Freeform direct-write and rewritable photonic integrated circuits in phase-change thin films.

Photonic integrated circuits (PICs) with rapid prototyping and reprogramming capabilities promise revolutionary impacts on a plethora of photonic technologies. We report direct-write and rewritable photonic circuits on a low-loss phase-change material (PCM) thin film. Complete end-to-end PICs are directly laser-written in one step without additional fabrication processes, and any part of the circuit can be erased and rewritten, facilitating rapid design modification.

Programmable black phosphorus image sensor for broadband optoelectronic edge computing.

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).

Long-range transport of 2D excitons with acoustic waves.

Excitons are elementary optical excitation in semiconductors. The ability to manipulate and transport these quasiparticles would enable excitonic circuits and devices for quantum photonic technologies. Recently, interlayer excitons in 2D semiconductors have emerged as a promising candidate for engineering excitonic devices due to their long lifetime, large exciton binding energy, and gate tunability.

Harnessing optoelectronic noises in a photonic generative network.

Integrated optoelectronics is emerging as a promising platform of neural network accelerator, which affords efficient in-memory computing and high bandwidth interconnectivity. The inherent optoelectronic noises, however, make the photonic systems error-prone in practice. It is thus imperative to devise strategies to mitigate and, if possible, harness noises in photonic computing systems.

A CAN-Bus Lightweight Authentication Scheme.

The design of the Controller Area Network (CAN bus) did not account for security issues and, consequently, attacks often use external mobile communication interfaces to conduct eavesdropping, replay, spoofing, and denial-of-service attacks on a CAN bus, posing a risk to driving safety. Numerous studies have proposed CAN bus safety improvement techniques that emphasize modifying the original CAN bus method of transmitting frames. These changes place additional computational burdens on electronic control units cause the CAN bus to lose the delay guarantee feature.

Programmable phase-change metasurfaces on waveguides for multimode photonic convolutional neural network.

Neuromorphic photonics has recently emerged as a promising hardware accelerator, with significant potential speed and energy advantages over digital electronics for machine learning algorithms, such as neural networks of various types. Integrated photonic networks are particularly powerful in performing analog computing of matrix-vector multiplication (MVM) as they afford unparalleled speed and bandwidth density for data transmission. Incorporating nonvolatile phase-change materials in integrated photonic devices enables indispensable programming and in-memory computing capabilities for on-chip optical computing.

On-the-fly closed-loop materials discovery via Bayesian active learning.

Active learning-the field of machine learning (ML) dedicated to optimal experiment design-has played a part in science as far back as the 18th century when Laplace used it to guide his discovery of celestial mechanics. In this work, we focus a closed-loop, active learning-driven autonomous system on another major challenge, the discovery of advanced materials against the exceedingly complex synthesis-processes-structure-property landscape. We demonstrate an autonomous materials discovery methodology for functional inorganic compounds which allow scientists to fail smarter, learn faster, and spend less resources in their studies, while simultaneously improving trust in scientific results and machine learning tools.

Nonvolatile Electrically Reconfigurable Integrated Photonic Switch Enabled by a Silicon PIN Diode Heater.

Reconfigurability of photonic integrated circuits (PICs) has become increasingly important due to the growing demands for electronic-photonic systems on a chip driven by emerging applications, including neuromorphic computing, quantum information, and microwave photonics. Success in these fields usually requires highly scalable photonic switching units as essential building blocks. Current photonic switches, however, mainly rely on materials with weak, volatile thermo-optic or electro-optic modulation effects, resulting in large footprints and high energy consumption.

Effects of Rhizome Integration on the Water Physiology of Clones Under Heterogeneous Water Stress.

Water is crucial to plant growth and development. Under heterogeneous environmental water deficiency, physiological integration of the rhizomatous clonal plant triggers a series of physiological cascades, which induces both signaling and physiological responses. It is known that the rhizome of , which connects associated clonal ramets, has important significance in this physiological integration.

A study of lateral Schottky contacts in WSe2 and MoS2 field effect transistors using scanning photocurrent microscopy.

Schottky contacts, formed at metal/semiconductor interfaces, always have a large impact on the performance of field-effect transistors (FETs). Here, we report the experimental studies of Schottky contacts in two-dimensional (2D) transition metal dichalcogenide (TMDC) FET devices. We use scanning photocurrent microscopy (SPCM) to directly probe the spatial distribution of the in-plane lateral Schottky depletion regions at the metal/2D-TMDC interfaces.

Immunohistochemistry as a quick screening method for clinical detection of BRAF(V600E) mutation in melanoma patients.

With the increased uses of targeted therapeutics, diagnostic detection of target mutations becomes essential for the effective clinical applications of targeted therapeutics. Currently, there are two types of methods detecting target mutations in clinics: one is based on DNA sequence and the other uses the newly developed mutation-specific antibodies recognizing mutated proteins. Each method has its own advantages and disadvantages.