Rigorous dynamic model of a silicon ring resonator with phase change material for a neuromorphic node.

The photonics platform has been considered increasingly promising for neuromorphic computing, due to its potential in providing low latency and energy efficient large-scale parallel connectivity. Phase change materials (PCMs) have been recently employed to introduce all-optical non-volatile memory in integrated photonic circuits, especially finding application as non-volatile weighting element in photonic artificial neural networks. Interestingly, these weighting elements can potentially be used as building blocks for large-scale networks that can autonomously adapt to their input, i.e. presenting the property of plasticity, similarly to the biological brain. In this work, we develop a computationally efficient dynamical model of a silicon ring resonator (RR) enhanced by a phase change material, namely Ge2Sb2Te5 (GST). We do so starting from two existing dynamical models (of a silicon RR and of a GST thin film on a straight silicon waveguide), but extending the optical equations to properly account for the high absorption and asymmetry in the ring due to the phase change material. Our model accounts for silicon nonlinear effects due to free carriers and temperature, as well as for the phase change of GST, whose energy efficiency and optical contrast can be enhanced by the RR resonant behaviour. We also restructure the optical equations so that the model can be efficiently employed in a modular way within a commercial software for system-level photonics simulations. Moreover, exploiting the developed model, we explore several design parameters and show that both speed and energy efficiency of memory operations can be enhanced by factors from six to ten. Also, we show that the achievable optical contrast due to GST phase change can be increased by more than a factor ten by leveraging the resonant properties of the RR, at the expense of higher optical loss. Finally, by exploiting the nonlinear dynamics arising in silicon RR networks, we show that a strong contrast is achievable while preserving energy efficiency.

On-chip sub-wavelength Bragg grating design based on novel low loss phase-change materials.

We propose a reconfigurable and non-volatile Bragg grating in the telecommunication C-band based on the combination of novel low-loss phase-change materials (specifically Ge2Sb2Se4Te1 and Sb2S3) with a silicon nitride platform. The Bragg grating is formed by arrayed cells of phase-change material, whose crystallisation fraction modifies the Bragg wavelength and extinction ratio. These devices could be used in integrated photonic circuits for optical communications applications in smart filters and Bragg mirrors and could also find use in tuneable ring resonators, Mach-Zehnder interferometers or frequency selectors for future laser on chip applications. In the case of Ge2Sb2Se4Te1, crystallisation produces a Bragg resonance shift up to ∼ 15 nm, accompanied with a large amplitude modulation (insertion loss of 22 dB). Using Sb2S3, low losses are presented in both states of the phase change material, obtaining a ∼ 7 nm red-shift in the Bragg wavelength. The gratings are evaluated for two period numbers, 100 and 200 periods. The number of periods determines the bandwidth and extinction ratio of the filters. Increasing the number of periods increases the extinction ratio and reflected power, also narrowing the bandwidth. This results in a trade-off between device size and performance. Finally, we combine both phase-change materials in a single Bragg grating to provide both frequency and amplitude modulation. A defect is introduced in the Sb2S3 Bragg grating, producing a high quality factor resonance (Q ∼ 104) which can be shifted by 7 nm via crystallisation. A GSST cell is then placed in the defect which can modulate the transmission amplitude from low loss to below -16 dB.

An optoelectronic framework enabled by low-dimensional phase-change films.

The development of materials whose refractive index can be optically transformed as desired, such as chalcogenide-based phase-change materials, has revolutionized the media and data storage industries by providing inexpensive, high-speed, portable and reliable platforms able to store vast quantities of data. Phase-change materials switch between two solid states--amorphous and crystalline--in response to a stimulus, such as heat, with an associated change in the physical properties of the material, including optical absorption, electrical conductance and Young's modulus. The initial applications of these materials (particularly the germanium antimony tellurium alloy Ge2Sb2Te5) exploited the reversible change in their optical properties in rewritable optical data storage technologies. More recently, the change in their electrical conductivity has also been extensively studied in the development of non-volatile phase-change memories. Here we show that by combining the optical and electronic property modulation of such materials, display and data visualization applications that go beyond data storage can be created. Using extremely thin phase-change materials and transparent conductors, we demonstrate electrically induced stable colour changes in both reflective and semi-transparent modes. Further, we show how a pixelated approach can be used in displays on both rigid and flexible films. This optoelectronic framework using low-dimensional phase-change materials has many likely applications, such as ultrafast, entirely solid-state displays with nanometre-scale pixels, semi-transparent 'smart' glasses, 'smart' contact lenses and artificial retina devices.

Plasmonically-enhanced all-optical integrated phase-change memory.

