Edward Stone Award for Outstanding Publication Seminars Computational Nanoelectronics Towards: Design, Analysis, Synthesis, and Fundamental Limits

I 180/101

Dr. Gerhard Klimeck Q 0 10 20 30 40 50 60 Position (nm) Technical group supervisor of the Applied Cluster Computing Technologies Group and a Principal member at the Jet Propulsion Laboratory

Nanotechnology and Nanoelectronics in particular have received a lot of public attention since President Clinton announced a National Nanotechnology Initiative at Caltech. Nanotechnology bears the promise to provide new approaches to electronics, materials, medicine, biology and a variety of other technologies. In the world of semiconductor electronics, nanotechnology has already arrived in practical devices. Wave-like properties of electrons modify the functional device behavior once spatial variations in structures reach length scales of a few tens of nanometers. While standard technologies require extensive simulation tools for design, analysis and characterization, no such tools exist for nanoelectronic devices. The modeling and simulation of such devices now deviates strongly from classical approaches: it must be fundamentally quantum mechanical. JPL has been involved in nanoelectronic modeling since 1998 following efforts started at Texas Instrument in 1993. This seminar will review the development of a comprehensive nanoelectronic modeling tool (NEMO 1-D and NEMO 3-D) and its application to high-speed electronics (resonant tunneling diodes) and IR detectors and lasers (quantum dots and 1-D heterostructures). 0cn I- .-6 m C 8 U 0 a, v) a, cCI .- .L a a a L .-mi a> 1 120 0 -E m C s 3 S nf m 0 3 > E YI m 0 m nS 0 C 3 I m- LL O 9 % . US 0 m m .s m O .-S E 0- E E rW i= I >s s II € 0 W F a> US LL3 JPL Presentation Outline Introduction / Motivation Nan0 device needs, modeling needs. Critical look at the SIA Roadmap. ID heterostructure modeling Ba nds t ruct ure eng inee ri ng basics . Resonant tunneling diodes Hole transport (Ed Stone Award). "EM0 I-D - First quantum device simulator. 3D heterostructure modeling NEMO 3-D Modeling agenda. .What is a quantum dot? .Quantum dot examples. *Alloy disorder in quantum dots. Analysis and Synthesis using Genetic Algorithms (GAS) GA basics Design Synthesis Conclusion / Outlook

Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Motivation

Our enthusiasm for Nano- technology stems from its potential value in addressing Deep Space technology needs: 4 Autonomous navigation and maneuvering, 4 Miniature in-situ sensors, 4 Radiation and temperature tolerant electronics.

Nano-technology will provide essential computing and sensing capabilities. c Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Near Term Example Application Quantum Dots for Optoelectronic Devices InGaAsSb/GaSb InGaAsP/InP Quantum Cascade Diode Sources

CH, NO2 HF HCL HN(’3 03 CIO Atmospheric Gases I 31 I I

NH3 C2H2 H2p I JPL Need for Nanoelectronic Simulation Problems: Design space is huge Simulation Choice of materials, shapes, orientations, dopings, heat anneals Characterizations are incomplete and invasive / destructive

Simulation Impact: *Aide Design Fast, cost effective. -> Device performance successful for 1 -D quantum devices

Aide Characterization Non-invasive More accurate Characterization Fabrication =>Structure and doping analysis Q 03 t

LI rI n.. I a, 03 cn cn>a S a,r S 0 -cIL 0 0 .--cI S 0 -a, mN .-CI .- \a, L 0 3 .Im - L 2 .- 0 Sm n -cI .- rcm E m CIa, .-0a, a, > cnt a, .- U0 n0 .I 1 0 0 0 JPL Technology Push Toward Fundamental Limitations

CommerciaI market pushes I computing (FLOPS/weight/power): Enabled by odevice miniaturization .chip size increase 0 Limited by: Costs of fabrication *Discrete atoms/electrons Add iti o na I NASA Requ i reme n ts : 0 High radiation tolerance 1990 0 Extreme temperature operation- -"d80 2000 2010 : 0: - hot/coId L 2-D Lithograp feature 1 I-D feature t5-100 I A

