Rajeev J. Ram

The precise control of light propagation through dispersion engineering is essential for the development of compact systems such as chip-integrated coherent sources and amplifiers that aim to manipulate the temporal characteristics of light pulses and exploit nonlinear phenomena in long waveguides. Given the complexity of photonic device design, versatile and broadly accessible dispersion characterization techniques are needed. In this work, we present single photon avalanche diode (SPAD)-based time-of-flight (ToF) dispersion measurements of integrated waveguides that are insensitive to both chip-coupling efficiency and alignment. We demonstrate that SPAD-ToF can be used to measure the magnitude and sign of the dispersion parameter in ultra-low-loss silicon nitride (SiN) spiral waveguides.

Using nanosensors in living plants allows the real-time detection of internal reactive oxygen species (e.g., hydrogen peroxide) signaling in response to environmental stressors. The time-dependent pulse of hydrogen peroxide (H 2 O 2 ) constitutes a signaling waveform; however, standardized methods of extracting and analyzing such waveforms quantitatively remain elusive. Here, we develop a reference-less framework to extract stress-induced H 2 O 2 waveforms in planta directly from active nanosensors for the first time. We show that waveforms extracted for 3-week-old spinach across different experimental configurations, including 2D nIR imaging and 1D spectroscopy, are identical. Using this standardized approach, we systematically validate an analytical waveform model based on H 2 O 2 reaction-diffusion transport with a large waveform data set and extract the wave velocities and propagation rate constants from different waveforms. A wave-velocity-rate constant map is created for comparative studies. Results suggest that nanosensors can identify distinct waveforms associated with specific plant stressors with the proposed framework, providing opportunities for new diagnostic tools.

We present a modeling framework that can perform real-time estimation of per-cell metabolic rates of T cells expanded ex vivo in a reactor. We validate our estimated rates using metabolic assays, show how average rates can be deconvoluted to rates of individual T cell phenotypes, and demonstrate applicability to different reactor types. Applying our tool to the expansion of both healthy and patient-derived cells in a perfusion-based microbioreactor, we offer proof-of-principle to show that correlations exist between early metabolic rates of T cells in culture and cellular attributes related to growth, differentiation, and exhaustion of the final product. Given the biological variation that exists in the growth and dynamics of patient-derived cells in culture, such modeling contributes to the overarching goal of improving the consistency of cell therapy through adaptive process control (APC).

Here, we used Raman spectroscopy to characterize the effects of chitin treatment and fungal inoculations on Arabidopsis thaliana and Brassica vegetables. Chitin, a recognized fungal pathogen-associated molecular pattern (PAMP), elicited a dose dependent positive Elicitor Response Index (ERI) in wild-type Arabidopsis. Mutant plants lacking chitin receptors ( cerk1 and lyk4/5 ) displayed minimal ERI, whereas fls2 mutant deficient in the bacterial-specific flg22 receptor was hyper-responsive. These results confirm critical role of chitin receptors in activating downstream pathways and highlighting distinct responses in two separate pattern-triggered immunity (PTI) systems. Inoculations of Colletotrichum higginsianum and Alternaria brassicicola induced significant changes in Infection Response Index (IRI) values, with the former giving positive IRI at 12–48 hours post-inoculation whereas the latter exhibited a transient negative IRI before transitioning to positive values. Notably, Raman shifts could predict fungal infection before the appearance of visible symptoms, establishing Raman shifts as a potential early diagnostic marker. Comparative analyses of infected Brassica vegetables revealed varied sensitivity to fungal pathogens and a correlation between symptom severity and IRI values. Furthermore, randomized controlled trials validated the reliability of Raman technology for early, pre-symptomatic detection of fungal infections, achieving an accuracy rate of 76.2% in Arabidopsis and 72.5% in Pak-Choy ( Brassica rapa chinensis ). Principal component analysis differentiated Raman spectral features associated with fungal and bacterial infections, emphasizing their unique profiles and reinforcing the utility of Raman spectroscopy for early detection of pathogen-related plant stress. Our work supports the application of non-invasive diagnostic techniques in agricultural practices, enabling timely intervention against crop diseases.

