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Highly responsive organic photodetectors allow a plethora of applications in fields like imaging, health, security monitoring, etc. Photomultiplication‐type organic photodetectors (PM‐OPDs) are a desirable option due to their internal amplification mechanism. However, for such devices, significant gain and low dark currents are often mutually excluded since large operation voltages often induce high shot noise. Here, a fully vacuum‐processed PM‐OPD is demonstrated using trap‐assisted electron injection in BDP‐OMe:C60 material system. By applying only −1 V, compared with the self‐powered working condition, the responsivity is increased by one order of magnitude, resulting in an outstanding specific detectivity of ≈1013 Jones. Remarkably, the superior detectivity in the near‐infrared region is stable and almost voltage‐independent up to −10 V. Compared with two photovoltaic‐type photodetectors, these PM‐OPDs exhibit the great potential to be easily integrated with state‐of‐the‐art readout electronics in terms of their high responsivity, fast response speed, and bias‐independent specific detectivity. The employed vacuum fabrication process and the easy‐to‐adapt PM‐OPD concept enable seamless upscaling of production, paving the way to a commercially relevant photodetector technology. A fully vacuum‐processed photomultiplication‐type organic photodetector for near‐infrared (NIR) sensing with high and bias‐independent specific detectivity is achieved by efficient trap‐assisted electron injection. More than 100% external quantum efficiency is exhibited at only −1 V. For the NIR light, an impressive specific detectivity ≈1013 Jones can almost be voltage‐independent up to −10 V, indicating their potential in state‐of‐the‐art readout electronics.

Submarine groundwater discharge (SGD) in volcanic areas commonly exhibits high temperatures, concentrations of metals and CO2, and acidity, all of which could affect sensitive coastal ecosystems. Identifying and quantifying volcanic SGD is crucial yet challenging because the SGD might be both discrete, through fractured volcanic rock, and diffuse. At a volcanic area in the Philippines, the novel combination of satellite and drone‐based thermal infrared remote sensing, ground‐based fiber‐optic distributed temperature sensing, and in situ thermal profiling in coastal sediment identified the multi‐scale nature of SGD and quantified fluxes. We identified SGD across ∼30 km of coastline. The different approaches revealed numerous SGD signals from the intertidal zone to about a hundred meters offshore. In active seepage areas, temperatures peaked at 80°C, and Darcy fluxes were as high as 150 cm/d. SGD is therefore locally prominent and regionally important across the study area. Plain Language Summary Submarine groundwater discharge (SGD) is the flow of groundwater from land to sea. SGD in volcanic areas can have high temperatures, high concentrations of heavy metals, high CO2, and can be acidic, all of which impact sensitive coastal ecosystems. Quantifying volcanic SGD is important yet challenging because the flow can be diffuse and broadly distributed. At a volcanic area in the Philippines, the unique combination of satellite and drone‐based thermal infrared remote sensing, ground‐based fiber‐optic distributed temperature sensing, and in situ thermal profiling in coastal sediment identified the multi‐scale nature of SGD and quantified flow rates. We identified SGD across ∼30 km of coastline. The different approaches revealed numerous SGD signals from the intertidal zone (the region between high and low tide) to about a hundred meters offshore. At some locations, active seepage areas reached temperatures up to 80°C, and we calculated groundwater flow rates to be as high as 150 cm/day. SGD is therefore locally prominent and regionally important across the study area. Key Points Multi‐scale thermal submarine groundwater discharge (SGD) was mapped in a volcanic area with coral reefs and marine protected areas Thermal SGD was prevalent in the area with both broadly diffuse signals and pronounced discrete discharge Local SGD reached 150 cm/d and 80°C

Up-conversion sensing based on optical heterodyning of an IR (infrared) image with a local oscillator laser wave in a nonlinear optical sum-frequency mixing (SFM) process is a practical solution to circumvent some limitations of IR image sensors in terms of signal-to-noise ratio, speed, resolution, or cooling needs in some demanding applications. In this way, the spectral content of an IR image can become spectrally shifted to the visible/near infrared (VIS/NWIR) and then detected with silicon focal plane arrayed sensors (Si-FPA), such as CCD/CMOS (charge-coupled and complementary metal-oxide-semiconductor devices). This work is an extension of a previous study where we recently introduced this technique in the context of optical communications, in particular in FSOC (free-space optical communications). Herein, we present an image up-conversion system based on a 1064 nm Nd3+: YVO4 solid-state laser with a KTP (potassium titanyl phosphate) nonlinear crystal located intra-cavity where a laser beam at 1550 nm 2D spatially-modulated with a binary Quick Response (QR) code is mixed, giving an up-converted code image at 631 nm that is detected with an Si-based camera. The underlying technology allows for the extension of other IR spectral allocations, construction of compact receivers at low cost, and provides a natural way for increased protection against eavesdropping.