L / Gerhard Klimeck Applied Cluster Computing Technologies Group I Technology Push I Toward Fundamental Limitations - ~ Commercial market pushes Number of Electrons I computing (FLOPS/weight/power): 1 o4 e2 kT >> - Enabled by 2c .device min iat u rization E1 .c,2 o3 .chip size increase -8 W Limited by: Y-10 u2 Costs of fabrication 3 ODiscrete atomslelectrons 51 0' e2 : z kT << - Add it iona I NASA Requ i remen ts 2c High radiation tolerance 1oo Extreme temperature operation- 1980 1990 2000 2010 2020 hotlcold 2-D Lithography feature c 1 l=D 3 feature L0 t5-700 A (3 L Gerhard Klimeck Applied Cluster Computing Technologies Group JPL I Technology Push Toward Fundamental Limitations

~ Commercial market pushes

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hotfcold 2-D Lithography - feature JPL Presentation Outline Introduction / Motivation *Nan0 device needs, modeling needs. *Critical look at the SIA Roadmap. ID heterostructure modeling Bandst ruct ure engineering basics . Resonant tunneling diodes Hole transport (Ed Stone Award). *NEMO 1-D - First quantum device simulator. 3D heterostructure modeling NEMO 3=D Modeling agenda. *What is a quantum dot? *Quantum dot examples. *Alloy disorder in quantum dots. Analysis and Synthesis using Genetic Algorithms (GAS) GA basics Design Synthesis Conclusion I Outlook

Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Bandstructure Basics Electron Conduction in Solids

Physics

t Transport conductivity, mobility Devices Bands are channels in which electrons move “freely”. Layers of different atoms are deposited with monolayer control. We can engineer the electron bands. L Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Bandstructure Engineering Basics I Resonance Energies / Eigenvalues ------I r -- -r - -I I

Barriers and Wells Wave Functions / Eigenstates

Layers with different band alignments 0 0 +

& Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Bandstructure Engineering Basics Resonance Energies / Eigenvalues

L Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Bandstructure Engineering Applications Transitions / Transport

Photon Photon Absorption Emission Tunneling

c Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Bandstructure Engineering Applications Transitions / Transport - -1- I-- -n- - -- r

Photon 1__1 Absorption

Detectors I

Quantum Well Infrared Detector \ Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Bandstructure Engineering Applications Transi :ions / Transport

-1--- -1--- I Photon Emission 1 Lasers

-1,or:::::::::::i 0 10 20 30 40 50 60 Position (nm) Quantum Cascade L Laser Gerhard Klimeck Ap pI ied C Ius te r Comput i ng Techno Iog ies G roup JPL Bandstructure Engineering Applications ---rTransitions / Trans 30t-t Tunneling

Logic I Memory n

4Resonant Tunneling Diode

Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Transitions / Transport Controlled by Desi

Photon Absorption Emission Tunneling 1 Detectors Lasers Logic I Memory i 2.0

57 10 J 5r

S UJF 00

9 40 tiis 88 2i5 qm 0 10 20 30 40 50 60 P @W Position (rim) Resonant Quantum Well Quantum Cascade Tunneling Infrared Detector Laser Diode L Gerhard Klimeck Applied Cluster Computing Technologies Group Sb1780 Sb 1781 R=8.8R Nominal Size 07/20/07 ml I I I I I 4 EXP o 1 108/17/0L8 - 1

0 0.2 0.4 0.6 0.8 1 1.2 Applied Bias (V) 12 different I-V curves: 2 wafers, 3 mesa sizes, 2 bias directions Voltage 50nm le18 InGaAs 7 ml nid InGaAs 7 ml nid AlAs m 20 ml nid InGaAs Conduction band diagrams 7 mi nid AlAs for different voltages 7 ml nid InGaAs and the resulting current flow. 50 nm le18 InGaAs JPL Testmatrix-Based Verification (room temperature) Strained InGaAs/AIAs 4 Stack RTD with Asymmetric Barrier Variation