Current workflows in autologous cell therapy manufacturing are reliant on manual processes that are difficult to scale out to meet patient demands. High throughput bioreactor systems that enable multiple cultures to occur in parallel can address this need, but require good bioprocess monitoring workflows to produce good quality cell therapy products. Commercial sampling systems have thus been developed for better feedback control and monitoring capabilities. However, they are targeted towards large scale processes and often bioreactor specific, making them less robust for integration across different bioreactor scales and types, such as perfusion-capable microbioreactors which allows for greater process intensification. Here, an automated cell culture sampling system (Auto-CeSS) was developed to eliminate laborious manual sampling while minimizing sterility risks for cell therapy manufacturing processes. The system is aseptically integrated with a variety of bioreactors of different working volumes. This system can accurately and aseptically sample a minimum volume of 30 μL and can consistently perform periodic sampling of supernatant over a minimum interval of 15 min. We integrated Auto-CeSS with a 2 mL perfusion microbioreactor and a 8 mL gas-permeable well-plate for T cell culture, collecting 200 μL of supernatant samples daily for metabolite analysis. Comparison of the metabolic profiles of the samples collected via Auto-CeSS versus manual sampling revealed insignificant differences in metabolite levels, including glucose, lactate, glutamine, and glutamate. This report demonstrates the potential of Auto-CeSS as an at-line sampling platform in a real-time T cell production run to facilitate in-process culture monitoring.

Today, molecular analysis at multiple locations requires either transporting samples to a central laboratory via transportation or conveyor networks or deploying independent analyzers at each sampling point. Neither of these approaches offers the accessibility and scalability we have come to expect from modern utility infrastructure that provides access to water, electricity, information (internet), and computation resources. Here, we demonstrate a novel parallel, distributed, optical fiber swept-source Raman spectroscopy approach that replaces spectrometers with compact semiconductor tunable lasers along with high-collection power fiber-optic probes and sensitive single photon avalanche detectors (SPAD) photodetectors. Fiber probes with 12x higher light collection power than benchtop spectrometers are integrated with compact detection hardware, allowing us to realize a scalable network of Raman sensors distributed over 16 locations at distances of 100 m. This network shares essential resources, such as the tunable laser, and leverages existing infrastructure networks, such as communication optical fiber and computation hardware. We illustrate the capabilities of this network with an industrial monitoring application, where we monitor therapeutic monoclonal antibody production in a CHO cell culture, and an environmental monitoring application, where we monitor nitrogen fertilizer in hydroponic agriculture.

Abstract Adoptive cell therapies such as CAR T cells have revolutionized cancer treatment and shown successes even with refractory cases of haematological malignancies. There is burgeoning interest in the optimization and improved manufacturing of cell therapy products. For CAR T cell therapy, enrichment of certain phenotypes of T cells in the infusion product have been correlated with improved long-term treatment outcomes. While metabolic control of T cell phenotypic fates has been demonstrated in some contexts, gaps still exist in our knowledge of how T cell metabolic dynamics early during CAR T manufacturing might affect critical quality attributes (CQAs) of the final product (e.g., differentiation/exhaustion/potency). We present a modelling framework that can perform real-time estimation of per-cell metabolic rates of T cells expanded ex vivo in a reactor. We validate our estimated rates using metabolic assays, show how average rates can be deconvoluted to rates of individual T cell phenotypes, and demonstrate applicability to different reactor types. Applying our tool to the expansion of both healthy and patient-derived cells in a perfusion-based microbioreactor, we offer proof-of-principle to show that correlations exist between early metabolic rates of T cells in culture and cellular attributes related to growth, differentiation and exhaustion of the final product. Given the biological variation that exists in the growth and dynamics of patient-derived cells in culture, such modelling contributes to the overarching goal of improving the consistency of cell therapy through Adaptive Process Control (APC).