Integrated phase-change photonic memory devices offer a novel route to non-volatile storage and computing that can be carried out entirely in the optical domain, obviating the necessity for time and energy consuming opto-electrical conversions. Such memory devices generally consist of integrated waveguide structures onto which are fabricated small phase-change memory cells. Switching these cells between their amorphous and crystalline states modifies significantly the optical transmission through the waveguide, so providing memory, and computing, functionality. To carry out such switching, optical pulses are sent down the waveguide, coupling to the phase-change cell, heating it up, and so switching it between states. While great strides have been made in the development of integrated phase-change photonic devices in recent years, there is always a pressing need for faster switching times, lower energy consumption and a smaller device footprint. In this work, therefore, we propose the use of plasmonic enhancement of the light-matter interaction between the propagating waveguide mode and the phase-change cell as a means to faster, smaller and more energy-efficient devices. In particular, we propose a form of plasmonic dimer nanoantenna of significantly sub-micron size that, in simulations, offers significant improvements in switching speeds and energies. Write/erase speeds in the range 2 to 20 ns and write/erase energies in the range 2 to 15 pJ were predicted, representing improvements of one to two orders of magnitude when compared to conventional device architectures.

Reconfigurable phase-change meta-absorbers with on-demand quality factor control.

Perfect absorber type devices are well-suited to many applications, such as solar cells, spatial light modulators, bio-sensors, and highly-sensitive photo-detectors. In such applications, a method for the design and fabrication of devices in a simple and efficient way, while at the same time maintaining design control over the key performance characteristics of resonant frequency, reflection coefficient at resonance and quality factor, would be particularly advantageous. In this work we develop such a method, based on eigenmode analysis and critical coupling theory, and apply it to the design of reconfigurable phase-change metasurface absorber devices. To validate the method, the design and fabrication of a family of absorbers was carried out with a range of 'on-demand' quality factors, all operating at the same resonant frequency and able to be fabricated simply and simultaneously on the same chip. Furthermore, by switching the phase-change layer between its amorphous and crystalline states, we show that our devices can provide an active or reconfigurable functionality.

Can conventional phase-change memory devices be scaled down to single-nanometre dimensions?

The scaling potential of 'mushroom-type' phase-change memory devices is evaluated, down to single-nanometre dimensions, using physically realistic simulations that combine electro-thermal modelling with a Gillespie Cellular Automata phase-transformation approach. We found that cells with heater contact sizes as small as 6 nm could be successfully amorphized and re-crystallized (RESET and SET) using moderate excitation voltages. However, to enable the efficient formation of amorphous domes during RESET in small cells (heater contact diameters of 10 nm or less), it was necessary to improve the thermal confinement of the cell to reduce heat loss via the electrodes. The resistance window between the SET and RESET states decreased as the cell size reduced, but it was still more than an order of magnitude even for the smallest cells. As expected, the RESET current reduced as the cells got smaller; indeed, RESET current scaled with the inverse of the heater contact diameter and ultra-small RESET currents of only 19 µA were achieved for the smallest cells. Our results show that the conventional mushroom-type phase-change cell architecture is scalable and operable in the sub-10nm region.

Design of practicable phase-change metadevices for near-infrared absorber and modulator applications.

Phase-change chalcogenide alloys, such as Ge2Sb2Te5 (GST), have very different optical properties in their amorphous and crystalline phases. The fact that such alloys can be switched, optically or electrically, between such phases rapidly and repeatedly means that they have much potential for applications as tunable photonic devices. Here we incorporate chalcogenide phase-change films into a metal-dielectric-metal metamaterial electromagnetic absorber structure and design absorbers and modulators for operation at technologically important near-infrared wavelengths, specifically 1550 nm. Our design not only exhibits excellent performance (e.g. a modulation depth of ~77% and an extinction ratio of ~20 dB) but also includes a suitable means for protecting the GST layer from environmental oxidation and is well-suited, as confirmed by electro-thermal and phase-transformation simulations, to in situ electrical switching. We also present a systematic study of design optimization, including the effects of expected manufacturing tolerances on device performance and, by means of a sensitivity analysis, identify the most critical design parameters.

Event-driven adaptive optical neural network.

