H.-S. Philip Wong

Stanford University | SU · Department of Electrical Engineering

Semiconducting carbon nanotubes are robust molecules with nanometer-scale diameters that can be used in field-effect transistors, from larger thin-film implementation to devices that work in conjunction with silicon electronics, and can potentially be used as a platform for high-performance digital electronics as well as radio-frequency and sensing...

Hafnia-based ferroelectric thin films are promising for semiconductor memory and neuromorphic computing applications. Amorphous, as-deposited, thin-film binary alloys of HfO2 and ZrO2 transform to the metastable, orthorhombic ferroelectric phase during post-deposition annealing and cooling. This transformation is generally thought to involve format...

Resistance drift in phase change memory (PCM) reduces the accuracy of analog computing applications such as neural network inference. Recently, PCMs based on superlattice (SL) phase change layers have shown low resistance drift, however the origin of this low drift remains unexplored. Here, we uncover that resistance drift in SL-PCM based on altern...

Carbon nanotube field effect transistors (CNFETs) have potential applications in future logic technology as they display good electrostatic control and excellent transport properties. However, contact resistance and leakage currents could limit scaling of CNFETs. Non-equilibrium Green’s function (NEGF) simulation investigates that coupling between...

Superlattice (SL) phase change materials have shown promise to reduce the switching current and resistance drift of phase change memory (PCM). However, the effects of internal SL interfaces and intermixing on PCM performance remain unexplored, although these are essential to understand and ensure reliable memory operation. Here, using nanometer-thi...

Low-dimensional (low-D) semiconductors such as carbon nanotubes (CNTs) and 2-D materials are promising channel materials for nanoscale field-effect transistors (FETs) due to their superior electrostatic control. However, classical scale length theory (SLT) does not incorporate the effect of channel extensions, which becomes crucial for thin channel...

Gradual switching between multiple resistance levels is desirable for analog in-memory computing using resistive random-access memory (RRAM). However, the filamentary switching of $HfO_x$-based conventional RRAM often yields only two stable memory states instead of gradual switching between multiple resistance states. Here, we demonstrate that a th...

Semiconductor innovation drives improvements to technologies that are critical to modern society. The country that successfully accelerates semiconductor innovation is positioned to lead future semiconductor-driven industries and benefit from the resulting economic growth. It is our view that a next generation infrastructure is necessary to acceler...

Ferroelectric switching is demonstrated in CeO2‐doped Hf0.5Zr0.5O2 (HZCO) thin films with application in back‐end‐of‐line compatible embedded memories. At low cerium oxide doping concentrations (2.0–5.6 mol%), the ferroelectric orthorhombic phase is stabilized after annealing at temperatures below 400 °C. HZCO ferroelectrics show reliable switching...

Carbon nanotube (CNT) transistors exemplify the fundamental tradeoff between desirable high mobility and undesirable leakage current due to the small effective mass and bandgap. To understand leakage current limits in high-speed CNT transistors, electrical bandgaps are extracted on 12 single-CNT top-gate MOSFETs from the energy gap between thermion...

Emerging nonvolatile memory technologies are promising due to their anticipated capacity benefits, nonvolatility, and zero idle energy. One of the most promising candidates is resistive random access memory (RRAM) based on resistive switching (RS). This paper reviews the development of RS device technology including the fundamental physics, materia...

Large switching current density and resistance drift remain challenges for phase change memory (PCM) in data storage and neuromorphic computing applications. Here, we address these by electro-thermal and structural confinement in a GeTe/Sb2Te3 superlattice PCM (SL-PCM) with thermally-induced phase change, while observing scalability with bottom ele...

One of the major roadblocks for filamentary type resistive random access memory is variations in both the write voltage and the read resistance. The variation is inevitable because of the stochastic nature of oxygen ion movement inside the metal oxide. In this letter, we show that by inserting a thin SnO <sub xmlns:mml="http://www.w3.org/1998/Math/...

We present a DevIce-to-System Performance EvaLuation (DISPEL) workflow that integrates transistor and interconnect modeling, parasitic extraction, standard cell library characterization, logic synthesis, cell placement and routing, and timing analysis to evaluate system-level performance of new CMOS technologies. As the impact of parasitic resistan...