Thin-film lithium niobate (TFLN) is a widely used platform for nonlinear frequency conversion, as its strong nonlinear susceptibility and enhanced modal confinement intensify nonlinear interactions. Among phase matching techniques in TFLN, quasi-phase matching (QPM) is the dominant approach. For frequency doubling from near-infrared to visible wavelengths, this necessitates fabrication of QPM gratings with minimal period variation (<20nm) and control of ferroelectric domain inversion at the micron-scale along centimeter-long waveguides. Second harmonic generation microscopy (SHM) is a powerful tool for optimizing domain engineering (E-field poling), and it enabled the fabrication of near-ideal (∼50% duty cycle, ∼5% variation in period) QPM gratings in 5.6mm-long TFLN waveguides. Here, we show that increasing the SHM raster scan step size from 200nm to 400nm results in a 4x imaging speedup without sacrificing the accuracy of QPM grating characterization. To that end, we model device performance using Monte Carlo simulation of the coupled rate equations. Summary metrics of the QPM grating derived from SHM images are used as simulation inputs, and predictions of second harmonic output powers agreed well with experimentally measured values. We also modeled device performance using quasi-analytic correction factors, but we found that the predictions of second harmonic output power diverged from experimental measurements as the QPM grating quality degraded. To further speedup SHM imaging, we employed a statistical subsampling scheme that allows for characterization of 5.6mm-long waveguides (poling period Λ=3.240) in approximately 5 minutes (30 seconds per field×10 fields per waveguide). Each field is 100 microns in length, so our results indicate that sampling only ∼300 periods of a QPM grating is sufficient to accurately predict its second harmonic output. For the device characterized, this corresponds to ∼20% of the total grating length. Together, discretization and device-length subsampling speed up SHM imaging by an order of magnitude. These results can enable wafer-scale imaging of TFLN devices, which is critical for realizing the scaling potential of this high-performance, integrated nonlinear platform. More generally, this work highlights the role of SHM as an invaluable tool for multi-scale materials characterization.

Raman microscopy allows label-free chemical imaging by probing the roto-vibrational modes of target analytes. However, rapid image acquisition and reliable analyte quantification are impeded by the small spontaneous Raman cross-section, which necessitates long pixel dwell times and complicates the extraction of weak Raman peaks from strong fluorescent backgrounds. Stimulated Raman Scattering (SRS) addresses these challenges by inducing stimulated emission of Stokes photons, yielding non-resonant background free spectra linear with analyte concentration. Despite these advantages, widespread adoption of SRS microscopy has been hindered by the increased system cost and complexity, requiring high-power, synchronized, wavelength-tunable ultrafast sources. Here, we develop and experimentally validate a model demonstrating signal propagation through an SRS microscope in the modulation transfer scheme, from the conversion of pump to Stokes photons to the measured output voltage at the lock-in amplifier. The model calculates stimulated Raman gain from tabulated spontaneous Raman cross-sections, allowing direct sensitivity comparisons with spontaneous Raman systems using comparable average input powers. Using this model, we analyze one minimalistic SRS configuration and consider the limit where SRS microscopy ceases to yield SNR advantages over simpler spontaneous Raman approaches. These considerations provide guidelines in the development of practical, compact, low-cost sources for SRS.

We present a detailed comparison of fluorescence imaging systems to determine optimal design conditions for different applications. We first compare ultrawide-field single lens imaging (>5cm field of view) and wide-field (1-2cm) tandem lens imaging with oblique illumination. This comparison allows us to understand the advantages and drawbacks of single lens and tandem lens configuration.Then we compare wide-field (1-2cm) tandem lens imaging with oblique illumination, and wide-field tandem lens imaging with epi-illumination. This initial analysis is used to guide the optical design of low-light wide-field imaging modalities such as two-photon imaging and wide-field Raman imaging.

