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IEDM 2016 Next Week!

By Dick James, Senior Technology Analyst, Chipworks

On December 3rd – 7th , the good and the great of the electron device world will make their usual pilgrimage to San Francisco for the 2016 IEEE International Electron Devices Meeting. To quote the conference website front page, IEDM is “is the world’s preeminent forum for reporting technological breakthroughs in the areas of semiconductor and electronic device technology, design, manufacturing, physics, and modeling. IEDM is the flagship conference for nanometer-scale CMOS transistor technology, advanced memory, displays, sensors, MEMS devices, novel quantum and nano-scale devices and phenomenology, optoelectronics, devices for power and energy harvesting, high-speed devices, as well as process technology and device modeling and simulation.”

That’s a pretty broad range of topics, but from my perspective at Chipworks, focused on the analysis of chips that have made it to production, it’s the conference where companies strut their technology, and post some of the research that may make it into real product in the next few years. Though these days process papers actually tend to be after the launch of the relevant product, such is the preoccupation with trade secrecy.

In the last few weeks I’ve gone through the advance program, and here’s my look at what’s coming up, in more or less chronological order. As usual there are overlapping sessions with interesting papers in parallel slots, but we’ll take the decision as to which to attend on the conference floor.


Again this year the conference starts on the Saturday afternoon, with a set of six 90-minute tutorials on a range of leading-edge topics:

The first three are from 2.45 – 4.15, and the remainder from 4.30 – 6.00. This year I hope to make it to the Physical Characterization session, and possibly the IoT talk at 4.30.

On Sunday December 14th, we start with the short courses, “Technology Options at the 5-Nanometer Node” and “Design/Technology Enablers for Computing Applications”.

Last year the process short course was “Emerging CMOS Technology at 5 nm and Beyond”, so I guess we will see how things have evolved at 5 nm.

The course has been organized by An Steegen and Dan Mocuta of Imec. They introduce it bright and early, at 8.30 a.m.

The first session is “Nano Patterning Challenges at the 5nm Node”, given byAkihisa Sekiguchi of Tokyo Electron. Next up is Nadine Collaert from imec, discussing “Novel Channel Materials for High-Performance and Low-Power CMOS”, followed by Aaron Thean, of the National University of Singapore (and formerly imec),who is presenting on “Options beyond FinFETs at 5nm node”.

Contacts are the next topic, “Low Resistance Contacts to Enable 5nm Node Technology: Patterning, Etch, Clean, Metallization and Device Performance”, by Reza Arghavani of Lam Research.

The back-end stack gets more critical as dimensions shrink, so we have a review of “Parasitic R and C Mitigation Options for BEOL and MOL in N5 Technology”, by Theodorus Standaert from IBM.

The last session covers off “Metrology Challenges for 5nm Technology”, by Applied Materials’ Ofer Adan – given that we are now counting atoms, challenging is a good way to describe it.

John Chen of Nvidia set up the Design/Technology short course, which takes a fairly high-level look at the technologies involved in processing Big Data, discussing the different processors themselves, the effects of memory, managing the power and connectivity, and where advanced packaging fits in.

So we have:

  • The Rise of Massively Parallel Processing: Why the Demands of Big Data and Power Efficiency are Changing the Computing Landscape” – Liam Madden, Xilinx
  • Breaking the Memory Bottleneck in Computing Applications with Emerging Memory Technologies: a Design and Technology Perspective” – Gabriel Molas, Leti
  • Power Management with Integrated Power Devices…and how GaN Changes the Story” –Alberto Doronzo, Texas Instruments
  • Interconnect Challenges for Future Computing” – William J. Dally, NVIDIA/ Stanford U
  • Advanced Packaging Technologies for System Integration” – Douglas Yu, TSMC

I would call both courses a full day, seeing as we finish at ~5.30 p.m., but it’s worth sticking around to the end.

If you have the stamina, at 6.00 CEA-Leti is hosting a Devices Workshop at the Nikko Hotel, across the street from the Hilton.


