCI datasets. For instance, both the land cover and fire CCI dataset were generated globally in low resolution, while high resolution data only exists for specific geographical regions. By adapting super-resolution algorithms to the specific science use cases, we can accelerate the generation of global, high-resolution datasets with the required temporal coverage to support long-term climate studies.

To understand the solar evolution and effects of solar eruptive events, the Sun is permanently observed by multiple satellite missions. The optically-thin emission of the solar plasma and the limited number of viewpoints make it challenging to reconstruct the geometry and structure of the solar atmosphere; however, this information is the missing link to understand the Sun as it is: a three-dimensional, evolving star. We present a method that enables a complete 3D representation of the uppermost solar layer (corona) observed in extreme ultraviolet (EUV) light. We use a deep learning approach for 3D scene representation that accounts for radiative transfer, to map the entire solar atmosphere from three simultaneous observations. We demonstrate that our approach provides unprecedented reconstructions of the solar poles, and directly enables height estimates of coronal structures, solar flux ropes, coronal hole profiles, and coronal mass ejections. We validate the approach using model-generated synthetic EUV images, finding that our method accurately captures the 3D geometry even from a limited number of viewpoints. We quantify uncertainties of our model using an ensemble approach that allows us to estimate the model performance in absence of a ground-truth. Our method enables a novel view of our closest star, and is a breakthrough technology for the efficient use of multi-instrument datasets, which paves the way for future cluster missions.

Free charge generation in organic solar cells generally proceeds via (1) the formation of charge transfer (CT) excitons after photoexcitation of donor or acceptor molecules, and (2) CT dissociation into the charge separated (CS) state. While the efficiency of CT formation depends on the energetic difference between local excitation (LE) singlet and CT states, the CT dissociation efficiency is determined by the energetic barrier between the CT and CS states. For a long time, research either studied the combined effect of CT formation and dissociation on photocurrents without distinguishing the individual processes, or primarily focused on understanding and improving CT formation to increase photocurrents, neglecting the efficiency of CT dissociation all-together. In this work, we provide evidence that CT dissociation rather than CT formation presents a major bottleneck for free charge generation in fullerene-based blends with low energetic offsets between LE and CT states. We fabricate devices based on dilute donor content blends of ZnPc or its fluorinated derivatives and C60. Fluorination of ZnPc simultaneously shifts the molecular orbitals away from the vacuum level, increasing the CT state energy at the donor-acceptor interface with C60. Through experimental device characterization, density functional theory (DFT) calculations, and time-resolved electron paramagnetic resonance (trEPR) measurements, we draw a comprehensive picture of how LE, CT, and CS state energies and the transitions among states change upon fluorination of ZnPc. We find that, upon fluorination of ZnPc, primarily CT dissociation decreases, resulting in a significant decrease in the photocurrents of the blends.

Vacuum-thermal evaporation (VTE) is a highly relevant fabrication route for organic solar cells (OSCs), especially on an industrial scale as proven by the commercialisation of organic light emitting diode (OLED) based displays. While OSC performance is reported for a range of VTE-deposited molecules, a comprehensive assessment of donor:acceptor blend properties with respect to their photovoltaic performance is scarce. Here, we fabricate organic thin films and solar cells of three select systems and measure ellipsometry, external quantum efficiency with high dynamic range, as well as OTRACE to quantify absorption, voltage losses, and charge carrier mobility. These parameters are key to explain OSC performance and will help to rationalize the performance of other material systems reported in literature as our methodology is applicable beyond VTE systems. Furthermore, it could help to judge the prospects of new molecules in general. We find large differences in the measured values and find that today's VTE OSCs can reach high extinction coefficients, but only moderate mobility and voltage loss compared to their solution-processed counterparts. We outline what needs to improve for VTE organic solar cells to again catch up with their solution-processed counterparts in terms of power conversion efficiency. This article is protected by copyright. All rights reserved.

Elucidating the interplay between film morphology, photophysics, and device performance of bulk heterojunction (BHJ) organic photovoltaics remains challenging. Here, we use the well-defined morphology of vapor-deposited di-[4-(N,N-di-p-tolyl-amino)-phenyl]cyclohexane (TAPC):C60 blends to address charge generation and recombination by transient ultrafast spectroscopy. We gain relevant new insights to the functioning of dilute-donor (5% TAPC) fullerene-based BHJs compared to molecularly intermixed systems (50% TAPC). First, we show that intermolecular charge-transfer (CT) excitons in the C60 clusters of dilute BHJs rapidly localize to Frenkel excitons prior to dissociating at the donor:acceptor interface. Thus, both Frenkel and CT excitons generate photocurrent over the entire fullerene absorption range. Second, we selectively monitor interfacial and bulk C60 clusters via their electro-absorption, demonstrating an energetic gradient that assists free charge generation. Third, we identify a fast (

Elucidating the interplay between film morphology, photophysics, and device performance of bulk heterojunction (BHJ) organic photovoltaics remains challenging. Here, we use the well-defined morphology of vapor-deposited di-[4-(

A correct determination of voltage losses is crucial for the development of organic solar cells (OSCs) with improved performance. This requires an in-depth understanding of the properties of interfacial charge transfer (CT) states, which not only set the upper limit for the open-circuit voltage of a system, but also govern radiative and non-radiative recombination processes. Over the last decade, different approaches have emerged to classify voltage losses in OSCs that rely on a generic detailed balance approach or additionally include CT state parameters that are specific to OSCs. In the latter case, a correct determination of CT state properties is paramount. In this work, we summarize the different frameworks used today to calculate voltage losses and provide an in-depth discussion of the currently most important models used to characterize CT state properties from absorption and emission data of organic thin films and solar cells. We also address practical concerns during the data recording, analysis, and fitting process. Departing from the classical two-state Marcus theory approach, we discuss the importance of quantized molecular vibrations and energetic hybridization effects in organic donor-acceptor systems with the goal to providing the reader with a detailed understanding of when each model is most appropriate.

Stability is now a critical factor in the commercialization of organic photovoltaic (OPV) devices. Both extrinsic stability to oxygen and water and intrinsic stability to light and heat in inert conditions must be achieved. Triplet states are known to be problematic in both cases, leading to singlet oxygen production or fullerene dimerization. The latter is thought to proceed from unquenched singlet excitons that have undergone intersystem crossing (ISC). Instead, we show that in bulk heterojunction (BHJ) solar cells the photo-degradation of C60 via photo-oligomerization occurs primarily via back-hole transfer (BHT) from a charge-transfer state to a C60 excited triplet state. We demonstrate this to be the principal pathway from a combination of steady-state optoelectronic measurements, time-resolved electron paramagnetic resonance, and temperature-dependent transient absorption spectroscopy on model systems. BHT is a much more serious concern than ISC because it cannot be mitigated by improved exciton quenching, obtained for example by a finer BHJ morphology. As BHT is not specific to fullerenes, our results suggest that the role of electron and hole back transfer in the degradation of BHJs should also be carefully considered when designing stable OPV devices., The commercialisation of organic photovoltaic technology calls for research on material degradation mechanisms. Ramirez et al. show that triplet excitons produced by back charge transfer can significantly impact the photo-stability of fullerene-based devices even in the absence of water and oxygen.