We demonstrate the feasibility of machine-learning aided UV absorbance spectroscopy for in-process microbial contamination detection during cell therapy product (CTP) manufacturing. This method leverages a one-class support vector machine to analyse the absorbance spectra of cell cultures and predict if a sample is sterile or contaminated. This label-free technique provides a rapid output (< 30 minutes) with minimal sample preparation and volume (< 1 mL). Spiking of 7 microbial organisms into mesenchymal stromal cells supernatant aliquots from 6 commercial donors showed that contamination events could be detected at low inoculums of 10 CFUs with mean true positive and negative rates of 92.7% and 77.7% respectively. The true negative rate further improved to 92% after excluding samples from a single donor with anomalously high nicotinic acid. In cells spiked with 10 CFUs of E. coli, contamination was detected at the 21-hour timepoint, demonstrating comparable sensitivity to compendial USP < 71 > test (~ 24 hours). We hypothesize that spectral differences between nicotinic acid and nicotinamide in the UV region are the underlying mechanisms for contamination detection. This approach can be deployed as a preliminary test during different CTP manufacturing stages, for real-time, continuous culture monitoring enabling early detection of microbial contamination, assuring safety of CTP.

Traditional silicon photonic platforms offer powerful capabilities for light manipulation and detection but cannot realize an integrated light source. This results in systems with increased cost and complexity due to the need for external light generation and coupling. In this work we overcome this limitation and experimentally demonstrate the generation, manipulation, and detection of waveguide-coupled light in a commercial silicon photonics foundry with monolithically integrated electronics—without any modification to the fabrication process and no additional post-processing steps. We propose the use of our platform to realize fully integrated, monolithic optical refractometric sensors and theoretically show that performance comparable to commercial, state of the art bench-top systems can be achieved. Our work lays the foundation for the realization of truly monolithic, full-functionality silicon photonic electro-optical systems with increasing levels of miniaturization and cost reduction.

Fluorescence labeled biomolecules have become an invaluable tool for researchers, enabling novel applications in biological sensing, high-resolution imaging, and precise nanoscale manipulation especially in the context of single cell proteomics and real-time monitoring of certain proteins for applications like CAR-T cell lines. These advances are driven by tools that can precisely detect minute changes in the optical properties of the analyte, facilitated by the integration of sensitive optical detectors with microfluidic or nanofluidic platforms. Although CMOS platforms offer appealing features for integrated readout systems, it is still quite challenging to introduce efficient optical detectors in a standard process especially if it requires post-processing steps to introduce fluidic compartment on the same die, such platform will enable wide range of applications limited by the abundance of samples. Here, we introduce an all-CMOS platform designed for biomolecule sensing where the integration of single photon avalanche detector (SPAD), nanofluidic channels, and electronics is demonstrated. Nanofluidic channels are implemented by post-fabrication release in a microelectronics foundry process (Global Foundries 55BCDL). CMOS SPADs are embedded besides nanofluidic channels in the front-end of the CMOS process. Initial experiments confirm the resilience of these SPADs to the process steps required to release the nanochannels – namely reactive ion etching followed by selective XeF2 etching to open nanochannels. Geiger mode operation is realized for the nanofluidic integrated SPADs with maximum probability of photon detection (PDP) of 35% at 520nm wavelength with a separation between the SPADs and nanochannels of only 200nm. The implementation of nanochannels and SPADs in a microelectronics CMOS process allows us to integrate high-speed quenching circuits alongside the SPADs. The results illustrate the platform’s potential in advancing single-molecule fluorescence detection as a valuable tool in molecular biology and diagnostics.

Tracking the movement of molecules through cells and tissue is invaluable for characterizing metabolic pathways. To this end, previous works have used Fluorine-18 labeled glucose (FDG) for radioluminescence imaging.1 Due to the short half life of 18F, its usage requires on-site synthesis of tagged metabolites, and the duration of time for in vivo tracking is limited. 14C presents an alternative that avoids these issues with its half life of 5700 years. This long half-life means that this radio-label is commercially available in a wide range of molecules – from simple sugars to pharmaceuticals. Unfortunately, 14C emits primarly low energy beta radiation (49keV) which significantly reduces the light yield from scintillators (60 photons/keV) relative to 18F. Additionally, its specific activity is limited (<2MBq/μmol) further reducing the available signal. To address these low light conditions, we used an ´etendue based analysis to design an optical system which maximizes light collection. Using a thin-plate Gadolinium Aluminum Gallium Garnet (GAGG) scintillator placed directly on a 14C source, we have developed a high collection efficiency microscope that can image a 14C source that undergoes only 14,000 14C decay events/second. Over a field of view of 1.25mm diameter, this gives a sensitivity better than 1 nanomole for 14C labeled metabolites.

