Shortwave Infrared Research Articles

Freeform-surface-based optical design of a broadband compressive spectral imager with co-aperture coding

Compressive spectral imaging (CSI) is an advanced computational imaging approach to reconstruct the three-dimensional (3D) spatio-spectral data cube of a target scene through a single or a few snapshots. However, limited by the response range of the image detector, the existing CSI systems mostly work within narrow spectral bands, such as the visible or shortwave-infrared (SWIR) spectral band. The work band of the CSI system constrains the detection capacity for the targets under complex environments (such as rain, snow, haze, etc.). In addition, most of the current CSI prototypes lack engineering design for practical applications. This paper develops a novel, to the best of our knowledge, optical design scheme of a broadband CSI system with co-aperture coding to simultaneously realize visible multi-spectral imaging (10 channels) and SWIR super-resolution imaging (16×). The freeform surfaces are used to design the front-end reflective objective lens, thus significantly improving the image quality and spatial modulation precision of the system. By means of performance evaluation and tolerance analysis, excellent image quality and manufacturability of the proposed system are demonstrated.

Use of bioresorbable fibers for short-wave infrared spectroscopy using time-domain diffuse optics.

We demonstrate the usability of bioresorbable phosphate glass fibers for time-domain diffuse optical spectroscopy (TD-DOS) in the short-wave infrared (SWIR) region of 950-1600 nm, with the use of an InGaAs detector. Bioresorbable fibers for diffuse optics present an exciting prospect due to their ability to be left implanted while retrieving optical properties from deeper regions (few cm) for monitoring treatments. Extending TD-DOS to the SWIR region could be useful to better identify biomarkers such as water, lipids and collagen, given their increase in absorption in this range. We attempt to use the bioresorbable fibers to spectrally identify these biomarkers by measuring a series of biological samples known to contain them, such as porcine muscle, porcine fat and bone. We further validate our measurements by comparing the optical properties of high-scattering solid silicone phantoms retrieved with these bioresorbable fibers with those by a standard Si fiber.

Ultrasmall HgTe Quantum Dots with Near-Unity Photoluminescent Quantum Yields in the Near and Shortwave Infrared

Ultrasmall HgTe Quantum Dots with Near-Unity Photoluminescent Quantum Yields in the Near and Shortwave Infrared

Preliminary Assessment of On-Orbit Radiometric Calibration Challenges in NOAA-21 VIIRS Reflective Solar Bands (RSBs)

The National Oceanic and Atmospheric Administration (NOAA) 21 Visible Infrared Imaging Radiometer Suite (VIIRS) was successfully launched on 10 November 2022. To ensure the required instrument performance, a series of Post-Launch Tests (PLTs) were performed and analyzed. The primary calibration source for NOAA-21 VIIRS Reflective Solar Bands (RSBs) is the Solar Diffuser (SD), which retains the prelaunch radiometric calibration standard from prelaunch to on-orbit. Upon reaching orbit, the SD undergoes degradation as a result of ultraviolet solar illumination. The rate of SD degradation (called the H-factor) is monitored by a Solar Diffuser Stability Monitor (SDSM). The initial H-factor’s instability was significantly improved by deriving a new sun transmittance function from the yaw maneuver and one-year SDSM data. The F-factors (normally represent the inverse of instrument gain) thus calculated for the Visible/Near-Infrared (VISNIR) bands were proven to be stable throughout the first year of the on-orbit operations. On the other hand, the Shortwave Infrared (SWIR) bands unexpectedly showed fast degradation, which is possibly due to unknown substance accumulation along the optical path. To mitigate these SWIR band gain changes, the NOAA VIIRS Sensor Data Record (SDR) team used an automated calibration software package called RSBautoCal. In March 2024, the second middle-mission outgassing event to reverse SWIR band degradation was shown to be successful and its effects are closely monitored. Finally, the deep convective cloud trends and lunar collection results validated the operational F-factors. This paper summarizes the preliminary on-orbit radiometric calibration updates and performance for the NOAA-21 VIIRS SDR products in the RSB.