Monday morning we have the plenary session, with three pertinent talks on the challenges and potential of contemporary electronics:

  • “Technology Scaling Challenges and Opportunities of Memory Devices” – Seok-Hee Lee, Hynix
  • “Brain-Inspired Computing” Dharmendra S. Modha – IBM
  • “Symbiotic Low-Power, Smart and Secure Technologies in the age of Hyperconnectivity” – Marie-Noëlle Semeria, Leti

Three quality presentations in three hours, but beware of numb bum if you take in all of them – get up and have a stretch in between, and take a walk before lunch!

After lunch, in keeping with IEDM’s tradition of intellectual overload, we have seven parallel sessions!

Session 2: Circuit and Device Interaction — Advanced Platform Technologies – including 7 nm finFETs!

Session 2 starts a track on Circuit and Device Interaction, in this case with papers on Advanced Platform Technologies – for me a highlight session, since the session ends with duelling 7-nm late-news papers from TSMC (2.6) and the Samsung/GLOBALFOUNDRIES (GF)/IBM consortium (2.7).

In addition, we have a GF/Leti discussion of the GF 22FDX SOI technology (2.2) announced last year; paper 2.3 is a research paper on 3D monolithic integration of ultra-thin body MOSFETs into a VCO and power management circuit, with a 4-layer Vertical ReRAM, by Taiwan’s National Nano Device Laboratories and National Chiao Tung University.

GF co-authors the next two papers, detailing a high-resistance SOI technology for RF front-end modules (2.4), integrating a power MOSFET with a RF switch by using selective silicon thinning; and (2.5) a look at monolithic 3D IC design partitioning to mitigate the performance limits set by the limited thermal budget of the upper transistor level in the 3D IC stack.

In 2.6, TSMC announces the “world’s first 7nm CMOS platform technology for mobile system-on-a-chip (SoC) applications, featuring FinFET transistors”. They claim the world’s smallest-ever SRAM cell at 0.27 µm2, and 3x the gate density of the 16-nm process, together with a 35 – 40% speed gain or over 65% power reduction.

In addition, the process uses 93nm immersion lithography, raised source/drain epi, a novel contact technique, and a 12-layer copper/low-k interconnect stack.

By contrast, the finFETs in 2.7 from the GF/IBM/Samsung group consortium (presumably at Albany, NY) were manufactured using EUV, with contacted polysilicon pitch (CPP) of 44/48nm, and metallization pitch of 36nm. It also features dual-strained channels formed on a thick strain-relaxed buffer (SRB) virtual substrate to give tensile-strained NMOS and compressively strained SiGE PMOS for the enhancement of drive current by 11% and 20%,  respectively, when compared with a common planar (my italics) HKMG process. Epitaxy is used in the contact trenches to minimize resistance.

Schematic (center) of dual-stressed channel materials on the SRB with a super-steep retrograde well (SSRW), along with TEM images of (a) the tensile-strained silicon fin and (b) the compressively-strained SiGe fin on a common SRB (2.7). Schematic (center) of dual-stressed channel materials on the SRB with a super-steep retrograde well (SSRW), along with TEM images of (a) the tensile-strained silicon fin and (b) the compressively-strained SiGe fin on a common SRB (2.7).

Session 3: Compound Semiconductor and High Speed Devices — Compound Semiconductors for High Speed RF and Low Power Logic Applications

The session starts with a paper (3.1) from Germany’s IHP Institute, on their (claimed) fastest silicon-based heterojunction bipolar transistor (HBT), with an fT/fmax of 505 GHz/720 GHz, respectively, at 1.6 V; they attribute this to optimized vertical profiles of the emitter-base-collector regions, the use of “flash” annealing and low-temperature backend processing to lower base and emitter resistance, and lateral device scaling.

TEM image of a cross-section of an optimized Si HBT device (3.1). TEM image of a cross-section of an optimized Si HBT device (3.1).

Lund University is up next (3.2), discussing InGaAs tri-gate MOSFETs with record on-current of 650 µA/µm at 0.5 V. Paper 3.3 is an invited talk on “High Frequency GaN HEMTs for RF MMIC Applications”, from HRL Labs.

In paper 3.4, MIT studies a new form of instability due to F- migration and the passivation/depassivation of Si dopants in a n-InAlAs cap layer in InGaAs MOSFETs; it turns out that removing the cap layer gets rid of the instability!