Classical transport of electrons and holes in nanoscale devices leads to heating that severely limits performance, reliability, and efficiency. In contrast, recent theory suggests that interband quantum tunneling and subsequent thermalization of carriers with the lattice results in local cooling of devices. However, internal cooling in nanoscale devices is largely unexplored. Here, using a novel scanning thermal microscopy technique with millikelvin temperature resolution and nanometer spatial resolution, we directly record the cross-sectional temperature in functional InGaAs tunnel diodes. Our measurements reveal large, localized cooling of 2-3 W/cm^{2} at the tunnel junction, which is in quantitative agreement with the bipolar Peltier process associated with interband tunneling. These advances hold significant potential for integration into electronic and energy conversion devices and improving their performance.

Patterning of stable, spatially tailored ferroelectric domains in thin-film lithium niobate enables efficient nonlinear optical interactions through quasi-phase matching. The engineering of domain structure is limited by the uncontrolled distribution of defects, which disrupt domain wall motion. Here, we fabricate quasi-phase matching gratings in thin-film lithium niobate with sub 20 nm of period variation. We demonstrate that annealing processed samples at 350 or 500 °C for 48 h, prior to E-field poling, can dramatically reduce the duty cycle variation. We show that maintaining an elevated temperature of 200 °C during poling enhances defect mobility, which leads to more rectangular inverted domains. Moreover, poling at elevated temperatures also increases inversion depth without sacrificing the periodic domain pattern's accuracy or precision. Elevating the temperature prior to and during poling resulted in near-ideal square wave patterning of ferroelectric domains (50% mean duty cycle, sub 10% domain width variation, and 100% depth inversion). This enables effective quasi-phase matching for second harmonic generation in 5.6 mm-long waveguides fabricated from MgO-doped x-cut thin-film lithium niobate.

Inverse design of optical components based on adjoint sensitivity analysis has the potential to address the most challenging photonic engineering problems. However, existing inverse design tools based on finite-difference-time-domain (FDTD) models are poorly suited for optimizing waveguide modes for adiabatic transformation or perturbative coupling, which lies at the heart of many important photonic devices. Among these, dispersion engineering of optical waveguides is especially challenging in ultrafast and nonlinear optical applications involving broad optical bandwidths and frequency-dependent anisotropic dielectric material response. In this work, we develop gradient back-propagation through a general-purpose electromagnetic eigenmode solver and use it to demonstrate waveguide dispersion optimization for second harmonic generation with maximized phase-matching bandwidth. This optimization of three design parameters converges in eight steps, reducing the computational cost of optimization by ∼100x compared to exhaustive search and identifying new designs for broadband optical frequency doubling of laser sources in the 1.3-1.4 µm wavelength range. Furthermore, we demonstrate that the computational cost of gradient back-propagation is independent of the number of parameters, as required for optimization of complex geometries. This technique enables practical inverse design for a broad range of previously intractable photonic devices.

Optical phased arrays (OPAs) are a promising technology for the realization of fast and compact non-mechanical optical beam steering. While many experimental demonstrations of integrated OPAs exist in the literature, it is challenging to evaluate their suitability for real-world applications due to the lack of system-level performance requirements. Here, we derive such performance requirements for two of the most promising OPA applications - namely free space optical communications (FSOC) and light detection and ranging (LIDAR) - and show that traditional uniformly spaced OPA architectures likely cannot reach the required performance. In response, we propose the use of non-uniformly spaced OPAs, analyze its performance tradeoffs and show that in certain scenarios they can offer superior performance with decreased complexity.