We present an adaptive optical neural network based on a large-scale event-driven architecture. In addition to changing the synaptic weights (synaptic plasticity), the optical neural network's structure can also be reconfigured enabling various functionalities (structural plasticity). Key building blocks are wavelength-addressable artificial neurons with embedded phase-change materials that implement nonlinear activation functions and nonvolatile memory. Using multimode focusing, the activation function features both excitatory and inhibitory responses and shows a reversible switching contrast of 3.2 decibels. We train the neural network to distinguish between English and German text samples via an evolutionary algorithm. We investigate both the synaptic and structural plasticity during the training process. On the basis of this concept, we realize a large-scale network consisting of 736 subnetworks with 16 phase-change material neurons each. Overall, 8398 neurons are functional, highlighting the scalability of the photonic architecture.

Chalcogenide optomemristors for multi-factor neuromorphic computation.

Neuromorphic hardware that emulates biological computations is a key driver of progress in AI. For example, memristive technologies, including chalcogenide-based in-memory computing concepts, have been employed to dramatically accelerate and increase the efficiency of basic neural operations. However, powerful mechanisms such as reinforcement learning and dendritic computation require more advanced device operations involving multiple interacting signals. Here we show that nano-scaled films of chalcogenide semiconductors can perform such multi-factor in-memory computation where their tunable electronic and optical properties are jointly exploited. We demonstrate that ultrathin photoactive cavities of Ge-doped Selenide can emulate synapses with three-factor neo-Hebbian plasticity and dendrites with shunting inhibition. We apply these properties to solve a maze game through on-device reinforcement learning, as well as to provide a single-neuron solution to linearly inseparable XOR implementation.

Polarization-selective reconfigurability in hybridized-active-dielectric nanowires.

Wavelength and polarization are two fundamental properties of light within which information can be encoded and (de)multiplexed. While wavelength-selective systems have widely proliferated, polarization-addressable active photonics has not seen notable progress, primarily because tunable and polarization-selective nanostructures have been elusive. Here, we introduce hybridized-active-dielectric (HAD) nanowires to achieve polarization-selective tunability. We then demonstrate the ability to use polarization as a parameter to selectively modulate the conductance of individual nanowires within a multi-nanowire system. By using polarization as the tunable vector, we show matrix-vector multiplication in a nanowire device configuration. While our HAD nanowires use phase-change materials as the active material, this concept is readily generalized to other active materials hybridized with dielectrics and thus has the potential in a broad range of applications from photonic memories and routing to polarization-multiplexed computing.

Optical and Thermal Design and Analysis of Phase-Change Metalenses for Active Numerical Aperture Control.

The control of a lens's numerical aperture has potential applications in areas such as photography and imaging, displays, sensing, laser processing and even laser-implosion fusion. In such fields, the ability to control lens properties dynamically is of much interest, and active meta-lenses of various kinds are under investigation due to their modulation speed and compactness. However, as of yet, meta-lenses that explicitly offer dynamic control of a lens's numerical aperture have received little attention. Here, we design and simulate active meta-lenses (specifically, focusing meta-mirrors) using chalcogenide phase-change materials to provide such control. We show that, operating at a wavelength of 3000 nm, our devices can change the numerical aperture by up to a factor of 1.85 and operate at optical intensities of the order of 1.2 × 109 Wm-2. Furthermore, we show the scalability of our design towards shorter wavelengths (visible spectrum), where we demonstrate a change in NA by a factor of 1.92.

Single-Step Fabrication of High-Performance Extraordinary Transmission Plasmonic Metasurfaces Employing Ultrafast Lasers.

Plasmonic metasurfaces based on the extraordinary optical transmission (EOT) effect can be designed to efficiently transmit specific spectral bands from the visible to the far-infrared regimes, offering numerous applications in important technological fields such as compact multispectral imaging, biological and chemical sensing, or color displays. However, due to their subwavelength nature, EOT metasurfaces are nowadays fabricated with nano- and micro-lithographic techniques, requiring many processing steps and carrying out in expensive cleanroom environments. In this work, we propose and experimentally demonstrate a novel, single-step process for the rapid fabrication of high-performance mid- and long-wave infrared EOT metasurfaces employing ultrafast direct laser writing. Microhole arrays composing extraordinary transmission metasurfaces were fabricated over an area of 4 mm2 in timescales of units of minutes, employing single pulse ablation of 40 nm thick Au films on dielectric substrates mounted on a high-precision motorized stage. We show how by carefully characterizing the influence of only three key experimental parameters on the processed micro-morphologies (namely, laser pulse energy, scan velocity, and beam shaping slit), we can have on-demand control of the optical characteristics of the extraordinary transmission effect in terms of transmission wavelength, quality factor, and polarization sensitivity of the resonances. To illustrate this concept, a set of EOT metasurfaces having different performances and operating in different spectral regimes has been successfully designed, fabricated, and tested. Comparison between transmittance measurements and numerical simulations has revealed that all the fabricated devices behave as expected, thus demonstrating the high performance, flexibility, and reliability of the proposed fabrication method. We believe that our findings provide the pillars for mass production of EOT metasurfaces with on-demand optical properties and create new research trends toward single-step laser fabrication of metasurfaces with alternative geometries and/or functionalities.