The Polar Radiant Energy in the Far‐InfraRed Experiment (PREFIRE) was selected by NASA to fly two miniaturized Thermal InfraRed Spectrometers (TIRS) capable of distinguishing the spectral signatures of surface and atmospheric properties in Earth's polar regions. A trade study examining spectral sampling as well as separation of cloudy and clear scenery at 20 km scales highlighted the possibility to utilize ambient (uncooled) detector technologies in a miniaturized spectrometer that could facilitate low‐cost and rapid access to space. This work describes the design, implementation, testing and performance of two TIRS systems, as well as the challenges and acceptable limitations of the cost‐constrained effort, that feature the novel joining of compact thermopile array technologies with concentric imaging spectrometry methods. The TIRS systems presented here each have 2.7 kg mass, draw 4.3 W power, and provide spectral resolution of 1.71 μ${\\upmu }$ m below 35 μ${\\upmu }$ m sampled at 0.86 μ${\\upmu }$ m increments. Plain Language Summary Earth absorbs energy emitted by the Sun, radiating some of that as heat back into space. The energy exchange between Earth and space drives weather and climate. Scientists measure and track this energy using satellite instruments that can identify which parts of Earth's surface and atmosphere emit specific portions of the overall heat radiated into space. But these instruments are complicated and expensive, and until now, no one has built a sensor that can look at and separate all of Earth's heat emissions in a systematic way. The Polar Radiant Energy in the Far‐InfraRed Experiment (PREFIRE) has developed a novel instrument that combines simple, miniaturized heat sensors with specially shaped optics and microelectronics to provide such measurements to further our understanding of the planet's weather and climate. Furthermore, implementation of the sensors has been done within a cost‐capped mission profile that encourages development of a sustainable sensor system for Earth monitoring. This manuscript describes the instrument design, including its components and their characteristics, the system and its functionality, its trade‐offs, cost limitations, and testing and performance information. PREFIRE began operating two of these instruments in space in 2024, in order to start quantifying the heat exchange processes in Earth's polar regions. Key Points Instrumentation for low‐cost, broadband spectral thermal imaging has been developed for spaceflight Thermal radiances across the majority of the Planck function can be quantified in a single polychromatic imager We are poised to disentangle biases in polar radiometric processes to improve predictive capabilities of local and global climate models

Quantum geometric properties of Bloch wave functions in solids, that is, Berry curvature and the quantum metric, are known to significantly influence the ground- and excited-state behaviour of electrons 1 – 5 . The bulk photovoltaic effect (BPVE), a nonlinear phenomenon depending on the polarization of excitation light, is largely governed by the quantum geometric properties in optical transitions 6 – 10 . Infrared BPVE has yet to be observed in graphene or moiré systems, although exciting strongly correlated phenomena related to quantum geometry have been reported in this emergent platform 11 – 14 . Here we report the observation of tunable mid-infrared BPVE at 5 µm and 7.7 µm in twisted double bilayer graphene (TDBG), arising from the moiré-induced strong symmetry breaking and quantum geometric contribution. The photoresponse depends substantially on the polarization state of the excitation light and is highly tunable by external electric fields. This wide tunability in quantum geometric properties enables us to use a convolutional neural network 15 , 16 to achieve full-Stokes polarimetry together with wavelength detection simultaneously, using only one single TDBG device with a subwavelength footprint of merely 3 × 3 µm 2 . Our work not only reveals the unique role of moiré engineered quantum geometry in tunable nonlinear light–matter interactions but also identifies a pathway for future intelligent sensing technologies in an extremely compact, on-chip manner. Tunable quantum geometric properties of moiré graphene enable the use of a convolutional neural network to simultaneously decipher the light polarization, power and wavelength in a subwavelength-scale smart device.

Infrared (IR) sensors are widely used in various applications due to their ability to detect infrared radiation. Currently, infrared detector technology is in its third generation and faces enormous challenges. IR radiation propagation is categorized into distinct transmission windows with the most intriguing aspects of thermal imaging being mid-wave infrared (MWIR) and long-wave infrared (LWIR). Infrared detectors for thermal imaging have many uses in industrial applications, security, search and rescue, surveillance, medical, research, meteorology, climatology, and astronomy. Presently, high-performance infrared imaging technology mostly relies on epitaxially grown structures of the small-bandgap bulk alloy mercury–cadmium–telluride (MCT), indium antimonide (InSb), and GaAs-based quantum well infrared photodetectors (QWIPs), contingent upon the application and wavelength range. Nanostructures and nanomaterials exhibiting appropriate electrical and mechanical properties including two-dimensional materials, graphene, quantum dots (QDs), quantum dot in well (DWELL), and colloidal quantum dot (CQD) will significantly enhance the electronic characteristics of infrared photodetectors, transition metal dichalcogenides, and metal oxides, which are garnering heightened interest. The present manuscript gives an overview of IR sensors, their types, materials commonly used in them, and examples of related applications. Finally, a summary of the manuscript and an outlook on prospects are given.