Decarbonizing food production and mitigating agriculture's environmental impact require new technologies for precise delivery of fertilizers and pesticides to plants. The cuticle, a waxy barrier that protects the surface of leaves, causes 60%-90% runoff of fertilizers and pesticides, leading to the wastage of intensive resources, soil depletion, and water bodies pollution. Solutions to mitigate runoff include adding chemicals (e.g., surfactants) to decrease surface tension and enhance cuticles' permeability but have low efficacy. In this study, vapor-induced synergistic differentiation (VISDi) is used to nanomanufacture echinate pollen-like, high payload content (≈50 wt%) microcapsules decorated with robust spines that mechanically disrupt the cuticle and adhere to the leaf. VISDi induces a core-shell structure in the spines, enabling the release of agrochemicals from the microparticles' body into the leaf. As proof of concept, precise and highthroughput delivery of iron fertilizer in Fe-deficient spinach plants is demonstrated. Spray of spiny microparticles improves leaf adhesion by mechanical interlocking, reduces wash-off by an ≈12.5 fold, and enhances chlorophyll content by ≈7.3 times compared to the application of spherical counterparts. Together, these results show that spiny microparticles can mitigate agricultural runoff and provide a high-throughput tool for precise plant drug delivery.

Here, we explore the application of Raman spectroscopy for the assessment of plant biodiversity. Raman spectra from 11 vascular plant species commonly found in forest ecosystems, specifically angiosperms (both monocots and eudicots) and pteridophytes (ferns), were acquired in vivo and in situ using a Raman leaf-clip. We achieved an overall accuracy of 91% for correct classification of a species within a plant group and identified lignin Raman spectral features as a useful discriminator for classification. The results demonstrate the potential of Raman spectroscopy in contributing to plant biodiversity assessment.

Inverse design of optical components based on adjoint sensitivity analysis has the potential to address the most challenging photonic engineering problems. However existing inverse design tools based on finite-difference-time-domain (FDTD) models are poorly suited for optimizing waveguide modes for adiabatic transformation or perturbative coupling, which lies at the heart of many important photonic devices. Among these, dispersion engineering of optical waveguides is especially challenging in ultrafast and nonlinear optical applications involving broad optical bandwidths and frequency-dependent anisotropic dielectric material response. In this work we develop gradient back-propagation through a general purpose electromagnetic eigenmode solver and use it to demonstrate waveguide dispersion optimization for second harmonic generation with maximized phase-matching bandwidth. This optimization of three design parameters converges in eight steps, reducing the computational cost of optimization by ~100x compared to exhaustive search and identifies new designs for broadband optical frequency doubling of laser sources in the 1.3-1.4 micron wavelength range.Furthermore we demonstrate that the computational cost of gradient back-propagation is independent of the number of parameters, as required for optimization of complex geometries. This technique enables practical inverse design for a broad range of previously intractable photonic devices.

Abstract Here, we explore the application of Raman spectroscopy for the assessment of plant biodiversity. Raman spectra from 11 vascular plant species commonly found in forest ecosystems, specifically angiosperms (both monocots and eudicots) and pteridophytes (ferns), were acquired in vivo and in situ using a Raman leaf-clip. We achieved an overall accuracy of 91% for correct classification of a species within a plant group and identified lignin Raman spectral features as a useful discriminator for classification. The results demonstrate the potential of Raman spectroscopy in contributing to plant biodiversity assessment.

We present an on-chip LED based on native Si, fabricated in an open foundry CMOS node. This LED has remarkable characteristics such as its sub-wavelength emission area, broad spectrum, high spatial intensity, high bandwidth, and high reproducibility, which make it an ideal light source for various imaging and sensing systems. Two prototypes, a holographic microscope and a LIDAR, are built employing this LED. Our work demonstrates the possibility of integrating monolithic light sources with other photonic and electronic components on a single photonic chip.

Generation of sub-100 ps pulses tunable over 48 nm is demonstrated by optically gain-switching a MEMS-vertical-cavity surface-emitting laser (VCSEL). A minimum pulse width of 61 ps and a maximum, unamplified peak power of 28 mW are demonstrated. The polarization stability of the VCSELs allows amplification with a polarization-dependent semiconductor optical amplifier, resulting in pulse compression to 57 ps with a peak power of 932 mW. The low threshold power (average &amp;lt;1 mW) enables simultaneous pumping of multiple lasers for the generation of synchronized, independently tunable picosecond pulses.

