We present a platform for parallel production of standalone, untethered electronic sensors that are truly microscopic, i.e., smaller than the resolution of the naked eye. This platform heterogeneously integrates silicon electronics and inorganic microlight emitting diodes (LEDs) into a 100-μm-scale package that is powered by and communicates with light. The devices are fabricated, packaged, and released in parallel using photolithographic techniques, resulting in ∼10,000 individual sensors per square inch. To illustrate their use, we show proof-of-concept measurements recording voltage, temperature, pressure, and conductivity in a variety of environments.

A growing body of evidence has substantiated the significance of quantitative phase imaging (QPI) in enabling cost‐effective and label‐free cellular assays, which provides useful insights into understanding the biophysical properties of cells and their roles in cellular functions. However, available QPI modalities are limited by the loss of imaging resolution at high throughput and thus run short of sufficient statistical power at the single‐cell precision to define cell identities in a large and heterogeneous population of cells—hindering their utility in mainstream biomedicine and biology. Here we present a new QPI modality, coined multiplexed asymmetric‐detection time‐stretch optical microscopy (multi‐ATOM) that captures and processes quantitative label‐free single‐cell images at ultrahigh throughput without compromising subcellular resolution. We show that multi‐ATOM, based upon ultrafast phase‐gradient encoding, outperforms state‐of‐the‐art QPI in permitting robust phase retrieval at a QPI throughput of >10 000 cell/sec, bypassing the need for interferometry which inevitably compromises QPI quality under ultrafast operation. We employ multi‐ATOM for large‐scale, label‐free, multivariate, cell‐type classification (e.g. breast cancer subtypes, and leukemic cells vs peripheral blood mononuclear cells) at high accuracy (>94%). Our results suggest that multi‐ATOM could empower new strategies in large‐scale biophysical single‐cell analysis with applications in biology and enriching disease diagnostics.

Optical microscopy is a valuable tool for in vivo monitoring of biological structures and functions because of its noninvasiveness. However, imaging deep into biological tissues is challenging due to the scattering and absorption of light. Previous research has shown that the two optimal wavelength windows for high-resolution deep mouse brain imaging are around 1300 and 1700 nm. However, one-photon fluorescence imaging in the wavelength region has been highly challenging due to the poor detection efficiency of currently available detectors. To fully utilize this wavelength advantage, we demonstrated here one-photon confocal fluorescence imaging of deep mouse brains with an excitation wavelength of 1310 nm and an emission wavelength within the 1700 nm window. Fluorescence emission at 1700 nm was detected by a custom-built superconducting nanowire single-photon detector (SNSPD) optimized for detection between 1600 nm and 2000 nm with low detection noise and high detection efficiency. With the PEGylated quantum dots and SNSPD both positioned at the optimal imaging window for deep tissue penetration, we demonstrated in vivo one-photon confocal fluorescence imaging at approximately 1.7 mm below the surface of the mouse brain, through the entire cortical column and into the hippocampus region with a low-cost continuous-wave laser source and low excitation power. We further discussed the significance of the staining inhomogeneity in determining the depth limit of one-photon confocal fluorescence imaging. Our work may motivate the further development of long wavelength fluorescent probes, and inspire innovations in high-efficiency, high-gain, and low-noise long wavelength detectors for biological imaging.

In vivo, chronic neural recording is critical to understand the nervous system, while a tetherless, miniaturized recording unit can render such recording minimally invasive. We present a tetherless, injectable micro-scale opto-electronically transduced electrode (MOTE) that is ∼60µm × 30µm × 330µm, the smallest neural recording unit to date. The MOTE consists of an AlGaAs micro-scale light emitting diode (µLED) heterogeneously integrated on top of conventional 180nm complementary metal-oxide-semiconductor (CMOS) circuit. The MOTE combines the merits of optics (AlGaAs µLED for power and data uplink), and of electronics (CMOS for signal amplification and encoding). The optical powering and communication enable the extreme scaling while the electrical circuits provide a high temporal resolution (<100µs). This paper elaborates on the heterogeneous integration in MOTEs, a topic that has been touted without much demonstration on feasibility or scalability. Based on photolithography, we demonstrate how to build heterogenous systems that are scalable as well as biologically stable-the MOTEs can function in saline water for more than six months, and in a mouse brain for two months (and counting). We also Manuscript

