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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Wireless System Development for GaN-Based Transmitters for Advanced Nuclear Reactor Environments

The market for consumer electronics is dominated by Si-based electronics. Many Si-based complementary metal–oxide–semiconductor (CMOS) devices are reaching their limitations in terms of switching frequencies, voltages, currents, and temperatures. Furthermore, these devices are widely known to be susceptible to ionizing radiation and neutrons. Advanced nuclear reactors, especially microreactors and small modular reactors, require wireless electronics that can survive larger neutron and gamma doses than Si CMOS. Because of their size, electronics will need to be placed closer to the reactor cores, and cabling capabilities may be limited. However, GaN high-electron-mobility transistors (HEMTs) have been shown to switch faster with higher gains, and they can achieve current and voltage limits beyond traditional Si CMOS. However, they have less market maturity and have undergone less testing. These GaN HEMTs have been shown to survive ionizing radiation with little effects, but the effects of neutron radiation remain widely unknown. In this report, a wireless electronic system capable of supporting multiple radiation-hardened (rad-hard) sensors is presented. The proposed transmission scheme was designed to be simple to increase the likelihood of success in the immature GaN HEMT process and in high-radiation environments. The transmission system was tested using software-defined radios to emulate the transmission scheme before the transmitter circuitry in the GaN process was developed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Overview of CMOS Sensors for Future Tracking Detectors

Depleted Complementary Metal-Oxide-Semiconductor (CMOS) sensors are emerging as one of the main candidate technologies for future tracking detectors in high luminosity colliders. Their capability of integrating the sensing diode into the CMOS wafer hosting the front-end electronics allows for reduced noise and higher signal sensitivity, due to the direct collection of the sensor signal by the readout electronics. They are suitable for high radiation environments due to the possibility of applying high depletion voltage and the availability of relatively high resistivity substrates. The use of a CMOS commercial fabrication process leads to their cost reduction and allows faster construction of large area detectors. In this contribution, a general perspective of the state of the art of CMOS detectors for High Energy Physics experiments is given. The main developments carried out with regard to these devices in the framework of the CERN RD50 collaboration are summarized.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Comparison of Hafnium Dioxide and Zirconium Dioxide Grown by Plasma-Enhanced Atomic Layer Deposition for the Application of Electronic Materials

We report the growth of nanoscale hafnium dioxide (HfO 2 ) and zirconium dioxide (ZrO 2 ) thin films using remote plasma-enhanced atomic layer deposition (PE-ALD), and the fabrication of complementary metal-oxide semiconductor (CMOS) integrated circuits using the HfO 2 and ZrO 2 thin films as the gate oxide. Tetrakis (dimethylamino) hafnium (Hf[N(CH 3 ) 2 ] 4 ) and tetrakis (dimethylamino) zirconium (IV) (Zr[N(CH 3 ) 2 ] 4 ) were used as the precursors, while O 2 gas was used as the reactive gas. The PE-ALD-grown HfO 2 and ZrO 2 thin films were analyzed using X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), and high-resolution transmission electron microscopy (HRTEM). The XPS measurements show that the ZrO 2 film has the atomic concentrations of 34% Zr, 2% C, and 64% O while the HfO 2 film has the atomic concentrations of 29% Hf, 11% C, and 60% O. The HRTEM and XRD measurements show both HfO 2 and ZrO 2 films have polycrystalline structures. n-channel and p-channel metal-oxide semiconductor field-effect transistors (nFETs and pFETs), CMOS inverters, and CMOS ring oscillators were fabricated to test the quality of the HfO 2 and ZrO 2 thin films as the gate oxide. Current-voltage (IV) curves, transfer characteristics, and oscillation waveforms were measured from the fabricated transistors, inverters, and oscillators, respectively. The experimental results measured from the HfO 2 and ZrO 2 thin films were compared.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Soft X-ray quantum efficiency of a commercial CMOS imaging sensor