Mineral dust absorbs and scatters solar and infrared radiation, thereby affecting the radiance spectrum at the surface and top-of-atmosphere and the atmospheric heating rate. While half of the outgoing thermal radiation is emitted in the far infrared (FIR, 15–100 µm), knowledge of the optical properties and thermal radiative effects of dust is currently limited to the mid-infrared region (MIR, 3–15 µm). In this study we performed pellet spectroscopy measurements to evaluate the MIR and FIR contribution to dust absorbance and explore the variability and spectral diversity of the dust signature within the 2.5–25 µm range. Thirteen dust samples re-suspended from parent soils with contrasting mineralogy were investigated, including low and mid latitude dust (LMLD) sources in Africa, America, Asia, and Middle East, and high latitude dust (HLD) from Iceland. Results show that the absorbance of dust in the FIR up to 25 µm is comparable in intensity to that in the MIR. Also, spectrally different absorption (position and shape of the peaks) is observed for Icelandic dust compared to LMLD, due to differences in mineralogical composition. Corroborated with the few available literature data on absorption properties of natural dust and single minerals up to 100 µm wavelength, these data suggest the relevance of MIR and FIR interactions to the dust radiative effect for low to high latitude sources. Furthermore, the dust spectral signatures in the MIR and FIR could potentially be used to characterise the mineralogy and differentiate the origin of airborne particles based on infrared remote sensing observations.

Land surface temperature (LST) is a key variable within Earth's climate system and a necessary input parameter required by numerous land–atmosphere models. It can be directly retrieved from satellite thermal infrared (TIR) observations, which contain many invalid pixels mainly caused by cloud contamination. To investigate the spatial and temporal variations in LST in China, long-term, high-quality, and spatiotemporally continuous LST datasets (i.e., all-weather LST) are urgently needed. Fusing satellite TIR LST and reanalysis datasets is a viable route to obtain long time-series all-weather LSTs. Among satellite TIR LSTs, the MODIS LST is the most commonly used, and a few corresponding all-weather LST products have been reported recently. However, the publicly reported all-weather LSTs were not available during the temporal gaps of MODIS between 2000 and 2002. In this study, we generated a daily (four observations per day) 1 km all-weather LST dataset for China's landmass and surrounding areas, the Thermal and Reanalysis Integrating Moderate-resolution Spatial-seamless (TRIMS) LST, which begins on the first day of the new millennium (1 January 2000). We used the enhanced reanalysis and thermal infrared remote sensing merging (E-RTM) method to generate the TRIMS LST dataset with the temporal gaps being filled, which had not been achieved by the original RTM method. Specifically, we developed two novel approaches, i.e., the random-forest-based spatiotemporal merging (RFSTM) approach and the time-sequential LST-based reconstruction (TSETR) approach, respectively, to produce Terra/MODIS-based and Aqua/MODIS-based TRIMS LSTs during the temporal gaps. We also conducted a thorough evaluation of the TRIMS LST. A comparison with the Global Land Data Assimilation System (GLDAS) and ERA5-Land LST demonstrates that the TRIMS LST has similar spatial patterns but a higher image quality, more spatial details, and no evident spatial discontinuities. The results outside the temporal gap show consistent comparisons of the TRIMS LST with the MODIS LST and the Advanced Along-Track Scanning Radiometer (AATSR) LST, with a mean bias deviation (MBD) of 0.09/0.37 K and a standard deviation of bias (SD) of 1.45/1.55 K. Validation based on the in situ LST at 19 ground sites indicates that the TRIMS LST has a mean bias error (MBE) ranging from −2.26 to 1.73 K and a root mean square error (RMSE) ranging from 0.80 to 3.68 K. There is no significant difference between the clear-sky and cloudy conditions. For the temporal gap, it is observed that RFSTM and TSETR perform similarly to the original RTM method. Additionally, the differences between Aqua and Terra remain stable throughout the temporal gap. The TRIMS LST has already been used by scientific communities in various applications such as soil moisture downscaling, evapotranspiration estimation, and urban heat island modeling. The TRIMS LST is freely and conveniently available at https://doi.org/10.11888/Meteoro.tpdc.271252 (Zhou et al., 2021).

Sea ice leads play an important role in the heat exchange between the ocean and the overlying atmosphere, particularly narrow leads with widths of less than 100 m. We present a method for detecting sea ice leads in the Arctic using high-resolution infrared images from the Thermal Infrared Spectrometer (TIS) on board the Sustainable Development Science Satellite 1 (SDGSAT-1), with a resolution of 30 m in a swath of 300 km. With the spatial resolution of leads observed by infrared remote sensing increasing to tens of meters, focused on the Beaufort Sea cases in April 2022, the TIS-detected leads achieve good agreement with Sentinel-2 visible images. For the three infrared bands of the TIS, the B2 (10.3–11.3 µm) and B3 (11.5–12.5 µm) bands show similar performance in detecting leads. The B1 band (8.0–10.5 µm) can be usefully complementary to the other two bands, as a result of different temperature measurement sensitivity. Combining the detected results from the three TIS bands, the TIS is able to detect more leads with widths less than hundreds of meters compared to the Moderate Resolution Imaging Spectroradiometer (MODIS). Our results demonstrate that SDGSAT-1 TIS data at 30 m resolution can effectively observe previously unresolvable sea ice leads, providing new insight into the contribution of narrow leads to rapid sea ice changes in the Arctic.