1. Trap Engineering for device design and reliability modeling in memory/logic application 1/12 2015 년 02 월 xx 일 School of EE, Seoul National University 대표 학생이승만 과제 책임자박영준 교수

2. 연구 성과 요약 (’10.07~’14. 12) 1. 참여 기간 : 2010. 07. 01 ~ 현재 2. 전략산학 장학생 현황 : ( 총 0 명 ) - 1 차년도 이후 누적 입사 : 총 4 명 ( 입사 : 우준명, 박수영, 심경석, 최연규 ) - 학술연수 : 총 8 명 ( 졸업 : 이석하, 권혁제, 박상용, 권주성, 심혜원 / 김희중, 문중수, 김강욱 ) 3. 대표 연구 주제 : - 3D MCRD framework 을 통한 NBTI-SILC-TDDB simulation - BEOL TDDB 에 대한 Theoretical approach (MC / analytic method) - Billions of transistors 에 대한 소자 산포 예측, tail part modeling 4.5 년간 전략산학 연구 성과 결산 2/12

3. 3/12 대표 논문 Review 논문 제목 : A 3-D Statistical Simulation Study of Mobility Fluctuations in MOSFET Induced by Discrete Trapped Charges in SiO2 Layer 논문 내용 : - Discrete trap 이 mobility 및 channel 의 current flux 에 미치는 영 향을 분석하였다. Si bar 에 대한 atomistic 한 시뮬레이션을 통해 트랩 주변으로 흐르는 current contour 가 mobility degradation 에 직접적인 영향을 준다는 것을 보였다.

4. 선정 이유 : - Discrete trap 이 mobility 및 channel 의 current flux 에 미치는 영향을 분석하 였음. 이러한 현상은 scale down 된 소자의 trap 에 의한 신뢰성 분석에 필수적 이며 본 연구 과제의 주된 방법론임. 4/12 대표 논문 Review 저널 정보 : - 저널명 : IEEE Transactions on Nanotechnology -IF: 1.619, SJR 6175/29385 -Published 4 SCI Journal papers, 13 conference papers

5. Introduction 5 Status/Steps : Development of 3D MCRD Simulation Framework 1) Achievements: Unified Oxide Reliability Modeling Framework Interface reaction Molecular transport: Brownian random motion Conversion from precursor to active trap Leakage: Trap Assisted Tunneling current Breakdown: percolation model  Based on stochastic MC particle simulation 2) Predicting ‘tail’ part of 1 Billion transistors regarding step 1). percolation approach Oxide trap + discrete dopant  dV t distribution of 1Billion transistors in tractable time and resources - Solving present issues of ‘Causes’ and ‘Effects’ of degradation NBTI relaxation Unified model of NBTI-SILC-TDDB BEOL oxide TDDB  Setting up for practical simulation Framework -> Trajectory of sample hydrogen in the oxide

6. Unified Model of NBTI-SILC-TDDB in Gate Oxide Modeling Strategy 6 [TDDB: Time Dependent Dielectric Breakdown] [NBTI: Negative Bias Temperature Instability] cause [SILC: Stress Induced Leakage Current] > Gbit cells? effects Oxide Trap Profile BEOL oxide TDDB Apply percolation theory with MC method Field dependence based on percolation model Statistical Analysis Development of Analytical model

7. 3/12 Need to predict.. After aging(NBTI,) - Trap(E,r) Time 0 - Random Dopant PDF VTVT VTVT Statistical approach to the reliability Goal for statistical analysis Finding rule for WC Verifying physical validity Probability of the WC

8. Worst case analysis (current blocking potential mountain chain) 7/12 TypeLWTox(SiO2)N-Sub(N D ) PMOS50nm40nm2nm5e18/cm3 Identifying anomalous V T shift according to the trap(fixed charge) distribution V D = -0.05V uniformlyrandomlyVertically distributed 20 fixed charges – 1e12/cm2 40 fixed charges - 2e12/cm2 80 fixed charges - 4e12/cm2 Uniformly distributed Vertically distributed - Worst case randomly

9. Simulation results, finding rules of the worst case (vd-1.0 mesh 2A) (vd-0.05 mesh 2A) Dependence on the one slit with maximum distance Dependence on the average distance between fixed charges 20Vertical +60 random 40Vertical +40 random 0Vertical +80 random

10. Probability calculation Percolation(potential chain) Start line path_4 (xd) path_1 (xa) path_2 (xb) path_3 (xc) Probability of a trap in a Cell = trap density x area of a Cell SourceDrain Trap density Probability of the WC Occurrence 1e11/cm2 1.78E-58 1e12/cm2 1.10E-36 1e13/cm2 3.02E-11 -Probability of the trap existence in a cell : 1e-3 (=1e11/cm2*1e-14cm2) -Considered distance between traps : 1nm~2nm  When the probability of a cell becomes 1/1000, probability of the occurrence of the worst case approaches to 3/100 billion transistors Calculation of the WC occurrence probability(permutation) x_position Kind of percolation 06 18 26 sample) A cell

11. Physical Validity of the Critical Length for WC Gate Oxide Substrate Depletion layer Ref[1] Verifying Physical Validity of Critical Length Method (on going) -Calculate potential fluctuation and its effective area due to a single charge through Image charge method -Definitions of effective potential area -The potential used to describe the scattering center(=screened Coulomb potential) suggested by BROOKS, HERRING, and DINGLE -How to cut off effective region from a infinite coulomb potential? -> Partial wave method (low energy scattering) -> Born approximation method (high energy scattering) => How to apply in defining critical length of the worst case?!  Electric field of a point charge through three or more dielectrics,  Si-SiO2 interface in not a equipotential surface, edge of the depletion region is equipotential ( symmetry to depletion edge) [1]T Takashima an, R Ishibashi, IEEE Trans. Electr. Insul, Vol EI-13, No 1, February 1978 [2] Brooks H., Vol. 7. Academic Press, Inc., New York (1956). [3] CONWELL E. M and WEISSKOPF V. F. “Theory of impurity Scattering in Semiconductors” Phys. Rev. 77, 388 (1950). Ref[2,3]

12. 향후 계획 5 차년도 하반기 (’15.1~’15.6) 주요 연구 계획 -BEOL oxide TDDB Development of analytic model -‘tail’ part modeling of ‘over 1B’ devices Defining critical length and verifying Physical validity Comparing V T distribution tail of the conventional analytic model with modeling results Considering the quantum effect(DG) 12/12