MIT also presents paper 3.7, on using a physical compact model to improve the RF circuit linearity performance of GaN HEMTs, in both device and circuit design techniques. GaN HEMTs are again discussed in 3.5, this time W-band N-polar devices; UCal Santa Barbera claims a record high efficiency of 27.8% at 94 GHz.

And to fill in the gap at 3.40 pm (3.6), IBM gives an invited talk on “Monolithic Integration of Multiple III-V Semiconductors on Si for MOSFETs and TFETs”, using template-assisted selective epitaxy (TASE) for a number of III-V compounds.

Session 4: Memory Technology — RRAM, PRAM and Applications

We start with an invited talk “Towards Ultimate Scaling Limits of Phase-Change Memory” (4.1) by Feng Xiong of Stanford U., reviewing advances in phase-change memory (PCM), which is now down to sub-10 nm scale, with switching energies approaching femtojoules per bit.

Paper 4.2 discusses confined ALD-based PCM with a metallic liner, which is reported to have record endurance of 2e12 cycles; and 4.3 looks at SiOx-based RRAM (Resistive Random-Access Memory) in crossbar memory arrays, and also as select devices in the arrays.

Oxygen implantation into Ta2O5 and HfO2 is used to form RRAM devices in the ON state (4.4), which subsequently switch similarly to regularly made reference devices. The correlation between endurance, window margin and retention of RRAM types (oxide RAM and conductive bridge RAM) is studied in 4.5, and the effect of programming parameters on oxide RAM retention is the topic in 4.6.

The intrinsic variability factors of RRAM are quantified in 4.7, to identify the fundamental variability limits of the technology, and the last paper (4.8) details a random number generator fabricated in Panasonic’s 40-nm embedded ReRAM process.

Session 5: Nano Device Technology — 1D and 2D Devices

This session (not surprisingly) is a set of research papers, starting with a pair of carbon nanotube (CNT) transistor studies; 5.1 details CNT-FETs with nickel contacts alloyed into the ends of the CNTs to reduce contact resistance and give scalability to the contact process.

Schematic of a CNT-based CMOS inverter with entirely Ni end-bonded contacts (5.1) Schematic of a CNT-based CMOS inverter with entirely Ni end-bonded contacts (5.1)

We look at vertically suspended CNT-FETs in 5.2, which allows a fully gate-all-around (GAA) structure with multiple channels, optimising gate controllability and enhancing charge transport.

In 5.3 we move to graphene FETs, again examining ways of reducing contact resistance, this time using “atomic orbital overlap engineering”.

Paper 5.4 is an invited talk from Mathieu Luisier of ETH Zurich on simulations of 2-D devices, reviewing mobility, I-V characteristics, and contact resistance, with extra detail on contacts to molybdenum disulphide (MoS2).

Black phosphorus is another potential 2-D transistor material, and PMOSFETs with a boron nitride/alumina gate dielectric are discussed in 5.5.

The last three papers focus on MoS2, examining 10-nm top-gated transistors in 5.6, and we go beyond transistor studies in 5.7 to develop guidelines for co-optimisation of material, devices, and circuits, to get the yield up and move towards manufacturability. The final paper (5.8) gets back into the detail of the MoS2 MOS interface trap density created by S vacancies in the MoS2.

Session 6: Sensors, MEMS, and BioMEMS — Focus Session: Wearables for the Internet-of-Things (IoT)

As a focus session, this features a series of seven invited presentations;

  • High Performance, Flexible CMOS Circuits and Sensors Toward Wearable Healthcare Applications,” by K. Takei, Osaka Prefecture University (6.1)
  • Circuits and Systems for Energy-Efficient Smart Wearables,” by A. Sharma, Texas Instruments (6.2)
  • Flexible Metal-Oxide Thin-Film Transistor Circuits for RFID and Health Patches,” by P. Heremans et al, Imec/University of Leuven/Holst Centre (Belgium)/National Centre for Flexible Electronics (India) (6.3)
  • Challenges and Opportunities in Flexible Electronics,” by R. D. Bringans and J. Veres, Xerox PARC (6.4)
  • Advanced Integrated Sensor and Layer Transfer Technologies for Wearable Bioelectronics,” by D. Shahrjerdi et al, New York University (6.5)
  • Wearable Sweat Biosensors,” by A. Javey et al, University of California, Berkeley (6.6)
  • Flexible Metamaterials, Comprising Multiferroic Films,” by Y. P. Lee et al, Hanyang University (6.7)
Schematics and example of wearable sweat sensor from paper 6.6 Schematics and example of wearable sweat sensor from paper 6.6