Non-invasive exploration of malting barley (Hordeum vulgare) in vitro germination and varietal effects using short wave infrared spectral imaging and ANOVA simultaneous component analysis

ANOVA-simultaneous component analysis (ASCA) was applied to short-wave infrared spectral fingerprints of 5 malting barley varieties collected using a hyperspectral imaging system to determine the effect of germination, the influence of time and the influence of barley by means of a full factorial experimental design. ASCA indicated that there was a significant (p < 0.0001) effect of the germination status, the germination time and interaction on the spectral data for all varieties. The biochemical and physiological modification of the samples were characterised by visualisation of the longitudinal scores obtained from simultaneous component analysis for the germination time factor. This resulted in the visualisation and explanation of biochemical change over the course of barley germination as a factor of time. The relevant loadings indicated a significant change to the proteome, lipid and starch structure as driven by the uptake of water over time. The ASCA model were extrapolated to include the effect of barley variety to the already mentioned germination status and germination time factors, resulting once again in all the effects being significant (p < 0.0001). Here it was shown that all the barley varieties are significantly different from one another pre- and post-modification, based on the molecular vibrations observed in the short wave-infrared (SWIR) spectra, suggesting that the detection of biotic stress factors, such as pre-harvest germination, also differ for each variety, by indicating that the germination profile of each barley variety varies as a function of germination time. Thus, also the malting performance, germinative energy and chemical profile of each barley variety tested will vary before, during and after imbibition and germination – indicating the importance of malting commercial barley malt true to variety. These results indicate that (SWIR) spectral imaging instrumentation can possibly be used to monitor controlled germination of barley grain. Due to the shown ability of SWIR spectral imaging to detect small biochemical changes over time of barley grain during germination.

Room-Temperature (RT) Extended Short-Wave Infrared (e-SWIR) Avalanche Photodiode (APD) with a 2.6 µm Cutoff Wavelength.

Highly sensitive infrared photodetectors are needed in numerous sensing and imaging applications. In this paper, we report on extended short-wave infrared (e-SWIR) avalanche photodiodes (APDs) capable of operating at room temperature (RT). To extend the detection wavelength, the e-SWIR APD utilizes a higher indium (In) composition, specifically In0.3Ga0.7As0.25Sb0.75/GaSb heterostructures. The detection cut-off wavelength is successfully extended to 2.6 µm at RT, as verified by the Fourier Transform Infrared Spectrometer (FTIR) detection spectrum measurement at RT. The In0.3Ga0.7As0.25Sb0.75/GaSb heterostructures are lattice-matched to GaSb substrates, ensuring high material quality. The noise current at RT is analyzed and found to be the shot noise-limited at RT. The e-SWIR APD achieves a high multiplication gain of M~190 at a low bias of Vbias=- 2.5 V under illumination of a distributed feedback laser (DFB) with an emission wavelength of 2.3 µm. A high photoresponsivity of R>140 A/W is also achieved at the low bias of Vbias=-2.5 V. This type of highly sensitive e-SWIR APD, with a high internal gain capable of RT operation, provides enabling technology for e-SWIR sensing and imaging while significantly reducing size, weight, and power consumption (SWaP).

Enhanced SWIR Light Detection in Organic Semiconductor Photodetectors through Up-Conversion of Mid-Gap Trap States.

Shortwave-infrared (SWIR) photodetectors are vital for many scientific and industrial applications including surveillance, quality control and inspection. In recent decades, photodetectors based on organic semiconductors have emerged, demonstrating potential to add real value to broadband and narrowband imaging and sensing scenarios, where factors such as thermal budget sensitivity, large area aperture necessity, cost considerations, and lightweight and conformal flexibility demands are prioritized. It is now recognized that the performance of organic photodetectors (OPDs), notably their specific detectivity, is ultimately limited by trap states, universally present in disordered semiconductors. This work adopts an approach of utilizing these mid-gap states to specifically create a SWIR photo-response. To this end, this work introduces a somewhat counter-intuitive approach of "trap-doping" in bulk heterojunction (BHJs) photodiodes, where small quantities of a guest organic molecule are intentionally incorporated into a semiconducting donor:acceptor host system. Following this approach, this work demonstrates a proof-of-concept for a visible-to-SWIR broadband OPD, approaching (and, to some extent, even exceeding) state-of-the-art performance across critical photodetector metrics. The trap-doping approach is, even though only a proof-of-concept currently, broadly applicable to various spectral windows. It represents a new modality for engineering photodetection using the unconventional strategy of turning a limitation into a feature.