The demonstrated performance and cost-effectiveness of complementary metal-oxide-semiconductor (CMOS) sensors make them a potentially attractive option for low-cost space-based X-ray observatories. We have previously reported on the performance of a commercially available backside-illuminated Sony IMX290LLR-C CMOS sensor and found it to offer X-ray spectral resolutions comparable to the charged coupled devices (CCDs) aboard Suzaku and Chandra and to have a sufficient radiation hardness for use in low Earth orbit. Here, in this work, we report on the quantum efficiency (QE) of this sensor, an essential metric for modeling the sensitivity of an instrument as an X-ray detector. Using the Advanced Photon Source at Argonne National Laboratory, we measure the soft X-ray QE of this CMOS sensor to be 0.28 ± 0.02 at a photon energy of 490.5 eV. This energy was chosen for its proximity to the astrophysically important O VII triplet emission lines (~574 eV) studied by the HaloSat mission. Although not surpassing that of the back-illuminated CCDs aboard Suzaku and Chandra, this QE compares favorably to that of the front-illuminated CCDs aboard the same observatories and is competitive with that of the silicon drift detectors used aboard HaloSat, making it a strong candidate for use on future X-ray small satellite (SmallSat) missions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Soft x-ray detection for small satellites with a commercial CMOS sensor at room temperature

Recently CMOS (complementary metal-oxide-semiconductor) sensors have progressed to a point where they may offer improved performance in imaging x-ray detection compared to the CCDs often used in x-ray satellites. We demonstrate x-ray detection in the soft x-ray band (250-1700 eV) by a commercially available back-illuminated Sony IMX290LLR CMOS sensor using the Advanced Photon Source at the Argonne National Laboratory. Additionally, while operating the device at room temperature, we measure energy resolutions (FWHM) of 47 eV at 250 eV and and 77 eV 1700 eV which are comparable to the performance of the Chandra ACIS and the Suzaku XIS. Furthermore, we demonstrate that the IMX290LLR can withstand radiation up to 17.1 krad, making it suitable for use on spacecraft in low earth orbit.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Topological Antiferromagnetic Van der Waals Phase in Topological Insulator/Ferromagnet Heterostructures Synthesized by a CMOS-Compatible Sputtering Technique

Breaking time-reversal symmetry by introducing magnetic order, thereby opening a gap in the topological surface state bands, is essential for realizing useful topological properties such as the quantum anomalous Hall and axion insulator states. In this work, a novel topological antiferromagnetic (AFM) phase is created at the interface of a sputtered, c-axis-oriented, topological insulator/ferromagnet heterostructure—Bi 2 Te 3 /Ni 80 Fe 20 because of diffusion of Ni in Bi 2 Te 3 (Ni-Bi 2 Te 3 ). The AFM property of the Ni-Bi2Te3 interfacial layer is established by observation of spontaneous exchange bias in the magnetic hysteresis loop and compensated moments in the depth profile of the magnetization using polarized neutron reflectometry. Analysis of the structural and chemical properties of the Ni-Bi2Te3 layer is carried out using selected-area electron diffraction, electron energy loss spectroscopy, and X-ray photoelectron spectroscopy. These studies, in parallel with first-principles calculations, indicate a solid-state chemical reaction that leads to the formation of Ni=Te bonds and the presence of topological antiferromagnetic (AFM) compound NiBi 2 Te 4 in the Ni-Bi 2 Te 3 interface layer. The Neél temperature of the Ni-Bi 2 Te 3 layer is ≈ 63 K, which is higher than that of typical magnetic topological insulators (MTIs). The presented results provide a pathway toward industrial complementary metal-oxide-semiconductor (CMOS)-process-compatible sputtered-MTI heterostructures, leading to novel materials for topological quantum devices.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Reconfigurable Cascaded Thermal Neuristors for Neuromorphic Computing

While the complementary metal-oxide semiconductor (CMOS) technology is the mainstream for the hardware implementation of neural networks, an alternative route is explored based on a new class of spiking oscillators called “thermal neuristors”, which operate and interact solely via thermal processes. Utilizing the insulator-to-metal transition (IMT) in vanadium dioxide, a wide variety of reconfigurable electrical dynamics mirroring biological neurons is demonstrated. Notably, inhibitory functionality is achieved just in a single oxide device, and cascaded information flow is realized exclusively through thermal interactions. To elucidate the underlying mechanisms of the neuristors, a detailed theoretical model is developed, which accurately reflects the experimental results. In conclusion, this study establishes the foundation for scalable and energy-efficient thermal neural networks, fostering progress in brain-inspired computing.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Epitaxial Growth of Large-Scale 2D CrTe 2 Films on Amorphous Silicon Wafers With Low Thermal Budget