V744 #I, Nom.: 07/17/07 ml, Sim.: 09/18/09 ml V744 #2, Nom.: 07/17/08 ml, Sim.: 09/18/10 ml 18000 I I Forw. Bias - 16000 CJ 14000 Rev. Bias - Simulation 12000 - x .G2 10000 CI ----- *g 8000 3 8000 a 8 hnnn---- c ffl i i -8 6000 c 4000 4000 s9 s9 " 2000 5 2000 HG HG n" 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 - Applied Bias (V) Applied Bias (V) 20/50/ 2 744 #3, Nom.: 07/17/09 ml, Sim.: 09/18/11 ml 744 #4, Nom.: 07/17/10 ml, Sim.: 09/18/12 ml 9000 I I I I I /1 9000 I I I I I I h 8000 Fonv. Bias -- Four increasingly CJ 8000 Simulation -+- 7000 Simulation asymmetric Rev. Bias Rev. Bias - 6000 Simulation .....)...... devices : 2A x et: 5000 s 5000 20/50/20 Angstrom 2 92 & 4000 & 4000 20/50/23 Angstrom 3000 'S0 3000 20/50/25 Angstrom 2 2000 5 2000 20/50/27 Angstrom u 1000 u 1000 0 0 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 Applied Bias (V) Applied Bias (V)

Presented at IEEE DRC 1997, work performed at Texas Instrument. Dallas Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Presentation Outline Introduction / Motivation .Nan0 device needs, modeling needs. .Critical look at the SIA Roadmap. 1D heterostructure modeling Bandstructure engineering basics. Resonant tunneling diodes Hole transport (Ed Stone Award). NEMO 1-D - First quantum device simulator. 3D heterostructure modeling NEMO 3-D Modeling agenda. .What is a quantum dot? .Quantum dot examples. .Alloy disorder in quantum dots. .Analysis and Synthesis using Genetic Algorithms (GAS) GA basics Design Synthesis Conclusion / Outlook

Gerhard Klimeck Applied Cluster Computing Technologies Group 4c

20 Electron Density of States and Transmission Coefficients 30I

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Hole Density of States and ..-. 2=- Transmission Coefficients

Gerhard Klimeck Applied Cluster Computing Technologies Grou 3 JPL Hole Transport in a GaAs/AIAs RTD - HH1

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Light hole states strongly coupled to continuum -> wide resc Heavy hole states weaklv cowled to continuum->narrow Gerhard Klimeck Applied Cluster Computing Technologies Group Electron vs. Hole Subbands

W g 0.1 0 22 0.0 W e> 0.0 ;-0.1 b4 k0 fi -0.2 0 I I I 8-0.3 I- ( -I IO-’ 10’ 0.0 0.04 0.08 Transmission Momentum k 0 0 I II 1 I I 0 0 d

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0 /s n 0 cd II v I I I I 24 m m M 0 0 w m m 0 0 0 0 0 0I 0I 0 1 1a JPL I NEMO 1-D: A User-friendly Quantum Device Design- Tool NEMO was developed under a government contract to Texas Instruments and Raytheon from 1993-97 EceeringTransport/ >50,000 person hours of R&D 250,000 lines of code in C, FORTRAN and F90

Based on Non-Equilibrium Green function formalism (Datta, b Lake, Klimeck). NEMO in THE state-of-the-art heterostructure design tool. Used at Intel, Motorola, HP, Texas Instruments, and >IO Un iversit ies. Quantum Mechanics / Physics

-

V744Y1 Nom 07/17/07 ml 09/18/09 ml V744d2, Nom 07/17/08 ml. 09/18/10ml I8wO Sm Sm i; 1m $14ooo 3 12000 * loo00 4 8000 Em X em .I 2000 c,L 0 0 02 04 06 08 1 0 02 04 06 08 1 Applied Bias (V) Applied Bias (V) c,; 201501 2 v) 744#3,Nom.:07/17/09ml, Sim.:09/18/11 ml 744 #4, Nom.: 07/17/10 ml, Sim.: 09/18/12 ml m, I 8w0 F 8 7000 3m p 5ooo eta 5 3000 8 2000 loo0 n 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 I Applied Bias (V) Applied Bias (V)

Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Presentation Outline Introduction / Motivation *Nan0 device needs, modeling needs. Critical look at the SIA Roadmap. ID heterostructure modeling Bandstructure engineering basics. Resonant tunneling diodes *Hole transport (Ed Stone Award). "EM0 1-D - First quantum device simulator. 3D heterostructure modeling NEMO 3-D Modeling agenda. *What is a quantum dot? *Quantum dot examples. *Alloy disorder in quantum dots. *Analysis and Synthesis using Genetic Algorithms (GAS) GA basics Design Synthesis Conclusion / Outlook

Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Nano-scale Device Analysis~ / Synthesis- Development of a Bottom-Up Nanoelectronic Modeling Tool

Atomic Orbitals tructures (-20nm)

~ ___ Assertions / Problems: Nanoscale structures are built today! The design space is huge: choice of materials, compositions, doping, size, shape Radiation on today’s sub-micron devices modifies the electronics on a nanoscale. Approach: Deliver a 3-D atomistic simulation tool Enable analysis of arbitrary crystal structures, particles, atom compositions and bond/structure at arbitrary temperatures and ambient electric and magnetic fields. Collaborators: U. of Alabama, Ames, Purdue, Ohio State, NlST Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Nano-scale Device Analysis / Synthesis Development of a Bottom-Up Nanoelectronic Modeling Tool

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Atomic Orbitals tructures (-20nm) Assertions / Problems: NASA Relevance: Nanoscale structures are built today! Enable new devices needed for NASA The design space is huge: choice of missions beyond existing industry roadmap: materials, compositions, doping, size, shape Water detection -> 2-5pm Lasers and Radiation on today’s sub-micron devices detectors. modifies the electronics on a nanoscale. Avionics -> High density, low power Approach : compu t i ng . Deliver a 3-D atomistic simulation tool Analyze state-of-the-art devices for non- Enable analysis of arbitrary crystal commercial environments: structures, particles, atom compositions and Europa -> Radiation and low temperature bondktructure at arbitrary temperatures and effects. Aging and failure modes. ambient electric and magnetic fields. Jovian system -> Magnetic field effects Collaborators: Venus -> high temperature materials: SiGe U. of Alabama, Ames, Purdue, Ohio State, Impact: -NlST ---. Low cost develoDment of revolutionarv techn. L Gerhard Klime JPL What is a Quantum Dot ? Basic Application Mechanisms Physical Structure: Well conducting domain surrounded in all 3 dim. by low conducting region(s) Domain size on the nanometer scale

Gerhard Klimeck Applied Cluster Computing Technologies Grou 3 JPL What is a Quantum Dot ? Basic Application Mechanisms Physical Structure: Well conducting domain surrounded in all 3 dim. by low conducting region(s) Domain size on the nanometer scale Electronic structure: Contains a countable number of electrons Electron energy may be quantized -> artificial atoms (coupled QD->molecule)

- PI- I JPL Eigenvalue- Solver for I08xl O8 Matrices Hermitian and Non-Hermitian Matrices

*T Nanoscale Quantum States strucibre I) (Artificial Atoms, size 20nm) GaAs InAs GaAs

Objective: Need to locate new quantum state energies and wave functions. Problem: Realistic Quantum Dots consist of about 1-10 x IO6 atoms Realistic system is OPEN Approach: Custom Lanczos Eigenvalue Solver for Hermitian and non-Hermitian Matrices Also use folded spectrum method. Parallel implementation

Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Nanotechnology I Nanoelectronic Example Implementations Self-assembled , InGaAs on GaAs.

Pyramidal or dome shaped

R,Leon,JPL(1998)

JPL Application: JPL Applications: Transducers, filters IR Sensors

Molecular Dots Ruthen i u m-based molecule Ru4(NH3)16(C4H4 N2)41O+ proposed by Marya Lieberman, Notre JPL Applications: Non-volatile Memory Dame (1999) omputing Appl.