High‐Speed Short Infrared Detector Based on Vertical Gr/Se0.2Te0.8/GaAs Heterojunction

AbstractIn the domain of high‐performance short‐wave infrared (SWIR) photodetection and imaging, existing technologies predominantly utilize single‐crystal germanium and III‐V semiconductors. Despite their efficacy, these materials are encumbered by laborious synthesis and complex fabrication demands. In this study, the synthesis of large‐area, high‐crystallinity Se0.2Te0.8 thin films through a CMOS‐compatible vacuum thermal evaporation process is reported. A high‐speed, broad‐spectrum photodetector engineered with an innovative Gr/Se0.2Te0.8/GaAs vertical heterostructure is presented, which capitalizes on the augmented carrier mobility and employs graphene innovatively as both a carrier collection interface and an electrode. This configuration facilitates a remarkably swift response time of 800 ns/1 µs at the crucial 1310 nm wavelength for optical communications. Moreover, the fabrication of a 5 × 5 array device demonstrates substantial SWIR imaging capabilities at ambient conditions, marking a paradigm shift in uncooled infrared imaging and communication technologies. This work not only extends the boundaries of SWIR photodetector performance but also underscores the potential of novel material systems in high‐speed optical applications.

Colloidal Quantum Dot‐Based Near and Shortwave Infrared Light Emitters: Recent Developments and Application Prospects

AbstractSolution‐processed quantum dot‐based near and short‐wave infrared light emitters have witnessed substantial developments in recent years. A variety of colloidal quantum dots (CQDs)‐based light emitters, including light‐emitting diodes, optical down‐converters, and emitters showing amplified spontaneous emission, lasing in the near and short‐wave infrared region, are demonstrated over the years. The progress in chemical synthesis of CQDs, development of novel CQDs, better understanding of the surface properties, chemical treatments to improve the optoelectronic properties, and suitable device engineering led to tremendous advances in the light emission performance in the near and short‐wave infrared region. A broad investigation is done into various CQD materials to achieve efficient near‐infrared light emitters. This review gives a detailed account of the advancement of the CQD‐based near and short‐wave infrared light emitters, strategies to improve the optoelectronic performance, controlling optical properties, demonstrated applications, the challenges that need to be tackled for further development, and future research direction.

Evaluation of Nutritional Values of Edible Algal Species Using a Shortwave Infrared Hyperspectral Imaging and Machine Learning Technique.

In recent years, the growing demand for algae in Western countries is due to their richness in nutrients and bioactive compounds, and their use as ingredients for foods, cosmetics, nutraceuticals, fertilizers, biofuels,, etc. Evaluation of the qualitative characteristics of algae involves assessing their physicochemical and nutritional components to determine their suitability for specific end uses, but this assessment is generally performed using destructive, expensive, and time-consuming traditional chemical analyses, and requires sample preparation. The hyperspectral imaging (HSI) technique has been successfully applied in food quality assessment and control and has the potential to overcome the limitations of traditional biochemical methods. In this study, the nutritional profile (proteins, lipids, and fibers) of seventeen edible macro- and microalgae species widely grown throughout the world were investigated using traditional methods. Moreover, a shortwave infrared (SWIR) hyperspectral imaging device and artificial neural network (ANN) algorithms were used to develop multi-species models for proteins, lipids, and fibers. The predictive power of the models was characterized by different metrics, which showed very high predictive performances for all nutritional parameters (for example, R2 = 0.9952, 0.9767, 0.9828 for proteins, lipids, and fibers, respectively). Our results demonstrated the ability of SWIR hyperspectral imaging coupled with ANN algorithms in quantifying biomolecules in algal species in a fast and sustainable way.

Range selective digital holographic imaging of vibrating objects using FMCW lidar

The use of frequency modulated continuous wave (FMCW) chirped transmit and reference waveforms in digital holographic (DH) imaging has enabled range selectivity. By frequency shifting the reference beam to compensate for the typical FMCW lidar beat frequency associated with a particular range, a temporally stable holographic image is formed for objects at the selected range and coherently integrates on a short wave infrared (SWIR) sensor. For vibrating objects, longitudinal movements of the object greater than half of an optical wavelength during the exposure time of the sensor array induce phase shifts that can wash out the hologram. An analog feedback system was designed and constructed whereby a lidar subassembly provides real time phase compensation information to a DH subassembly in order to stabilize the range selective digital holographic recording of the object. The design and characterization of the feedback system, as well as the results demonstrating the performance for vibrating objects that move over 17 wavelengths during the sensor exposure, are discussed.

Multiplexed Shortwave Infrared Imaging Highlights Anatomical Structures in Mice.