Session 7: Modeling and Simulation — Advanced Numerical and Compact Models

The first paper details an electro-thermal compact model for self-heating ICs, including the BEOL, that can predict front-and back-end reliability, and takes account of interconnect layout and geometry (7.1).

In 7.2 we hear about a model that considers the percolation path of the channel current in a transistor to help understand the statistical variability and reliability in nanoscale devices, and compares the different features of 3-D finFETs with planar transistors.

HfOx-based analog synaptic devices are considered in 7.3; the SET, RESET, and retention loss processes are simulated and given experimental verification, capturing the key material parameters and forming optimization guidelines.

P-channel GaN MOSHFETs are the topic in 7.4, examining the electric field distribution to determine why a higher threshold voltage needs reduced channel and oxide layer thicknesses. This led to the introduction of an AlGaN cap layer to modulate the field and increase the on-current.

We move to GAA-MOSFETs in the next presentation, modelling stacked-planar and vertical transistors of circular, square, and rectangular cross-sections (7.5). Then we change technologies again and look at the resistive switching behaviours of CBRAM devices (7.6).

CBRAMs use the property that if amorphous insulating materials contain a relatively large amount of metal, the metal ions they contain can form a conductive path when voltage is applied; this can be reversible, enabling the storage of data as the conductor appears and disappears. The paper studies three modes of filament formation.

3-D cross-point memory cells formed using germanium-selenium telluride (GST) are discussed in the last paper of the session (7.7), extending the model to simulate memory array circuits.

Session 8: Optoelectronics, Displays, and Imagers — Imaging and Photon Counting Sensors

The first paper in the session presents a backside-illuminated (BSI) single photon avalanche diode (SPAD) image sensor (8.1), a claimed first in the field. Most of the CMOS image sensors (CIS) in smartphone cameras these days are BSI, usually with stacked dies and through-silicon vias (TSVs), although the very latest use face-to-face wafer bonding of the metal interconnects.

It looks as though this device also uses stacked dies, since the SPADs are fabbed in a 65-nm process, and the processor is 40-nm.

SPADs are getting attention lately since they are also appearing in mobile phones in time-of-flight auto-focusing devices for the cameras, and in the latest iPhone they are doing double duty as a proximity sensor and autofocus for the selfie camera; see my last blog for more details.

STMicroelectronics time-of-flight sensor from iPhone 7 STMicroelectronics time-of-flight sensor from iPhone 7

Paper 8.2 is also focused on SPADs, in this case a 256 x 256 image sensor with 16 µm pixel pitch and a 61% fill factor. Then we have an invited talk from M.Mori of Panasonic (8.3), discussing “An APD-CMOS Image Sensor Toward High Sensitivity and Wide Dynamic Range”; followed by Sony (8.4) showing off their latest die stacking using copper/copper hybrid bonding connecting the image sensor to the image processor (also known as direct bond interconnect (DBI).

We at Chipworks actually found this technology in the Samsung Galaxy S7 Edge back in March, so it is definitely in volume production.

SEM cross-section of Sony image sensor from Samsung Galaxy S7 Edge, showing copper/copper direct bonding SEM cross-section of Sony image sensor from Samsung Galaxy S7 Edge, showing copper/copper direct bonding

Next up is a global shutter CIS (8.5) which somehow has 480 analog memories/pixel integrated using vertical analog memory technology, which enables 1 Mfps.

In 8.6, Canon exhibits one of their huge 35-mm full-frame sensors, this time a low-noise global shutter device with a 6.4 µm pixel size. Apparently, most CMOS imagers use a rolling shutter, which reads the pixels at different times at different parts of the imager, leading to image artifacts, especially for moving targets (see image below of vibrating ukulele strings).