Learning from a few examples (one/few-shot learning) on the fly is a key challenge for on-device machine intelligence. We present the first chip-level demonstration of one-shot learning with Stanford Associative memory for Programmable, Integrated Edge iNtelligence via life-long learning and Search (SAPIENS), a resistive random access memory (RRAM)...

Flexing computer memory Phase change materials leverage changes in structure into differences in electrical resistance that are attractive for computer memory and processing applications. Khan et al . developed a flexible phase change memory device with layers of antimony telluride and germanium telluride deposited directly on a flexible polyimide...

Two-dimensional (2D) semiconductors have been proposed for heterogeneous integration with existing silicon technology; however, their chemical vapor deposition (CVD) growth temperatures are often too high. Here, we demonstrate direct CVD solid-source precursor synthesis of continuous monolayer (1L) MoS$_2$ films at 560 C in 50 min, within the 450-t...

Realizing today's cloud-level artificial intelligence functionalities directly on devices distributed at the edge of the internet calls for edge hardware capable of processing multiple modalities of sensory data (e.g. video, audio) at unprecedented energy-efficiency. AI hardware architectures today cannot meet the demand due to a fundamental "memor...

HfO₂-based resistive RAM (RRAM) is an emerging nonvolatile memory technology that has recently been shown capable of storing multiple bits-per-cell. The energy/delay costs of an RRAM write operation are dependent on the number of pulses required for RRAM programming. The pulse count is often large when existing programming approaches are used for m...

Two-dimensional (2D) semiconductors are promising candidates for scaled transistors because they are immune to mobility degradation at the monolayer limit. However, sub-10 nm scaling of 2D semiconductors, such as MoS2, is limited by the contact resistance. In this work, we show for the first time a statistical study of Au contacts to chemical vapor...

Learning from a few examples (one/few-shot learning) on the fly is a key challenge for on-device machine intelligence. We present the first chip-level demonstration of one-shot learning using a 2T-2R resistive RAM (RRAM) non-volatile associative memory (AM) as the backend of memory-augmented neural networks (MANNs). The 64-kbit fully integrated RRA...

We demonstrate single crystal growth of wafer-scale hexagonal boron nitride (hBN), an insulating atomic thin monolayer, on high-symmetry index surface plane Cu(111). The unidirectional epitaxial growth is guaranteed by large binding energy difference, ~0.23 eV, between A- and B-steps edges on Cu(111) docking with BN clusters, confirmed by density f...

The rapid growth and development of technology has had significant implications for healthcare, personalized medicine, and our understanding of biology. In this work, we leverage the miniaturization of electronics to realize the first demonstration of wireless detection and communication of an electronic device inside a cell. This is a significant...

Down‐scaling of transistor size in the lateral dimensions must be accompanied by a corresponding reduction in the channel thickness to ensure sufficient gate control to turn off the transistor. However, the carrier mobility of 3D bulk semiconductors degrades rapidly as the body thickness thins down due to more pronounced surface scattering. Two‐dim...

Hardware for deep neural network (DNN) inference often suffers from insufficient on-chip memory, thus requiring accesses to separate memory-only chips. Such off-chip memory accesses incur considerable costs in terms of energy and execution time. Fitting entire DNNs in on-chip memory is challenging due, in particular, to the physical size of the tec...

Increasing computation demand of machine learning (ML) applications (recommender system, image classification, speech recognition, and so on) calls for the development of specialized hardware for ML and neuromorphic computing. New memories, such as resistive random access memory (RRAM), can be used to store weights of neural networks and to acceler...

High switching current density has been a key bottleneck for phase change memory (PCM) technology. Here, we demonstrate interfacial thermoelectric heating (TEH) as a promising way of tackling this challenge. We use TEH induced by a thin Bi <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> Te <sub...

Self-Assembly, a process in which molecules, polymers, and particles are driven by local interactions to organize into patterns and functional structures, is being exploited in advancing silicon electronics and in emerging, unconventional electronics. Silicon electronics has relied on lithographic patterning of polymer resists at progressively smal...