Multiplexed fluorescence in vivo imaging remains challenging due to the attenuation and scattering of visible and traditional near infrared (NIR-I, 650-950 nm) wavelengths. Fluorescence imaging using shortwave infrared (SWIR, 1000-1700 nm, a.k.a. NIR-II) light enables deeper tissue penetration due to reduced tissue scattering as well as minimal background autofluorescence. SWIR-emitting semiconductor quantum dots (QDs) with tunable emission peaks and optical stability are powerful contrast agents, yet few imaging demonstrations exclusively use SWIR emission beyond two-color imaging schemes. In this study, we engineered three high quality lead sulfide/cadmium sulfide (PbS/CdS) core/shell QDs with distinct SWIR emission peaks ranging from 1100-1550 nm for simultaneous three-color imaging in mice. We first use the exceptional photostability of QDs to non-invasively track lymphatic drainage with longitudinal imaging, highlighting the detailed networks of lymphatic vessels with widefield imaging over a 2 hr period. We then perform multiplexed imaging with all three QDs to distinctly visualize the lymphatic system and spatially overlapping vasculature networks, including clearly distinguishing the liver and spleen. This work establishes optimized SWIR QDs for next generation multiplexed and longitudinal preclinical imaging, unlocking numerous opportunities for preclinical studies of disease progression, drug biodistribution, and cell trafficking dynamics in living organisms.

Grass curing-driven fire danger index in a protected mountainous grassland using fused MODIS and Sentinel-2

ABSTRACT This study assessed the spatio-temporal variation of the degree of curing (DoC) in the Golden Gate Highlands National Park (GGHNP) from 2016 to 2020. The estimation of the degree of grass curing was carried out with the high spatial resolution fused remotely sensed data of MODIS and Sentinel-2 employing Index-then-Blend (IB) data fusion methods on Google Earth Engine (GEE) to compute Grassland Curing Index (GCI) using soil and vegetation moisture content indices-based grassland curing algorithm. Grassland curing indices were computed on Google Earth Engine and converted into Grassland Curing Maps (GCMs), which were then synthesized into fire danger maps. The study showed that all selected indices have the highest DoC in the month of September, with the minor time variation observed in MODIS and Sentinel 2-derived GCI estimated using Shortwave Infrared Water Stress (GCI_SIWSI) in the months of August and March, respectively. The analysis further revealed that GCI_SIWSI (44%) derived from Sentinel-2 data yielded the highest area of extremely high fire danger, followed by GCI estimated using Normalized Difference Moisture Index (GCI_NDMI) (25%) derived from fused data, MODIS-derived GCI_SIWSI and fused-derived GCI estimated using Global Vegetation Monitoring Index (GCI_GVMI) (both 16%). The GCI_SIWSI derived from Sentinel-2 data also showed that more than 95% of the entire landmass of the study area was within a high to extremely high fire danger zone, making the park’s vegetation susceptible to fire. Among all the four selected indices correlated against fire point, only SIWSI revealed a positive relationship across MODIS, Sentinel-2 and Fused data. It is also evident from the study that GCMs derived from Fused data outperformed MODIS and Sentinel-2 with the highest R2 and F values of 0.65 and 380, respectively. These results indicate that GCI derived from fused remotely sensed data is a promising GCI for accurately assessing the DoC over mountainous grassland environments. The study paved the way for increasing the spatial resolution for estimating the DoC for fire and fuel management of parks and other fire agencies within mountainous grassland environments.

Multispectral, Thermographic and Spectroradiometric Analyses Unravel Bio-Stimulatory Effects of Wood Distillate in Field-Grown Chickpea (Cicer arietinum L.)

