<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Journal Article</dc:product_type><dc:title>Programmable black phosphorus image sensor for broadband optoelectronic edge computing</dc:title><dc:creator>Lee, Seokhyeong; Peng, Ruoming; Wu, Changming; Li, Mo</dc:creator><dc:corporate_author/><dc:editor/><dc:description>Abstract            Image sensors with internal computing capability enable in-sensor computing that can significantly reduce the communication latency and power consumption for machine vision in distributed systems and robotics. Two-dimensional semiconductors have many advantages in realizing such intelligent vision sensors because of their tunable electrical and optical properties and amenability for heterogeneous integration. Here, we report a multifunctional infrared image sensor based on an array of black phosphorous programmable phototransistors (bP-PPT). By controlling the stored charges in the gate dielectric layers electrically and optically, the bP-PPT’s electrical conductance and photoresponsivity can be locally or remotely programmed with 5-bit precision to implement an in-sensor convolutional neural network (CNN). The sensor array can receive optical images transmitted over a broad spectral range in the infrared and perform inference computation to process and recognize the images with 92% accuracy. The demonstrated bP image sensor array can be scaled up to build a more complex vision-sensory neural network, which will find many promising applications for distributed and remote multispectral sensing.</dc:description><dc:publisher/><dc:date>2022-12-01</dc:date><dc:nsf_par_id>10319321</dc:nsf_par_id><dc:journal_name>Nature Communications</dc:journal_name><dc:journal_volume>13</dc:journal_volume><dc:journal_issue>1</dc:journal_issue><dc:page_range_or_elocation/><dc:issn>2041-1723</dc:issn><dc:isbn/><dc:doi>https://doi.org/10.1038/s41467-022-29171-1</dc:doi><dcq:identifierAwardId>2025489; 1719797</dcq:identifierAwardId><dc:subject/><dc:version_number/><dc:location/><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>