An integrated photonics engine for unsupervised correlation detection.

With more and more aspects of modern life and scientific tools becoming digitized, the amount of data being generated is growing exponentially. Fast and efficient statistical processing, such as identifying correlations in big datasets, is therefore becoming increasingly important, and this, on account of the various compute bottlenecks in modern digital machines, has necessitated new computational paradigms. Here, we demonstrate one such novel paradigm, via the development of an integrated phase-change photonics engine. The computational memory engine exploits the accumulative property of Ge2Sb2Te5 phase-change cells and wavelength division multiplexing property of optics in delivering fully parallelized and colocated temporal correlation detection computations. We investigate this property and present an experimental demonstration of identifying real-time correlations in data streams on the social media platform Twitter and high-traffic computing nodes in data centers. Our results demonstrate the use case of high-speed integrated photonics in accelerating statistical analysis methods.

Electronically Reconfigurable Photonic Switches Incorporating Plasmonic Structures and Phase Change Materials.

The ever-increasing demands for data processing and storage will require seamless monolithic co-integration of electronics and photonics. Phase-change materials are uniquely suited to fulfill this function due to their dual electro-optical sensitivity, nonvolatile retention properties, and fast switching dynamics. The extreme size disparity however between CMOS electronics and dielectric photonics inhibits the realization of efficient and compact electrically driven photonic switches, logic and routing elements. Here, the authors achieve an important milestone in harmonizing the two domains by demonstrating an electrically reconfigurable, ultra-compact and nonvolatile memory that is optically accessible. The platform relies on localized heat, generated within a plasmonic structure; this uniquely allows for both optical and electrical readout signals to be interlocked with the material state of the PCM while still ensuring that the writing operation is electrically decoupled. Importantly, by miniaturization and effective thermal engineering, the authors achieve unprecedented energy efficiency, opening up a path towards low-energy optoelectronic hardware for neuromorphic and in-memory computing.

Enhanced Performance and Diffusion Robustness of Phase-Change Metasurfaces via a Hybrid Dielectric/Plasmonic Approach.

Materials of which the refractive indices can be thermally tuned or switched, such as in chalcogenide phase-change alloys, offer a promising path towards the development of active optical metasurfaces for the control of the amplitude, phase, and polarization of light. However, for phase-change metasurfaces to be able to provide viable technology for active light control, in situ electrical switching via resistive heaters integral to or embedded in the metasurface itself is highly desirable. In this context, good electrical conductors (metals) with high melting points (i.e., significantly above the melting point of commonly used phase-change alloys) are required. In addition, such metals should ideally have low plasmonic losses, so as to not degrade metasurface optical performance. This essentially limits the choice to a few noble metals, namely, gold and silver, but these tend to diffuse quite readily into phase-change materials (particularly the archetypal Ge2Sb2Te5 alloy used here), and into dielectric resonators such as Si or Ge. In this work, we introduce a novel hybrid dielectric/plasmonic metasurface architecture, where we incorporated a thin Ge2Sb2Te5 layer into the body of a cubic silicon nanoresonator lying on metallic planes that simultaneously acted as high-efficiency reflectors and resistive heaters. Through systematic studies based on changing the configuration of the bottom metal plane between high-melting-point diffusive and low-melting-point nondiffusive metals (Au and Al, respectively), we explicitly show how thermally activated diffusion can catastrophically and irreversibly degrade the optical performance of chalcogenide phase-change metasurface devices, and how such degradation can be successfully overcome at the design stage via the incorporation of ultrathin Si3N4 barrier layers between the gold plane and the hybrid Si/Ge2Sb2Te5 resonators. Our work clarifies the importance of diffusion of noble metals in thermally tunable metasurfaces and how to overcome it, thus helping phase-change-based metasurface technology move a step closer towards the realization of real-world applications.

In-memory computing on a photonic platform.

Collocated data processing and storage are the norm in biological computing systems such as the mammalian brain. As our ability to create better hardware improves, new computational paradigms are being explored beyond von Neumann architectures. Integrated photonic circuits are an attractive solution for on-chip computing which can leverage the increased speed and bandwidth potential of the optical domain, and importantly, remove the need for electro-optical conversions. Here we show that we can combine integrated optics with collocated data storage and processing to enable all-photonic in-memory computations. By employing nonvolatile photonic elements based on the phase-change material, Ge2Sb2Te5, we achieve direct scalar and matrix-vector multiplication, featuring a novel single-shot Write/Erase and a drift-free process. The output pulse, carrying the information of the light-matter interaction, is the result of the computation. Our all-optical approach is novel, easy to fabricate and operate, and sets the stage for development of entirely photonic computers.

