Accurate and fast modeling of scattering from random arrays of nanoparticles using the discrete dipole approximation and angular spectrum method

Building blocks for nanophotonic devices and metamaterials

Nanophotonic devices control and manipulate light at the nanometer scale. Applications include biological imaging, integrated photonic circuits, and metamaterials. The design of these devices requires the accurate modeling of light-matter interactions at the nanoscale and the optimization of multiple design parameters, both of which can be computationally demanding and time intensive. Further, fabrication of these devices demands a high level of accuracy, resolution, and throughput while ideally being able to incorporate multiple materials in complex geometries. To address these considerations in the realization of nanophotonic devices, recent work within our lab has pursued the efficient and accurate modeling of nanoparticles and the assembly of complex 3D micro- and nanostructures using optical tweezers. This Feature Article review highlights these developments as well as related efforts by others in computation and fabrication methods related to nanophotonic devices and metamaterials.

Lensfree Air-Quality Monitoring of Fine and Ultrafine Particulate Matter Using Vapor-Condensed Nanolenses

Current commercial air-quality monitoring devices lack a large dynamic range, especially at the small, ultrafine size scale. Furthermore, there is a low density of air-quality monitoring stations, reducing the precision with which local particulate matter hazards can be tracked. Here, we show a low-cost, lensfree, and portable air-quality monitoring device (LPAQD) that can detect and measure micron-sized particles down to 100 nm-sized particles, with the capability to track and measure particles in real time throughout a day and the ability to accurately measure particulate matter densities as low as 3 μg m-3. A vapor-condensed film is deposited onto the coverslip used to collect particles before the LPAQD is deployed at outdoor monitoring sites. The vapor-condensed film increases the scattering cross section of particles smaller than the pixel size, enabling the sub-pixel and sub-diffraction-limit-sized particles to be detected. The high dynamic range, low cost, and portability of this device can enable citizens to monitor their own air quality to hopefully impact user decisions that reduce the risk for particulate matter-related diseases.

Point-of-care SARS-CoV-2 sensing using lens-free imaging and a deep learning-assisted quantitative agglutination assay

The persistence of the global COVID-19 pandemic caused by the SARS-CoV-2 virus has continued to emphasize the need for point-of-care (POC) diagnostic tests for viral diagnosis. The most widely used tests, lateral flow assays used in rapid antigen tests, and reverse-transcriptase real-time polymerase chain reaction (RT-PCR), have been instrumental in mitigating the impact of new waves of the pandemic, but fail to provide both sensitive and rapid readout to patients. Here, we present a portable lens-free imaging system coupled with a particle agglutination assay as a novel biosensor for SARS-CoV-2. This sensor images and quantifies individual microbeads undergoing agglutination through a combination of computational imaging and deep learning as a way to detect levels of SARS-CoV-2 in a complex sample. SARS-CoV-2 pseudovirus in solution is incubated with acetyl cholinesterase 2 (ACE2)-functionalized microbeads then loaded into an inexpensive imaging chip. The sample is imaged in a portable in-line lens-free holographic microscope and an image is reconstructed from a pixel superresolved hologram. Images are analyzed by a deep-learning algorithm that distinguishes microbead agglutination from cell debris and viral particle aggregates, and agglutination is quantified based on the network output. We propose an assay procedure using two images which results in the accurate determination of viral concentrations greater than the limit of detection (LOD) of 1.27 × 103 copies per mL, with a tested dynamic range of 3 orders of magnitude, without yet reaching the upper limit. This biosensor can be used for fast SARS-CoV-2 diagnosis in low-resource POC settings and has the potential to mitigate the spread of future waves of the pandemic.

Topological edge states of a long-range surface plasmon polariton at the telecommunication wavelength

Confining light by plasmonic waveguides is promising for miniaturizing optical components, while topological photonics has been explored for robust light localization. Here we propose combining the two approaches into a simple periodically perforated plasmonic waveguide (PPW) design exhibiting robust localization of long-range surface plasmon polaritons. We predict the existence of a topological edge state originating from a quantized topological invariant, and numerically demonstrate the viability of its excitation at telecommunication wavelength using near-field and waveguide-based approaches. Strong modification of the radiative lifetime of dipole emitters by the edge state, and its robustness to disorder, are demonstrated.

Computational Modeling of Chromatin Fiber to Characterize Its Organization Using Angle-Resolved Scattering of Circularly Polarized Light

Understanding the structural organization of chromatin is essential to comprehend the gene functions. The chromatin organization changes in the cell cycle, and it conforms to various compaction levels. We investigated a chromatin solenoid model with nucleosomes shaped as cylindrical units arranged in a helical array. The solenoid with spherical-shaped nucleosomes was also modeled. The changes in chiral structural parameters of solenoid induced different compaction levels of chromatin fiber. We calculated the angle-resolved scattering of circularly polarized light to probe the changes in the organization of chromatin fiber in response to the changes in its chiral parameters. The electromagnetic scattering calculations were performed using discrete dipole approximation (DDA). In the chromatin structure, nucleosomes have internal interactions that affect chromatin compaction. The merit of performing computations with DDA is that it takes into account the internal interactions. We demonstrated sensitivity of the scattering signal’s angular behavior to the changes in these chiral parameters: pitch, radius, the handedness of solenoid, number of solenoid turns, the orientation of solenoid, the orientation of nucleosomes, number of nucleosomes, and shape of nucleosomes. These scattering calculations can potentially benefit applying a label-free polarized-light-based approach to characterize chromatin DNA and chiral polymers at the nanoscale level.