Abstract Upconverting luminescent nanoparticles are photostable, nonblinking, and low chemically toxic fluorophores that are emerging as promising fluorescent probes at the single molecule level. High luminescence intensity upconversion nanoparticles (UCNPs) have previously been achieved by doping with high amounts of rare-earth ions using high excitation power (>2.5 MW/cm2). However, such particles are inadequate for in vitro live-cell imaging and single-particle tracking, as high excitation power can cause photodamage. Here, we compared UCNP luminescence intensities with different dopant concentrations and presented more efficient (about seven times) UCNPs at low excitation power by increasing the concentrations of Yb3+ and Tm3+ dopants (NaYF4: 60% Yb3+, 8% Tm3+) and adding a core-shell structure.

We developed a multiphoton imaging method to capture neural structure and activity in behaving flies through the intact cuticles. Our measurements show that the fly head cuticle has surprisingly high transmission at wavelengths > 900 nm, and the difficulty of through-cuticle imaging is due to the air sacs and/or fat tissue underneath the head cuticle. By compressing or removing the air sacs, we performed multiphoton imaging of the fly brain through the intact cuticle. Our anatomical and functional imaging results show that 2- and 3-photon imaging are comparable in superficial regions such as the mushroom body, but 3-photon imaging is superior in deeper regions such as the central complex and beyond. We further demonstrated 2-photon through-cuticle functional imaging of odor-evoked calcium responses from the mushroom body g-lobes in behaving flies short-term and long-term. The through-cuticle imaging method developed here extends the time limits of in vivo imaging in flies and opens new ways to capture neural structure and activity from the fly brain.

Apart from the spatial resolution enhancement, scaling of temporal resolution, equivalently the imaging throughput, of fluorescence microscopy is of equal importance in advancing cell biology and clinical diagnostics. Yet, this attribute has mostly been overlooked because of the inherent speed limitation of existing imaging strategies. To address the challenge, we employ an all-optical laser-scanning mechanism, enabled by an array of reconfigurable spatiotemporally-encoded virtual sources, to demonstrate ultrafast fluorescence microscopy at line-scan rate as high as 8 MHz. We show that this technique enables high-throughput single-cell microfluidic fluorescence imaging at 75,000 cells/second and high-speed cellular 2D dynamical imaging at 3,000 frames per second, outperforming the state-of-the-art high-speed cameras and the gold-standard laser scanning strategies. Together with its wide compatibility to the existing imaging modalities, this technology could empower new forms of high-throughput and high-speed biological fluorescence microscopy that was once challenged.

A growing body of evidence has substantiated the significance of quantitative phase imaging (QPI) in enabling cost-effective and label-free cellular assay, which provides useful insights into understanding biophysical properties of cells and their roles in cellular functions. However, available QPI modalities are limited by the loss of imaging resolution at high throughput and thus run short of sufficient statistical power at the single cell precision to define cell identities in a large and heterogeneous population of cellshindering their utility in mainstream biomedicine and biology. Here we present a new QPI modality, coined multi-ATOM that captures and processes quantitative label-free single-cell images at ultra-high throughput without compromising sub-cellular resolution. We show that multi-ATOM, based upon ultrafast phase-gradient encoding, outperforms state-of-the-art QPI in permitting robust phase retrieval at a QPI throughput of >10,000 cell/sec, bypassing the need for interferometry which inevitably compromises QPI quality under ultrafast operation. We employ multi-ATOM for large-scale, label-free, multi-variate, cell-type classification (e.g. breast cancer sub-types, and leukemic cells versus peripheral blood mononuclear cells) at high accuracy (>94%). Our results suggest that multi-ATOM could empower new strategies in large-scale biophysical single-cell analysis with applications in biology and enriching disease diagnostics.