2D van der Waals (vdW) magnets open landmark horizons in the development of innovative spintronic device architectures. However, their fabrication with large scale poses challenges due to high synthesis temperatures (>500 °C) and difficulties in integrating them with standard complementary metal-oxide semiconductor (CMOS) technology on amorphous substrates such as silicon oxide (SiO 2 ) and silicon nitride (SiN x ). Here, a seeded growth technique for crystallizing CrTe 2 films on amorphous SiN x /Si and SiO 2 /Si substrates with a low thermal budget is presented. This fabrication process optimizes large-scale, granular atomic layers on amorphous substrates, yielding a substantial coercivity of 11.5 kilo-oersted, attributed to weak intergranular exchange coupling. Field-driven Néel-type stripe domain dynamics explain the amplified coercivity. Moreover, the granular CrTe 2 devices on Si wafers display significantly enhanced magnetoresistance, more than doubling that of single-crystalline counterparts. Current-assisted magnetization switching, enabled by a substantial spin–orbit torque with a large spin Hall angle (85) and spin Hall conductivity (1.02 × 10 7 ℏ/2e Ω -1 m -1 ), is also demonstrated. These observations underscore the proficiency in manipulating crystallinity within integrated 2D magnetic films on Si wafers, paving the way for large-scale batch manufacturing of practical magnetoelectronic and spintronic devices, heralding a new era of technological innovation.

2D magnetic thin films↗
DOE OSTI2023

Direct Visualization of Charge Migration in Bilayer Tantalum Oxide Films by Multimodal Imaging

Inspired by biological neuromorphic computing, artificial neural networks based on crossbar arrays of bilayer tantalum oxide memristors have shown to be promising alternatives to conventional complementary metal-oxide-semiconductor (CMOS) architectures. In order to understand the driving mechanism in these oxide systems, tantalum oxide films are resistively switched by conductive atomic force microscopy (C-AFM), and subsequently imaged by kelvin probe force microscopy (KPFM) and spatially resolved time-of-flight secondary ion mass spectrometry (ToF-SIMS). These workflows enable induction and analysis of the resistive switching mechanism as well as control over the resistively switched region of the film. In this work it is shown that the resistive switching mechanism is driven by both current and electric field effects. Reversible oxygen motion is enabled by applying low (<1 V) electric fields, while high electric fields generate irreversible breakdown of the material (>1 V). Fully understanding oxygen motion and electrical effects in bilayer oxide memristor systems is a fundamental step toward the adoption of memristors as a neuromorphic computing technology.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Roadmap for Reaching the Potential of Brain-Derived Computing

Neuromorphic computing is a critical future technology for the computing industry, but it has yet to achieve its promise and has struggled to establish a cohesive research community. A large part of the challenge is that full realization of the potential of brain inspiration requires advances in both device hardware, computing architectures, and algorithms. This simultaneous development across technology scales is unprecedented in the computing field. This article presents a strategy, framed by market and policy pressures, for moving past these current technological and cultural hurdles to realize its full impact across technology. Achieving the full potential of brain-derived algorithms as well as post-complementary metal-oxide-semiconductor (CMOS) scaling neuromorphic hardware requires appropriately balancing the near-term opportunities of deep learning applications with the long-term potential of less understood opportunities in neural computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Applications of Strain-Coupled Magnetoelectric Composites