Plasmonic nanogap enhanced phase-change devices with dual electrical-optical functionality.

Modern-day computers rely on electrical signaling for the processing and storage of data, which is bandwidth-limited and power hungry. This fact has long been realized in the communications field, where optical signaling is the norm. However, exploiting optical signaling in computing will require new on-chip devices that work seamlessly in both electrical and optical domains, without the need for repeated electrical-to-optical conversion. Phase-change devices can, in principle, provide such dual electrical-optical operation, but assimilating both functionalities into a single device has so far proved elusive owing to conflicting requirements of size-limited electrical switching and diffraction-limited optical response. Here, we combine plasmonics, photonics, and electronics to deliver an integrated phase-change memory cell that can be electrically or optically switched between binary or multilevel states. Crucially, this device can also be simultaneously read out both optically and electrically, offering a new strategy for merging computing and communications technologies.

Engineering Interface-Dependent Photoconductivity in Ge2Sb2Te5 Nanoscale Devices.

Phase-change materials are increasingly being explored for photonics applications, ranging from high-resolution displays to artificial retinas. Surprisingly, our understanding of the underlying mechanism of light-matter interaction in these materials has been limited to photothermal crystallization because of its relevance in applications such as rewritable optical discs. Here, we report a photoconductivity study of nanoscale thin films of phase-change materials. We identify strong photoconductive behavior in phase-change materials, which we show to be a complex interplay of three independent mechanisms: photoconductive, photoinduced crystallization, and photoinduced thermoelectric effects. We find that these effects also congruously contribute to a substantial photovoltaic effect, even in notionally symmetric devices. Notably, we show that device engineering plays a decisive role in determining the dominant mechanism; the contribution of the photothermal effects to the extractable photocurrent can be reduced to <0.4% by varying the electrodes and device geometry. We then show that the contribution of these individual effects to the photoresponse is phase-dependent with the amorphous state being more photoactive than the crystalline state and that a reversible change occurs in the charge transport from thermionic to tunnelling during phase transformation. Finally, we demonstrate photodetectors with an order of magnitude tunability in photodetection responsivity and bandwidth using these materials. Our results provide insights to the photophysics of phase-change materials and highlight their potential in future optoelectronics.

Device-Level Photonic Memories and Logic Applications Using Phase-Change Materials.

Inspired by the great success of fiber optics in ultrafast data transmission, photonic computing is being extensively studied as an alternative to replace or hybridize electronic computers, which are reaching speed and bandwidth limitations. Mimicking and implementing basic computing elements on photonic devices is a first and essential step toward all-optical computers. Here, an optical pulse-width modulation (PWM) switching of phase-change materials on an integrated waveguide is developed, which allows practical implementation of photonic memories and logic devices. It is established that PWM with low peak power is very effective for recrystallization of phase-change materials, in terms of both energy efficiency and process control. Using this understanding, multilevel photonic memories with complete random accessibility are then implemented. Finally, programmable optical logic devices are demonstrated conceptually and experimentally, with logic "OR" and "NAND" achieved on just a single integrated photonic phase-change cell. This study provides a practical and elegant technique to optically program photonic phase-change devices for computing applications.

A New Facile Route to Flexible and Semi-Transparent Electrodes Based on Water Exfoliated Graphene and their Single-Electrode Triboelectric Nanogenerator.

Wearable technologies are driving current research efforts to self-powered electronics, for which novel high-performance materials such as graphene and low-cost fabrication processes are highly sought.The integration of high-quality graphene films obtained from scalable water processing approaches in emerging applications for flexible and wearable electronics is demonstrated. A novel method for the assembly of shear exfoliated graphene in water, comprising a direct transfer process assisted by evaporation of isopropyl alcohol is developed. It is shown that graphene films can be easily transferred to any target substrate such as paper, flexible polymeric sheets and fibers, glass, and Si substrates. By combining graphene as the electrode and poly(dimethylsiloxane) as the active layer, a flexible and semi-transparent triboelectric nanogenerator (TENG) is demonstrated for harvesting energy. The results constitute a new step toward the realization of energy harvesting devices that could be integrated with a wide range of wearable and flexible technologies, and opens new possibilities for the use of TENGs in many applications such as electronic skin and wearable electronics.