Wood distillate (WD) has recently emerged as a promising bio-stimulant for sustainable legume crop production, owing to its ability to enhance seed yield and quality. However, no studies exist on the effects of WD on chickpea plants at pre-harvesting stages, hindering the farmers’ ability to acquire valuable knowledge on the early action of WD on the plants’ status and preventing the establishment of proactive measures to optimize WD use in agriculture. In this study, two multispectral, thermographic and spectroradiometric surveys, along with in-situ measurements of specific plant biometric traits, were conducted across the reproductive stage of field-grown chickpea in order to evaluate the early involvement of WD on plant health. The acquired multispectral images were used to calculate the Normalized Difference Vegetation Index (NDVI), revealing a notable ~35% increase in NDVI scores of WD-treated plants at the onset of physiological maturity, and indicating an improved plant status compared to the control (water-treated) plants. Moreover, control and WD-treated plants exhibited distinct spectral signatures across the visible, near-infrared (NIR) and short-wave infrared (SWIR) spectra, suggesting potential changes in their photosynthetic capacity, structural properties and water content both at the leaf and at the pod level. Furthermore, WD-treated plants showed a 25% increase in pod production, particularly at the beginning of seed maturity, suggesting that enhancements in plant status were also reflected in higher pod yields. These results point to a beneficial effect of WD on plant health during the preliminary stages of seed formation and indicate that a combination of both multispectral and spectroradiometric analyses can provide critical insights on the status of chickpea crops at pre-harvesting stages. In addition, these findings emphasize the importance of analyzing pre-harvesting stages to gain insights into the early involvement of WD in promoting plant health and, ultimately, in predicting final crop yields.

A novel vegetation-water resistant soil moisture index for remotely assessing soil surface moisture content under the low-moderate wheat cover

Soil surface moisture content (SMC) is one of the most critical and fundamental indicators of crop drought because water is vital for vegetation growth. In recent decades, satellite high-spatial-resolution optical multi-spectral remote-sensing sensors have entered a new stage. However, current optical remote sensing SMC indices (SMIs) are sensitive to cropland SMC and vegetation water content (VWC). From dry to saturated, the soil spectra decreased quickly as the SMC increased. For the vegetation spectra, the short-wave infrared (SWIR) bands decreased as the VWC increased. The differences in the responses of near-infrared (NIR) and SWIR bands to water may help distinguish soil moisture from mixed soil-vegetation spectra. This study focuses on (a) analyzing how soil and vegetation reflectance are affected by VWC and SMC, (b) designing a new vegetation-water resistant soil moisture index (VRSMI) based on the differences in the responses of NIR bands and SWIR bands to water, and (c) evaluating the potential of using VRSMI to remotely estimate SMC in low-moderate crop-covered regions. VRSMI uses SWIR1-SWIR2 as the numerator to detect the water absorption features and NIR×(SWIR1)0.5 as the denominator to weaken the vegetation effect. VRSMI and soil-VRSMI (VRSMIs) were tested using laboratory- and field-based spectra datasets. Our study presents the following conclusions: (1) The differences in the responses of NIR and SWIR bands to water help distinguish the effects of soil moisture on mixed soil-vegetation spectra. (2) VRSMIs can provide high-performance SMC estimates under low-moderate vegetation cover (NDVI < 0.55). (3) VRSMIs can be used for cropland SMC evaluation without considering crop VWC (laboratory-based spectra dataset: RMSE = 0.07–0.11, R2 = 0.96–0.98; field-based spectra dataset: RMSE = 0.17–0.18, R2 = 0.63–0.79). Our study indicates that VRSMI and VRSMIs can provide high-performance relative SMC estimates under low-to-moderate vegetation cover.

Impact of visibility limiting conditions on satellite and high-altitude platform quantum key distribution links

Satellite and aerial platforms are critical in the deployment of global quantum communications networks. Currently, there remain significant challenges including operation during daytime and robustness to visibility limiting conditions. In this work we investigate, through simulation, the impact of visibility limiting conditions on low-Earth orbit CubeSat dimensioned satellites, small satellites and high-altitude platform implementations. Three different operational wavelengths were considered: currently used near-infrared (at 850 nm); next-generation short-wave infrared (at 1550 nm); and a candidate longer wavelength (at 2133 nm). We present channel attenuation and consider quantum key distribution (QKD) system performance parameters. Results indicate that the “best wavelength” for an implementation depends on the minimum visibility rated and the single-photon detector technology utilized. In the cases where tolerated meteorological visibility is short, 1550 nm and 2133 nm wavelengths provide better performance. In cases when the visibility is long, the operational wavelength of 850 nm provides better QKD system performance.