This article deals with research, development and future directions of magnetoelectric composites for practical devices applications. In the past 20 years there has been a surge of research in the area of multiferroics (MF) and magnetoelectrics (ME) due to their potential to replace existing technologies based only on ferroelectric or ferromagnetic materials. Some of the magnetoelectric composites show exceptionally high potential in the area of magnetic field sensors, however, work remains before commercialization can be realized. The cross coupling among various ferroic parameters in magnetoelectric composites is several orders higher than single phase magetoelectrics, which make its favorable for low detection (nT or pT) magnetic field sensors. Advances in both layered structures or controlled three-dimensional matrix composites for applications as magnetoelectric nonvolatile memory elements are both required. Robust cross-coupling among various parameters with more than four logic states and its compatibility with complementary-symmetry metal–oxide–semiconductor (CMOS) technology are the main requirements for heterostructure magnetoelectric thin films. The major hurdles in the area of magnetoelectric nonvolatile memory elements are poor interfacial properties and weak magnetoelectric coupling for high density fast read and write processes. Another potential area is strained coupled magneto-electric composites where magnetostriction mediated dimensional change in the magnetic layer effectively modulate the change in the dimension of piezoelectric layers via piezostriction, which leads to a strong ME coupling where their coupling magnitude is sufficient for magnetic field sensors. Energy harvesters based on magnetoelectric composites are also intriguing concepts to capture various types of waste energy, in the form mechanical vibration, pressure, wind energy, hydrothermal and waste temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Ultrafast radiographic imaging and tracking: An overview of instruments, methods, data, and applications

Ultrafast radiographic imaging and tracking (U-RadIT) use state-of-the-art ionizing particle and light sources to experimentally study sub-nanosecond transients or dynamic processes in physics, chemistry, biology, geology, materials science and other fields. These processes are fundamental to modern technologies and applications, such as nuclear fusion energy, advanced manufacturing, communication, and green transportation, which often involve one mole or more atoms and elementary particles, and thus are challenging to compute by using the first principles of quantum physics or other forward models. One of the central problems in U-RadIT is to optimize information yield through, e.g. high-luminosity X-ray and particle sources, efficient imaging and tracking detectors, novel methods to collect data, and large-bandwidth online and offline data processing, regulated by the underlying physics, statistics, and computing power. We review and highlight recent progress in: (a.) Detectors such as high-speed complementary metal-oxide semiconductor (CMOS) cameras, hybrid pixelated array detectors integrated with Timepix4 and other application-specific integrated circuits (ASICs), and digital photon detectors; (b.) U-RadIT modalities such as dynamic phase contrast imaging, dynamic diffractive imaging, and four-dimensional (4D) particle tracking; (c.) U-RadIT data and algorithms such as neural networks and machine learning, and (d.) Applications in ultrafast dynamic material science using XFELs, synchrotrons and laser-driven sources. Hardware-centric approaches to U-RadIT optimization are constrained by detector material properties, low signal-to-noise ratio, high cost and long development cycles of critical hardware components such as ASICs. Interpretation of experimental data, including comparisons with forward models, is frequently hindered by sparse measurements, model and measurement uncertainties, and noise. Alternatively, U-RadIT make increasing use of data science and machine learning algorithms, including experimental implementations of compressed sensing. Machine learning and artificial intelligence approaches, refined by physics and materials information, may also contribute significantly to data interpretation, uncertainty quantification and U-RadIT optimization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Rapid spatial analysis of surrogate TRISO fuel particles using laser-induced breakdown spectroscopy image analysis

Laser-induced breakdown spectroscopy (LIBS) mapping enables rapid elemental and spatial analysis of solid samples. In this work, surrogate TRi-structural ISOtropic (TRISO) particles with various layers consisting of Zr, W, C, and Si were used to demonstrate the use of a new thickness measurement tool developed to analyze elemental images generated from LIBS maps. Zr particles with varying outer-layer thicknesses ranging from 16 to 32 μm were measured with scanning electron microscopy with energy dispersive spectroscopy (SEM-EDS) and LIBS with both a complementary metal-oxide-semiconductor (CMOS) detector and an intensified charged coupled device (ICCD) detector. LIBS maps of particles were completed using CMOS and ICCD spectrometers with effective spatial resolutions of 4 and 2 μm, respectively. The novel thickness measurement tool identified layer regions within a LIBS map and then identified the locations of the boundaries between these layers. The tool then generated up to 1000 random profiles stemming radially from the center region, which were used to measure the layer thickness/radius. This image analysis tool demonstrated LIBS's ability to provide values comparable with SEM-EDS (3.7% relative difference) along with a 95% reduction in measurement time. Furthermore, the precision of these measurements was on par with the SEM-EDS measurements at <15% relative standard deviation. Following the analysis of the Zr particles, W particles with increased complexity (e.g., five versus three layers) were analyzed using both the CMOS and ICCD spectrometers simultaneously. The spatial dimensions were extracted with an average relative difference of 2.7% and an average relative standard deviation of 9%.