The success of semiconductor electronics is built on the creation of compact, low-power switching elements that offer routing, logic, and memory functions. The availability of nanoscale optical switches could have a similarly transformative impact on the development of dynamic and programmable metasurfaces, optical neural networks, and quantum info...

Carbon nanotubes (CNTs) have great potential for future high-performance and energy-efficient transistor technology. To realize this potential, methods to dope the CNTs need to be developed to achieve low parasitic resistance of the transistor. Two key issues present themselves: (a) understanding the doping mechanism of the various methods and (b)...

To increase the density of magnetoresistive random access memory (MRAM) beyond the 1T1MTJ MRAM cell in use today, the design space for 1S1MTJ MRAM array is analyzed by cooptimizing both selectors and MTJs. Current low-resistance MTJs for 1T1MTJ MRAM are not suitable for 1S1MTJ MRAM. Threshold-type selectors would induce a strong read disturb on the...

Coming generations of information technology will process unprecedented amounts of loosely-structured data, including streaming video and audio, natural languages, real-time sensor readings, contextual environments, or even brain signals. The computational demands of these abundant-data applications, such as deep learning-based AI, far exceed the c...

Nanoscale semiconductor technology has been a key enabler of the computing revolution. It has done so via advances in new materials and manufacturing processes that resulted in the size of the basic building block of computing systems - the logic switch and memory devices - being reduced into the nanoscale regime. Nanotechnology has provided increa...

The exponential growth in data generation and large-scale data analysis creates an unprecedented need for inexpensive, low-latency, and high-density information storage. This need has motivated significant research into multi-level memory systems that can store multiple bits of information per device. Although both the memory state of these devices...

Since its inception, the semiconductor industry has used a physical dimension (the minimum gate length of a transistor) as a means to gauge continuous technology advancement. This metric is all but obsolete today. As a replacement, we propose a density metric, which aims to capture how advances in semiconductor device technologies enable system-lev...

Ultrathin two-dimensional (2D) semiconducting layered materials offer great potential for extending Moore’s law of the number of transistors in an integrated circuit¹. One key challenge with 2D semiconductors is to avoid the formation of charge scattering and trap sites from adjacent dielectrics. An insulating van der Waals layer of hexagonal boron...

One viable solution for continuous reduction in energy-per-operation is to rethink functionality to cope with uncertainty by adopting computational approaches that are inherently robust to uncertainty. It requires a novel look at data representations, associated operations, and circuits, and at materials and substrates that enable them. 3D integrat...

We study highly confined plasmons in individual single-walled carbon nanohrbe nanoantennas in the mid-infrared regime. This work paves the way for extreme light-matter interactions at the nanoscale and quanttrm plasmonics.

Resistive switching memory (RSM) shows potentials for high-capacity storage because of its simple cell structure, small footprint, and good scalability. This two-part article discusses how to implement ultrahigh-density (~terabits) storage with RSM covering design considerations from device to memory array architecture. In Part I of this two-part a...

Using the reduced resistor network developed in Part I of this two-part article, we present practical design guidelines from device to architecture levels to achieve ultrahigh-density 3-D vertical resistive switching memory (VRSM). We first design both hexagon and comb arrays using 7-nm FinFET as pillar driving transistors (pillar drivers). Small-f...

The demands of future applications in computing (from self-driving cars to bioinformatics) overwhelm the projected capabilities of current electronic systems. The need to process unprecedented amounts of loosely structured data is driving the push for ultradense and fine-grained integration of traditionally off-chip components (e.g., sensors, memor...

For high-volume manufacturing of 2-D transistors, area-selective chemical reaction deposition (CVD) growth is able to provide good-quality 2-D layers and may be more effective than exfoliation from bulk crystals or wet/dry transfer of large-area as-grown 2-D layers. We have successfully grown continuous and uniform WS <sub xmlns:mml="http://www.w3....

The manipulation of the amorphous to crystalline phase transition observed in chalcogenide glasses for non-volatile memory applications has been studied for many years since its initial conception. However‚ only recently has innovation in both materials development and memory device architecture enabled phase change random access memory (PCRAM) to...