We show that the use of colorimetric compounds in integrated optical refractometric sensors can enhance the response to the presence of analytes of interest by virtue of the Kramers-Konig relations.

Abstract High-resolution, three-dimensional fluorescence microscopy is widely used in biology and neuroscience. The challenges of conventional three-dimensional fluorescence microscopy which relies on scanning the focal spot across the object include limited imaging cycles due to photobleaching of the fluorophores, ambiguous spatiotemporal information in dynamic samples due to long scanning times, and mechanical perturbation during the scanning process. In this paper, we report a snapshot three-dimensional fluorescence microscopy method (CausWEI) where three-dimensional sample information is encoded in a single wide-field image by engineering a high-contrast, laterally invariant point-spread function composed of caustics generated via the interaction of a uniform, thick glass sample holder and a high-numerical aperture objective. The three-dimensional information is computationally reconstructed from the caustic pattern recorded at the camera plane. The method can be implemented with a wide-field fluorescence microscope, without any internal modification in the microscope optics. We qualitatively and quantitatively evaluate CausWEI’s capabilities and limitations with reference fluorescent beads, neural cells on three-dimensional scaffolds, and spinal cord tissue sections. CausWEI microscopy is of importance when fluorescently labelled features are located in a depth range significantly larger than the depth-of-field of the objective lens.

In the agricultural industry, the post-harvest leafy vegetable quality and shelf life significantly influence market value and consumer acceptability. This study examined the effects of different storage temperatures on leaf senescence, nitrogen assimilation, and remobilization in Pak Choi (Brassica rapa subsp. chinensis). Mature Pak Choi plants were harvested and stored at two different temperatures, 4 °C and 25 °C. Senescence was tracked via chlorophyll content and leaf yellowing. Concurrently, alterations in the total nitrogen, nitrate, and protein content were quantified on days 0, 3, 6, and 9 in old, mid, and young leaves of Pak Choi plants. As expected, 4 °C alleviated chlorophyll degradation and delayed senescence of Pak Choi compared to 25 °C. Total nitrogen and protein contents were inversely correlated, while the nitrate content remained nearly constant across leaf groups at 25 °C. Additionally, the transcript levels of genes involved in nitrogen assimilation and remobilization revealed key candidate genes that were differentially expressed between 4 °C and 25 °C, which might be targeted to extend the shelf life of the leafy vegetables. Thus, this study provides pivotal insights into the molecular and physiological responses of Pak Choi to post-harvest storage conditions.

We realize single-mode, waveguide-coupled, electrically driven silicon light emitting diodes in commercial, unmodified silicon photonics foundry processes and develop a model of both the electrical and optical behavior to understand the performance limitations. We measure a center wavelength of 1130 nm, a 90 nm 3 dB optical bandwidth, and 200 pW of optical power propagating in each direction. We show on-chip modulation and detection of the generated light using native resonant photodetectors integrated in the same chip. Our work unveils a new native light source available in silicon photonics processes, which can find applications ranging from device screening and fabrication quality assessment to imaging, refractive index sensing, or intra-chip communication.

Abstract Despite remarkable progress in the development of halide perovskite materials and devices, their integration into nanoscale optoelectronics has been hindered by a lack of control over nanoscale patterning. Owing to their tendency to degrade rapidly, perovskites suffer from chemical incompatibility with conventional lithographic processes. Here, we present an alternative, bottom-up approach for precise and scalable formation of perovskite nanocrystal arrays with deterministic control over size, number, and position. In our approach, localized growth and positioning is guided using topographical templates of controlled surface wettability through which nanoscale forces are engineered to achieve sub-lithographic resolutions. With this technique, we demonstrate deterministic arrays of CsPbBr 3 nanocrystals with tunable dimensions down to &lt;50 nm and positional accuracy &lt;50 nm. Versatile, scalable, and compatible with device integration processes, we then use our technique to demonstrate arrays of nanoscale light-emitting diodes, highlighting the new opportunities that this platform offers for perovskites’ integration into on-chip nanodevices.