A chemometric approach to assess the oil composition and content of microwave-treated mustard (Brassica juncea) seeds using Vis–NIR–SWIR hyperspectral imaging

The wide gap between the demand and supply of edible mustard oil can be overcome to a certain extent by enhancing the oil-recovery during mechanical oil expression. It has been reported that microwave (MW) pre-treatment of mustard seeds can have a positive effect on the availability of mechanically expressible oil. Hyperspectral imaging (HSI) was used to understand the change in spatial spread of oil in the microwave (MW) treated seeds with bed thickness and time of exposure as variables, using visible near-infrared (Vis–NIR, 400–1000 nm) and short-wave infrared (SWIR, 1000–1700 nm) systems. The spectral data was analysed using chemometric techniques such as partial least square discriminant analysis (PLS-DA) and regression (PLSR) to develop prediction models. The PLS-DA model demonstrated a strong capability to classify the mustard seeds subjected to different MW pre-treatments from control samples with a high accuracy level of 96.6 and 99.5% for Vis–NIR and SWIR-HSI, respectively. PLSR model developed with SWIR-HSI spectral data predicted (R2 > 0.90) the oil content and fatty acid components such as oleic acid, erucic acid, saturated fatty acids, and PUFAs closest to the results obtained by analytical techniques. However, these predictions (R2 > 0.70) were less accurate while using the Vis–NIR spectral data.

Cytometry in the Short-Wave Infrared.

Cytometry plays a crucial role in characterizing cell properties, but its restricted optical window (400-850 nm) limits the number of stained fluorophores that can be detected simultaneously and hampers the study and utilization of short-wave infrared (SWIR; 900-1700 nm) fluorophores in cells. Here we introduce two SWIR-based methods to address these limitations: SWIR flow cytometry and SWIR image cytometry. We develop a quantification protocol for deducing cellular fluorophore mass. Both systems achieve a limit of detection of ∼0.1 fg cell-1 within a 30 min experimental time frame, using individualized, high-purity (6,5) single-wall carbon nanotubes as a model fluorophore and macrophage-like RAW264.7 as a model cell line. This high-sensitivity feature reveals that low-dose (6,5) serves as an antioxidant, and cell morphology and oxidative stress dose-dependently correlate with (6,5) uptake. Our SWIR cytometry holds immediate applicability for existing SWIR fluorophores and offers a solution to the issue of spectral overlapping in conventional cytometry.

Technical note: Retrieval of the supercooled liquid fraction in mixed-phase clouds from Himawari-8 observations

Abstract. The supercooled liquid fraction (SLF) in mixed-phase clouds (MPCs) is an essential variable of cloud microphysical processes and climate sensitivity. However, the SLF is currently calculated in spaceborne remote sensing only as the cloud phase–frequency ratio of adjacent pixels, which results in a loss of the original resolution in observations of cloud liquid or ice content within MPCs. Here, we present a novel method for retrieving the SLF in MPCs based on the differences in radiative properties of supercooled liquid droplets and ice particles at visible (VIS) and shortwave infrared (SWI) channels of the geostationary Himawari-8. Liquid and ice water paths are inferred by assuming that clouds are composed of only liquid or ice, with the real cloud water path (CWP) expressed as a combination of these two water paths (SLF and 1-SLF as coefficients), and the SLF is determined by referring to the CWP from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The statistically relatively small cloud phase spatial inhomogeneity at a Himawari-8 pixel level indicates an optimal scene for cloud retrieval. The SLF results are comparable to global SLF distributions observed by active instruments, particularly for single-layered cloud systems. While accessing the method's feasibility, SLF averages are estimated between 74 % and 78 % in Southern Ocean (SO) stratocumulus across seasons, contrasting with a range of 29 % to 32 % in northeastern Asia. The former exhibits a minimum SLF around midday in summer and a maximum in winter, while the latter trend differs. This novel algorithm will be valuable for research to track the evolution of MPCs and constrain the related climate impact.

One-pot, easy and scalable synthesis of large-size short wave length IR emitting PbS quantum dots.

This study presents a versatile and efficient method to synthesize large-size lead sulfide (PbS) quantum dots (QDs) that display emission in the short-wave infrared (SWIR) region, using accessible and stable diethylammonium diethyldithiocarbamate (C2)2DTCA and octylammonium octyldithiocarbamate (C8DTCA) as sulfur sources. As these sulfur sources enable the formation of well-dispersed, large-size PbS QDs in a very convenient way, this method can further be taken up for scale-up studies. Importantly, this approach allows precise control over QD sizes, thereby enhancing their SWIR optical properties. By adjusting the hot injection temperatures and sulfur source concentrations, different synthesis routes are explored, providing flexibility for the desired QD characteristics. The results presented here offer a promising opportunity to leverage the synthesized PbS QDs in applications such as optoelectronics, sensors, and imaging technology.