As the physical dimensions of a transistor gate continue to shrink to a few atoms, performance can be increasingly determined by the limited electronic density of states (DOS) in the gate and the gate quantum capacitance (CQ). We demonstrate the impact of gate CQ and the dimensionality of the gate electrode on the performance of nanoscale transisto...

The recent surge of interest in brain-inspired computing and power-efficient electronics has dramatically bolstered development of computation and communication using neuron-like spiking signals. Devices that can produce rapid and energy-efficient spiking could significantly advance these applications. Here we demonstrate DC-current or voltage-driv...

Vanadium dioxide (VO2) has been widely studied for its rich physics and potential applications, undergoing a prominent insulator-metal transition (IMT) near room temperature. The transition mechanism remains highly debated, and little is known about the IMT at nanoscale dimensions. To shed light on this problem, here we use ~1 nm wide carbon nanotu...

Neuromorphic visual systems have considerable potential to emulate basic functions of the human visual system even beyond the visible light region. However, the complex circuitry of artificial visual systems based on conventional image sensors, memory and processing units presents serious challenges in terms of device integration and power consumpt...

Vanadium dioxide (VO2) has been widely studied for its rich physics and potential applications, undergoing a prominent insulator-metal transition (IMT) near room temperature. The transition mechanism remains highly debated, and little is known about the IMT at nanoscale dimensions. To shed light on this problem, here we use ~1 nm wide carbon nanotu...

Deep neural network (DNN) inference tasks have become ubiquitous workloads on mobile SoCs and demand energy-efficient hardware accelerators. Mobile DNN accelerators are heavily area-constrained, with only minimal on-chip SRAM, which results in heavy use of inefficient off-chip DRAM. With diminishing returns from conventional silicon technology scal...

Phase Change Memory (PCM) is a leading candidate for next generation data storage, but it typically suffers from high switching (RESET) current density (20–30 MA/cm²). Interfacial Phase Change Memory (IPCM) is a type of PCM using multilayers of Sb2Te3/GeTe, with up to 100× lower reported RESET current compared to the standard Ge2Sb2Te5-based PCM. S...

Carbon nanotube (CNT) thin-film transistor (TFT) is a promising candidate for flexible and wearable electronics. However, it usually suffers from low semiconducting tube purity, low device yield, and the mismatch between p- and n-type TFTs. Here, we report low-voltage and high-performance digital and analog CNT TFT circuits based on high-yield (19....

Threshold switches, which typically exhibit an abrupt increase in current at an onset voltage, have been used as selector devices to suppress leakage current in crosspoint arrays of two-terminal resistive switching memory devices. One of the most important metrics for selector devices is the leakage or low-voltage current, which limits the maximum...

Reliability of 80-, 100-, and 120-nm wide copper interconnects is improved using in situ grown graphene as a capping material. The graphene-capped Cu wires exhibit 2.4–3.5 $\times $ longer electromigration (EM) lifetime than thermally annealed Cu. In addition, the Cu resistivity is reduced by about 12%–30% and the breakdown current density is in...

The recent surge of interest in brain-inspired computing and power-efficient electronics has dramatically bolstered development of computation and communication using neuron-like spiking signals. Devices that can produce rapid and energy-efficient spiking could significantly advance these applications. Here we demonstrate DC-current or voltage-driv...

The measurement of inhomogeneous conductivity in optically crystallized, amorphous Ge 2 Sb 2 Te 5 (GST) films is demonstrated via scanning microwave impedance microscopy (MIM). Qualitative consistency with expectations is demonstrated in spots crystallized by focused coherent light at various intensities, exposure times, and film thicknesses. The c...

Phase change memory (PCM) is an emerging data storage technology, however its programming is thermal in nature and typically not energy-efficient. Here we reduce the switching power of PCM through the combined approaches of filamentary contacts and thermal confinement. The filamentary contact is formed through an oxidized TiN layer on the bottom el...

Ternary content-addressable memory (TCAM) is specialized hardware that can perform in-memory search and pattern matching for data-intensive applications. However, achieving TCAMs with high search capacity, good area efficiency and good energy efficiency remains a challenge. Here, we show that two-transistor–two-resistor (2T2R) transition metal dich...