8.6 Canon

The last paper is another from Sony (8.7), this time detailing a “Four-Directional Pixel-Wise Polarization CMOS Image Sensor Using Air-Gap Wire Grid on 2.5-µm Back-Illuminated Pixels”. If I understand the abstract correctly, this sensor has a wire grid with 150-nm pitch over the pixels which acts as a polarizer, presumably in the four directions of the grid sides.

That is the end of the Monday afternoon sessions, and the reception will start at 6.30 pm in the Grand Ballroom; but if you have links to Stanford U, there is a gathering at 5 before then.


Session 9: Process and Manufacturing Technology — 3D Integration and BEOL

The session starts (9.1) with a discussion of 3D-stackable finFETs compatible with back-end processing, using single-grained silicon fins and laser spike anneal to keep the thermal budget down.

We have seen the use of liquid surface tension for die positioning and self-assembly in years past; in 9.2 we have it applied to 2.5/3D integration of multiple types of die, even those with uneven surfaces and bottom topography.

Next we have an invited presentation (9.3) by Ruth Brain of Intel, on “Interconnect Scaling: Challenges and Opportunities”, focusing on the transistor/interconnect optimization that is necessary now that interconnect delay is dominating circuit performance.

Paper 9.4 looks at a high-k MIM decoupling capacitor aimed at the 7-nm node; and 9.5 discusses graphene-on-copper for improved interconnectivity and enhanced electro-migration lifetime. The last paper (9.6) explores the intriguing concept of vertical-channel devices gated by TSVs.

Session 10: Power Devices — Power Semiconductor Device Technologies

We get into the world of GaN devices in the first four papers – 10.1 details a normally-off V-trench GaN transistor formed on a GaN substrate, with a record 1.7 kV breakdown voltage and on-state resistance of 1.0 mΩcm2; 10.2 describes a vertical GaN Schottky rectifier incorporating trench MIS structures and field rings; 10.3 is about GaN gate injection transistors with high-speed switching, again built on a GaN substrate; and 10.4 presents on high-performance enhancement-mode GaN MIS-FETs with a recessed-gate structure and a SiNx gate dielectric.

Schematic cross-section of lateral p-type GaN transistor with slanted channel (10.1) Schematic cross-section of lateral p-type GaN transistor with slanted channel (10.1)

Next we have an invited talk (10.5) on “Superior Performance of SiC Power Devices and Its Limitation by Self-heating” by T. Terashima of Mitsubishi Electric, followed by a paper looking at the 3D scaling of IGBTs (10.6), giving lower on-resistance.

The last two papers go back to SiC devices, with a description of a vertical p-type SiC MOSFET with enhanced breakdown voltage (10.7), and 10.8 is a study of hysteresis in subthreshold drain current in SiC n-MOSFETs, caused by hole capture in border traps.

Session 11: Memory Technology — Charge Based Memories and Scaling

In this second session of the Memory track, we move to other forms of memory and embedded memory. Renesas and Hitachi have worked out a way to build split-gate MONOS flash on finFETs (11.1); then Samsung gives an invited review “A New Ruler on the Storage Market: 3D-NAND Flash for High-density Memory and its Technology Evolutions and Challenges on the Future” (11.2). We have seen 3D-NAND flash go from 24 – 32 – 48 – 64 layers in the last four years, and all four of the flash manufacturers are now in volume production; this review should cover off that evolution, as well as discuss some of the challenges as the process complexity increases.

Macronix has stated that they plan to join the 3D-NAND business, and in 11.3 they study instability caused by the grain boundaries in the polysilicon channel of vertical flash structures. Another invited talk is next, this time by Bosch (11.4), discussing the qualification of non-volatile memories (NVM) for automotive applications, and the resulting requirements for the NVM supplier, and the implications for design and technology of NVMs.

Paper 11.5 is a study of a ferroelectric transistor (FeFET) based eNVM retrofitted into GLOBALFOUNDRIES’ 28SLP HKMG process using an extra layer of SiHFO inserted into the transistor gate stack.

