Intelligent nanoscope for rapid nanomaterial identification and classification

Abstract

Microspheres array based intelligent nanoscope processed data collection for deep learning training. The trained convolutional neural network model classified the different sizes of nanoparticle samples.

Machine learning-driven advanced development of carbon-based luminescent nanomaterials

“…53,61 The data set could also be generated from the numerous published works through text mining or image processing. [62][63][64][65] The experimental data that has been obtained will also be documented in a scientific paper. Text mining and image processing are preferable methods to generate datasets from many reported cases that are painstakingly collected and curated through an experimental or computational investigation.…”

Robust Acute Pancreatitis Identification and Diagnosis: RAPIDx

“…19−21 In addition, the nanoscope imaging platform using microsphere arrays to characterize nanomaterials shows excellent potential for nanoscale EV identification. 22 Our group has recently developed an exosome detection method via the ultrafastisolation system (EXODUS) using nanoporous membranebased resonators, which can fast-purify EVs from diverse biofluid samples with high purity toward clinical translations. 23 With regard to high-throughput detection platforms, matrixassisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been demonstrated as a powerful analytical tool for quantitatively detecting and analyzing biomolecules such as peptides and proteins.…”

“…Many platforms have been developed to study EVs for clinical application. The traditional methods, including ultracentrifugation and polymer-based precipitation, are incompatible with a rapid clinical screening test. , To overcome these limitations, analytical techniques such as acoustofluidic-based vesicle analysis and microfluidic platforms have been reported to facilitate point-of-care applications. − In addition, the nanoscope imaging platform using microsphere arrays to characterize nanomaterials shows excellent potential for nanoscale EV identification . Our group has recently developed an exosome detection method via the ultrafast-isolation system (EXODUS) using nanoporous membrane-based resonators, which can fast-purify EVs from diverse biofluid samples with high purity toward clinical translations .…”

Dynamic nano-imaging via a microsphere compound lens integrated microfluidic device with a 10× objective lens

“…[32][33][34][35] Recently, there have been few preliminary attempts in dynamic nanoimaging applications with microspheres, including observing the Brownian motion of nanoparticles and sorting nanoobjects. 36,37 However, the minimum sizes of nanoparticles demonstrated are only near the optical diffraction limit. A potential limitation of these imaging schemes may be that the distance between the microsphere and microchannels is not optimized to fulfil the imaging characteristic of the microsphere, thus underutilizing its full imaging resolution capacity.…”