Andrews, Hunter B. [Oak Ridge National Laboratory ↗
DOE OSTI2024

Thermally generated magnonic spin currents in a polycrystalline gadolinium iron garnet thin film with perpendicular magnetic anisotropy

Rare-earth iron garnets (REIGs) are the benchmark systems for magnonics, including the longitudinal spin Seebeck effect (LSSE). While most research has focused on single-crystalline REIGs on complimentary garnet substrates, moving to more, cost-effective complementary metal-oxide semiconductor (CMOS)-compatible substrates is important to integrate REIG thin films with existing technology. In this regard, we grow a 130 nm-thick polycrystalline gadolinium iron garnet (GdIG) film on the Si/SiO2 substrate and investigate the temperature-dependent LSSE. Interestingly, the polycrystalline GdIG film exhibits perpendicular magnetic anisotropy (PMA) at room temperature which is induced by tensile in-plane (IP)-strain originating from the thermal-expansion mismatch between the GdIG film and the substrate during rapid thermal annealing. Further, a spin-reorientation transition from the out-of-plane IP direction below TS = 180 K is observed. Additionally, the film reveals a magnetic compensation temperature, TComp, of ≈240 K. The LSSE voltage not only demonstrates a sign-inversion around TComp, but also shows noticeable changes around TS. As compared to a single-crystalline GdIG film, the lower LSSE voltage for the polycrystalline GdIG is attributed to the higher effective magnetic anisotropy and enhanced magnon scattering at the grain boundaries. Our study not only paves the way for the cost-effective growth of CMOS-compatible REIG-based systems with PMA for magnonic memory and information processing applications, but also highlights the fact that the spincaloritronic and spin-insulatronic properties of the polycrystalline REIGs follow those of their single-crystalline counterparts with reduced spin-to-charge conversion efficiency through LSSE which can be tuned further by controlling the average gran size and interface engineering.

Physics↗
DOE OSTI2021

Low-temperature emergent neuromorphic networks with correlated oxide devices

Significance Designing neuromorphic hardware for cryoelectronics is an important area of research as the field of computing paradigms beyond complementary metal-oxide-semiconductor (CMOS) progresses. Superconductivity and metal−insulator transitions are two of the most celebrated emergent, collective properties found in quantum materials such as strongly correlated oxides. Here, we present simulations of artificial neural networks that can be designed by combining superconducting devices (e.g. Josephson junctions) with Mott metal−insulator transition−based tunable resistor devices. Our simulations show that 1) neurons and synapses can be seamlessly created, 2) their functions can be tuned via learning, and 3) controlling disorder by incorporating light ions enables exponential multiplicity of states. The results open up directions for incorporating emergent behavior seen in condensed matter into hardware design for artificial intelligence.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Atomic-scale polarization switching in wurtzite ferroelectrics

Ferroelectric wurtzites have the potential to revolutionize modern microelectronics because they are easily integrated with multiple mainstream semiconductor platforms. However, the electric fields required to reverse their polarization direction and unlock electronic and optical functions need substantial reduction for operational compatibility with complementary metal-oxide semiconductor (CMOS) electronics. To understand this process, we observed and quantified real-time polarization switching of a representative ferroelectric wurtzite (Al 0.94 B 0.06 N) at the atomic scale with scanning transmission electron microscopy. The analysis revealed a polarization reversal model in which puckered aluminum/boron nitride rings in the wurtzite basal planes gradually flatten and adopt a transient nonpolar geometry. Independent first-principles simulations reveal the details and energetics of the reversal process through an antipolar phase. Furthermore, this model and local mechanistic understanding are a critical initial step for property engineering efforts in this emerging material class.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Knowledge gaps for neuromorphic ionic computing