TEM cross-sections of GF 28SLP transistors (left), and FeFET device (right), showing the extra SiHfO layer (11.5) TEM cross-sections of GF 28SLP transistors (left), and FeFET device (right), showing the extra SiHfO layer (11.5)

The next paper (11.6) has an intriguing abstract – how to convert ZrO2-based DRAMs (i.e. most DRAMs) into NVMs – I look forward to the details! The last talk details a tantalum-oxide based selector device that can be formed in a crossbar array, and fitted into the back-end process sequence (11.7).

Session 12: Nano Device Technology — Negative Capacitance and New Material MOSFETs

In this session we have a series of papers on ferroelectric negative capacitance (NC) devices, mostly using HfZrOx. The first describes a NC-finFET with a 1.5-nm thick HfZrOx layer (12.1), then we have HfZrOx germanium (Ge) and Ge-tin p-MOSFETs (12.2), followed by a study on a HfO2 NC-FET, looking at its polarization-limited operating speed (12.3).

12.4 simulates sub-10-nm NC-finFETs, showing excellent short-channel performance; 12.5 examines InGaAs MOSFETs with a La2O3 dielectric, revealing that La2O3 can have ferroelectric properties, and can be used to form NC-FETs; and 12.6 analyzes the hole and electron effective masses in the inversion layers of Ge (100), (110) and (111) p- and n-MOSFETs.

Session 13: Optoelectronics, Displays, and Imagers — Focus Session: Quantum Computing

This Focus Session features invited papers describing several technologies to fabricate quantum bits (qubits), including transmon qubits, spin qubits in silicon, and FDSOI qubit technology with silicon nanowire field-effect transistors. There are also discussions of quantum technologies based on luminescent crystalline defects in diamond, and the prospects of scalability, considering the potential fabrication of large-scale systems with millions of qubits.

  • Quantum Computing Within the Framework of Advanced Semiconductor Manufacturing,” by J. S. Clarke et al, Intel/TU Delft
  • Spin-Based Quantum Computing in Silicon CMOS-Compatible Platforms,” by A.S. Dzurak, University of New South Wales
  • Coupled Quantum Dots on SOI as Highly Integrated Si Qubits,” S.Oda, Tokyo Institute of Technology
  • SOI Technology for Quantum Information Processing,” by S. De Franceschi et al, CEA/University Grenoble Alpes
  • Cryo-CMOS for Quantum Computing,” by E. Charbon et al, Delft University of Technology/EPFL/Institut Superieur d’Electronique de Paris/Tsinghua University/Univ. California, Berkeley
  • Diamond–A Quantum Engineer’s Best Friend,” by Marko Lončar, Harvard University
  • Large-Scale Quantum Technology Based on Luminescent Centers in Crystals,” by M. Trupke et al, TU Wien/University of Vienna/Nippon Telegraph and Telephone/National Institute of Informatics (Japan)

Session 14: Modeling and Simulation — 2D Materials and Organic Electronics

Back in session 5 we had some MoS2 papers, and 14.1 is a study on two MoS2 transistor types, a lateral heterostructure FET and a “planar barristor”; then we have an invited review (14.2) of “Physics of Electronic Transport in Two-dimensional Materials for Future FETs” by Massimo Fischetti from U. Texas (Dallas).

Next up is an atomic-scale simulation of silicon contact with MoS2 (14.3), and 14.4 is an examination of graphene/semiconductor contacts for a range of materials. Paper 14.5 predicts the performance of InAs, InN, InP and InSb double-gate, single-layer n- and p-type transistors; and 14.6 is an invited review of the “Current Status and Challenges of the Modeling of Organic Photodiodes and Solar Cells”, by R.R. Clerc of the Institut d’Optique Graduate School.

The session finishes with a discussion of ultra-thin nanowire gated 2D-FETs, focusing on dielectric growth and channel formation (14.7). In one example, a thin (6nm) conformal Al2O3 dielectric was formed around Co2Si nanowires on a carrier wafer, and were then gently pressed against a MoS2 substrate to transfer them – this avoids having to deposit the dielectric on the MoS2. The curvature of the nanowire ensures that only a short section of it is in contact with the 2D layer, creating a short channel length.