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I saJeu!pJoo=zO 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 JPL Fundamental Analysis: Alloy Disorder in QDs I Problem: Simulation of Alloy Dot Ensemble Cations are randomly distributed in alloy dots. EC(000 Does alloy disorder limit electronic 7 structure uniformity for dot ensembles? Approach : r=?t Simulate a statistical ensemble of alloyed \r F dots. I c Requires atomistic simulation tool.

Inom6Ga,,As Lense Shaped Dot Diameter=30nm,Heig ht=finm, GaAs em beddec -1,000,000 Atom Simulation, sp3s* basis In and Ga atoms are randomly distributec lnhomogenious Broadening? Gerhard Klimeck Applied Cluster Computing Technologies Group JPL I Spatial Irregularity in the Hole Ground St

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-10 x (nm) VCA I no Disorder Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Spatial Irregularity in the Hole Ground Stat

2 2

0 0

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Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Fundamental Analysis: Alloy Disorder in QDs I Problem: Simulation of Alloy Dot Ensemble Cations are randomly distributed in alloy 2 dots. Does alloy disorder limit electronic structure uniformity for dot ensembles? Approach : Simulate a statistical ensemble of alloyed dots. Requires atomistic simulation tool.

In,,,Ga,,As Lense Shaped Dot Diameter=30nm,Height=Snm, GaAs embedde( -1,000,000 Atom Simulation, sp3s" basis In and Ga atoms are randomly distributec lnhomogenious Broadening? Gerhard Klimeck Applied C I uster Computing Tech nologies Group JPL Presentation Outline Introduction / Motivation Nan0 device needs, modeling needs. *Critical look at the SIA Roadmap. 1D heterostructure modeling Ba nd st ruet ure eng inee ri n g basics . Resonant tunneling diodes .Hole transport (Ed Stone Award). .NEMO 1-D - First quantum device simulator. 3D heterostructure modeling NEMO 3-D Modeling agenda. *What is a quantum dot? .Quantum dot examples. .Alloy disorder in quantum dots. Analysis and Synthesis using Genetic Algorithms (GAS) GA basics Design Synthesis Conclusion / Outlook

Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Global Optimization via Genetic Algorithms

sin(x) sin(y) sin@ - 4) sin@ - 4) my)= + 0.7 x Y (x-4) (Y-4)

Gerhard Klimeck Applied CI uster Computing Technologies Group JPL Global Optimization: Genetic Algorithm Development Genetic Algorithm Convergence pop = 100, 300 generations, steady-state (IO%), 2-point crossover p = 0.85, mut t tion = 112

Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Basic Genetic Algorithm

Genetic algorithm parameter optimization is based on: Survival of good parameter sets Evolution of new parameter sets .Survival of a diverse population

Optimization can be performed globally, rather than locally.

Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Basic Evolution Operations Each set (Si) consists of several parameters (Pi) .The parameters Pj can be of different kinds: real, integers, symbols, ....

Gross Exploration Fine Tuning

Crossover explores different Creation of new gene values. combinations of existing genes. Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Genetically Engineered Nanoelectronic Structures (GENES) Objectives: Automate nanoelectror ic device synthesis, analysis, and op imizal on using genetic algorithms (GA). Approach : Augment paralle genetic algorithm (PGApack). Combine PGApack with NEMO. Develop graphical user interface for GA.

How do you know what you have built?

Resu Its : Nanoelectronic Device Structural 10 nn analysis 0 0 0.2 Applied0.4 Bias0.6 (V) 0.8 GA analyzed atomic monolayer structure

w and doping profile of RTD device Length Black: structure sc)ecs, Blue: Best fit A Gerhard Klimeck Applied Cluster Computing Technologies Group JPL Conclusions / Future Vision Nanoelectronics devices are already being build Quantum Dots Grading JPL is part of the national nanotechnology push Nanoelectronic devices will have impact on remote space exploration : Sensors lasers

Gerhard Klimeck Applied Cluster Computing Technologies Group