Publisher Correction: Integrating photonics with silicon nanoelectronics for the next generation of systems on a chip.

In this Letter, owing to an error during the production process, the author affiliations were listed incorrectly. Affiliation number 5 (Colleges of Nanoscale Science and Engineering, State University of New York (SUNY)) was repeated, and affiliation numbers 6-8 were incorrect. In addition, the phrase "two oxide thickness variants" should have been "two gate oxide thickness variants". These errors have all been corrected online.

Integrating photonics with silicon nanoelectronics for the next generation of systems on a chip.

Electronic and photonic technologies have transformed our lives-from computing and mobile devices, to information technology and the internet. Our future demands in these fields require innovation in each technology separately, but also depend on our ability to harness their complementary physics through integrated solutions1,2. This goal is hindered by the fact that most silicon nanotechnologies-which enable our processors, computer memory, communications chips and image sensors-rely on bulk silicon substrates, a cost-effective solution with an abundant supply chain, but with substantial limitations for the integration of photonic functions. Here we introduce photonics into bulk silicon complementary metal-oxide-semiconductor (CMOS) chips using a layer of polycrystalline silicon deposited on silicon oxide (glass) islands fabricated alongside transistors. We use this single deposited layer to realize optical waveguides and resonators, high-speed optical modulators and sensitive avalanche photodetectors. We integrated this photonic platform with a 65-nanometre-transistor bulk CMOS process technology inside a 300-millimetre-diameter-wafer microelectronics foundry. We then implemented integrated high-speed optical transceivers in this platform that operate at ten gigabits per second, composed of millions of transistors, and arrayed on a single optical bus for wavelength division multiplexing, to address the demand for high-bandwidth optical interconnects in data centres and high-performance computing3,4. By decoupling the formation of photonic devices from that of transistors, this integration approach can achieve many of the goals of multi-chip solutions 5 , but with the performance, complexity and scalability of 'systems on a chip'1,6-8. As transistors smaller than ten nanometres across become commercially available 9 , and as new nanotechnologies emerge10,11, this approach could provide a way to integrate photonics with state-of-the-art nanoelectronics.

Roadmap on emerging hardware and technology for machine learning.

Recent progress in artificial intelligence is largely attributed to the rapid development of machine learning, especially in the algorithm and neural network models. However, it is the performance of the hardware, in particular the energy efficiency of a computing system that sets the fundamental limit of the capability of machine learning. Data-centric computing requires a revolution in hardware systems, since traditional digital computers based on transistors and the von Neumann architecture were not purposely designed for neuromorphic computing. A hardware platform based on emerging devices and new architecture is the hope for future computing with dramatically improved throughput and energy efficiency. Building such a system, nevertheless, faces a number of challenges, ranging from materials selection, device optimization, circuit fabrication and system integration, to name a few. The aim of this Roadmap is to present a snapshot of emerging hardware technologies that are potentially beneficial for machine learning, providing the Nanotechnology readers with a perspective of challenges and opportunities in this burgeoning field.

Sub-bandgap polysilicon photodetector in zero-change CMOS process for telecommunication wavelength.

We report a defect state based guided-wave photoconductive detector at 1360-1630 nm telecommunication wavelength directly in standard microelectronics CMOS processes, with zero in-foundry process modification. The defect states in the polysilicon used to define a transistor gate assists light absorption. The body crystalline silicon helps form an inverse ridge waveguide to confine optical mode. The measured responsivity and dark current at 25 V forward bias are 0.34 A/W and 1.4 µA, respectively. The 3 dB bandwidth of the device is 1 GHz.