Schematic illustration of a nanowire-gated 2D FET (left), and TEM cross-section of a fabricated device (14.7) Schematic illustration of a nanowire-gated 2D FET (left), and TEM cross-section of a fabricated device (14.7)

Session 15: Characterization, Reliability and Yield – FINFET and Nanowire Device Reliability

Samsung is first up this session, characterizing the reliability of their 10-nm process technology (15.1). They presented the basics of it at VLSI at VLSI this year [1]; they described it as:

“Fin and dummy Si gate were defined by sidewall image transfer using a mandrel and sidewall space. 3rd generation Fin features more vertical and thinner shape than previous technologies, which allows for stronger control of the short channel effect. Highly doped S/D with 3rd generation epitaxial process is combined with advanced contact process to boost performance. Copper interconnects were fabricated using conventional immersion bi-directional patterning and CVD-liner process.”

And these are some of the design rules:

Samsung VLSI

In addition to reliability studies, the paper will describe describe process optimizations that overcome problems such as self-heating effects caused by the taller and narrower fin shape.

TSMC contributes an invited talk (15.2) on a similar topic “Consideration of BTI Variability and Product Level Reliability to Expedite Advanced FinFET Process Development”, and we get into serious detail in 15.3 with a statistical model of NBTI degradation of p-finFETs.

IBM reports on hot-carrier reliability in gate-last SiGe-channel p-finFETs in 15.4, and we have a post-mortem study of dielectric breakdown in finFETs in 15.5, including TEM/EELS/EDX analysis; and, according to the abstract “The assumption that the kinetics of failure would remain the same for both planar and FinFET devices is proved to be untrue.”

15.6 is an imec review of self-heating in finFETS and gate-all-around nanowires (GAA-NWs), and 15.7 continues the theme, exploring thermally-aware transistor design to reduce self-heating of floating-body devices such as FD-SOI, SOI-finFETS, and GAA-NWs.

We finish with an invited presentation (15.8) on nano-thermometry, using an AFM-based tool to look at localized hot spots in nano devices.

Session 16: Circuit and Device Interaction – Resistive Device Designs for von-Neumann Computing and Beyond

One of the trends in recent years has been the application of resistive RAM for neuromorphic computing; it appears that RRAM memories have the advantage in that they can hold a range of resistive states that can correspond to the “shades of grey” in human thinking.

The second session in this track continues that theme. The first paper examines the use of vertical RRAM for language recognition (16.1). Here, the RRAM is vertically oriented, whose physical structure corresponds to the team’s hyper-dimensional computing algorithm. This 3D-VRRAM allowed the computing framework to recognize words in 21 different languages from sample texts.

The next paper (16.2) details a binary neural network using 16-Mb RRAM devices for image recognition; 16.3 discusses a novel non-volatile flip-flop with a single RRAM NVM included; 16.4 describes a 50 x 20 crossbar switch block with two a-Si/SiN/a-Si varistors for non-volatile FPGAs; and a 4-transistor NV-SRAM with two RRAMs (4T2R, instead of the usual 6T SRAM cell) is fabricated in TSMC’s 40-nm process in 16.5.

16.6 is a higher-level study of a fully connected neural network using arrays of OxRAM devices, and applying short- and long-term plasticity rules, suitable for (e.g.) visual pattern extraction from highly noisy data.

Image reconstruction is used as a diagnostic tool to evaluate the device variability in memristor crossbar arrays in 16.7, and 16.8 demonstrates unsupervised learning by spike-time dependent plasticity (STDP) and spike-rate dependent plasticity (SRDP) in neural networks using CMOS-based RRAM synapses.

Finally, it’s time for lunch! This year’s speaker at the conference lunch is Prof. Roberto Cingolani from the Istituto Italiano di Tecnologia in Genoa, Italy, presenting on “Translating evolution into technology: from biochemical robots to autonomous anthropomorphic machines”. We are used to the concept of living creatures evolving over time – here we will have a comparison between living and artificial systems, and the attempts to reproduce the characteristics of living things using technology.

Tickets are available online when you register – if you haven’t, there are usually some at the conference front desk. The afternoon sessions start again at 2.15.

Part 2 of the preview will be up in a few days, before the conference!

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