BACKGROUND Neuromorphic computing, inspired by the human brain’s ability to process information efficiently, represents a transformative approach to computation. In this Review, we explore the emerging field of neuromorphic ionic computing, which leverages ionic conduction and coupling to mimic neural processes, and identify critical knowledge gaps that must be addressed to realize its full potential. A central theme of the discussion is energy efficiency, a challenge that is both a limitation and an opportunity for this technology. Although complementary metal-oxide semiconductor (CMOS)–based neuromorphic technologies have made strides in scaling to billions of neurons and are increasingly applied in artificial intelligence and numerical computing, they remain orders of magnitude behind the human brain in terms of connectivity and energy efficiency. Neuromorphic ionic computing promises to overcome these limitations by leveraging the distinct architectural and operational principles of the brain. Our brains achieve this energy efficiency by combining several key features: using the same network elements to store and process information; using an incredibly complex and massively interconnected three-dimensional (3D) network of locally active elements that enables sparsity, robustness in the presence of noise, adaptation, and life-long learning; computing at comparatively low voltage and frequency; and last, taking advantage of a plethora of ions and small molecules as information carriers. Here, we propose that ionic computing systems can take advantage of similar features to achieve substantial gains in energy efficiency. ADVANCES Since the first reports of neuromorphic ionic behavior in nanofluidic channels, we have witnessed an explosion of reports that used ionic devices to produce synaptomimetic behaviors. However, achieving the goals of ionic computing requires not only implementation of much more sophisticated device functionality but also overcoming fundamental barriers in materials science, device architecture, and system integration. Current ionic devices, even those incorporating state-of-the-art materials, still suffer from limited functionality and stability, which restrict their performance and increase energy demands. Developing new materials with enhanced ionic properties is essential to overcome these limitations. Similarly, the design of neuromorphic devices must evolve to leverage the particular advantages of ionic processes. Existing architectures often follow a single-information-carrier logic of conventional electronics or are constructed of mesoscale fluidics, failing to capitalize on the energy-efficient mechanisms inherent to ionic systems or implement the multiple-information-carrier paradigm. Current neuromorphic chips focus on large-scale networks of analog memory elements based on mechanisms such as charge trap (flash), filamentary, phase change, or spin, which are built on top of a network of artificial CMOS neurons. Although such prototype networks have achieved impressive performance, it is difficult to envision how they can implement the key features such as massive connectivity, sophisticated plasticity, adaptability, sparsity, and “multichromatic” computing. Although small-scale devices have demonstrated promising results, integrating them, maintaining energy efficiency, and implementing temperature control as systems grow in complexity and size to computationally relevant scale remain major hurdles. Furthermore, interfacing neuromorphic ionic devices with existing computing technologies presents technical and conceptual challenges that will require innovative approaches that combine insights from neuroscience, materials science, and engineering. OUTLOOK Despite these challenges, the potential impact of neuromorphic ionic computing is profound with potential applications ranging from artificial intelligence to robotics and beyond. We also argue that neuromorphic ionic computing systems should not, at least in the beginning, compete with CMOS technologies but rather should focus on applications that require extreme energy efficiency with chemical and/or biological compatibility, such as biomedical applications (for example, brain-computer interfaces), environmental monitoring, and agricultural and food applications. Ultimately, this Review highlights the crucial role of interdisciplinary collaboration in advancing the field. Neuromorphic ionic computing is not merely a technological innovation; it represents a substantial step toward sustainable computation, aligning with the growing demand for energy-conscious solutions in a world that is increasingly reliant on data and computation.

Neuromorphic↗
DOE OSTI2025

Telecom-to-visible quantum frequency converter on a silicon nitride chip

Quantum frequency conversion serves a key role in the realization of hybrid quantum networks by interfacing between wavelength-incompatible platforms. Here we present what is believed to be the first quantum frequency converter connecting visible and telecom domains on a silicon nitride (SiN) chip, using Bragg-scattering four-wave mixing to upconvert heralded single photons from 1260 to 698 nm, which covers a 192 THz span. We examine the noise sources in SiN and devise approaches to suppress noise photons at the source and target frequencies to enable measurements at the single-photon level. We demonstrate an on-chip conversion efficiency of 5% in photon flux and describe design modifications that can be implemented to significantly improve it. Our results pave the way for the implementation of complementary metal-oxide-semiconductor (CMOS)-compatible devices in quantum networks.

59 BASIC BIOLOGICAL SCIENCES↗