Light detection and ranging (LIDAR) is a widely used technique for measuring distance. With recent advancements in integrated photonics, there is a growing interest in miniaturizing LIDAR systems through on-chip photonic devices, but a LIDAR light source compatible with current integrated circuit technology remains elusive. In this letter, we report a pulsed CMOS LED based on native Si, which spectrally overlaps with Si detectors' responsivity and can produce optical pulses as short as 1.6 ns. A LIDAR prototype is built by incorporating this LED and a Si single-photon avalanche diode (SPAD). By utilizing time-correlated single-photon counting (TCSPC) to measure the time-of-flight (ToF) of reflected optical pulses, our LIDAR successfully estimated the distance of targets located approximately 30 cm away with sub-centimeter resolution, approaching the Cramér-Rao lower bound set by the pulse width and instrument jitter. Additionally, our LIDAR is capable of generating depth images of natural targets. This all-Si LIDAR demonstrates the feasibility of integrated distance sensors on a single photonic chip.

Scalable, low power, high speed data transfer between cryogenic and room temperature environments is essential for the realization of practical, large-scale systems based on superconducting technologies. Optical fiber presents a 100–1,000x lower heat load than conventional electrical wiring, relaxing the requirements for thermal anchoring, and allows for very high bandwidth densities by carrying multiple signals through the same physical fiber. By operating a CMOS modulator in the forward bias regime at a temperature of 3.6 K, we have demonstrated the optical readout of a superconducting nanowire single-photon detector (SNSPD) without the need for an interfacing device.

Abstract While adoptive cell therapies have revolutionized cancer immunotherapy, current autologous chimeric antigen receptor (CAR) T cell manufacturing face challenges in scaling to meet patient demands. CAR T cell production still largely rely on fed-batch, manual, open processes that lack environmental monitoring and control, whereas most perfusion-based, automated, closed-system bioreactors currently suffer from large footprints and working volumes, thus hindering process development and scaling-out. Here, we present a means of conducting anti-CD19 CAR T cell culture-on-a-chip. We show that T cells can be activated, transduced, and expanded to densities exceeding 150 million cells/mL in a two-milliliter perfusion-capable microfluidic bioreactor, thus enabling the production of CAR T cells at clinical dose levels in a small footprint. Key functional attributes such as exhaustion phenotype and cytolytic function were comparable to T cells generated in a gas-permeable well. The process intensification and online analytics offered by the microbioreactor could facilitate high-throughput process optimization studies, as well as enable efficient scale-out of cell therapy manufacturing, while providing insights into the growth and metabolic state of the CAR T cells during ex vivo culture.

Abstract A nanoscale on-chip light source with high intensity is desired for various applications in integrated photonics systems. However, it is challenging to realize such an emitter using materials and fabrication processes compatible with the standard integrated circuit technology. In this letter, we report an electrically driven Si light-emitting diode with sub-wavelength emission area fabricated in an open-foundry microelectronics complementary metal-oxide-semiconductor platform. The light-emitting diode emission spectrum is centered around 1100 nm and the emission area is smaller than 0.14 μm 2 (~ $$\varnothing 400$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>∅</mml:mi> <mml:mn>400</mml:mn> </mml:math> nm). This light-emitting diode has high spatial intensity of &gt;50 mW/cm 2 which is comparable with state-of-the-art Si-based emitters with much larger emission areas. Due to sub-wavelength confinement, the emission exhibits a high degree of spatial coherence, which is demonstrated by incorporating the light-emitting diode into a compact lensless in-line holographic microscope. This centimeter-scale, all-silicon microscope utilizes a single emitter to simultaneously illuminate ~9.5 million pixels of a complementary metal-oxide-semiconductor imager.

Nanoscale, sub-wavelength size light-emitting diodes (LEDs) have attractive features including high spatial coherence, fast modulation, and high array density. Here we present digital holography and time-of-flight ranging using nanoscale CMOS LEDs.

We present a snapshot 3D fluorescence microscopy technique that extracts depth from defocus by exploiting caustics generated when spherical aberration is intentionally introduced in a high-numerical aperture microscope. The snapshot acquisition reduces the imaging time and the risk of phototoxicity associated with scanning based methods.