Browsing by Subject "RTN"
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Item Methodologies for Statistical Characterization of Circuit Reliability in Advanced Silicon Processes(2012-07) Jain, PulkitRising electric fields and imperfections due to atomic level scaling create non-ideal and stochastic electrodynamics inside a transistor.These appear as reliability mechanisms such as Bias Temperature Instability (BTI), Time Dependent Dielectric Breakdown (TDDB) and Random Telegraph Noise (RTN) at transistor level, and as a convolved statistical manifestation in performance and functionality, at a circuit level. Compounded by shrinking operating margins with process variability and power constraints, these reliability issues have been propelled from device research arena to the forefront of chip design.The first part of my thesis will explore these different reliability issues in three dedicated test chips. While device level probing has been de-facto estimation method for reliability engineers due to legacy and simplicity, the approach has become cumbersome due to time and effort needed to cover the required statistics. Conversely, we demonstrate circuit based reliability monitors which are a more scalable and representative alternative. The latter also enable superior timing resolution which is critical to record phenomenon such as BTI and RTN without measurement noise. For example, leveraging on-chip methods and intelligent timing control, we demonstrate a SRAMreliability macro with BTI estimation at three order smaller measurement times than possible using conventional approaches. On-chip logic could also be used to control test on large number of blocks resulting in a large experiment time speedup which is the basis for our TDDB macro.The second part of my thesis will focus on 3D integration, a reakthrough technology for reducing interconnects delays and chip form factors. In particular, we measure the impact of chip stacking on power delivery and propose schemes to mitigate it through a statistical framework, fabricated in an actual 3D technology.Overall, the ideas here can pave the way for not only accurate empirical modeling and robust guard-banding for pre-silicon phase but also post-silicon adaptive tuning. And thus we can better reap the benefits of these new silicon technologies.Item Non-Equilibrium Two-State Switching in Mesoscale, Ferromagnetic Particles(2019-07) Delles, JamesThere has been much theoretical study attempting to expand upon the Arrhenius law, $f=f_o exp(U/kT)$, which describes the switching rate in thermally activated, two-state systems, but few experiments to verify it. This is especially true for ferromagnetic particles. Most of the previous experiments performed attempting to study the Arrhenius law focus on the effect the Boltzmann factor, exp(U/kT), has on the switching rate since it dominates any measurement due to its exponential dependence on temperature. This has made it difficult to probe the underlying physics of the prefactor in front of the exponential. Using square, ferromagnetic particles of sizes 250 nm x 250 nm x 10 nm and 210 nm x 210 nm x 10 nm, controlling the barrier height using an applied field, and measuring the average dwell times in each individual state has allowed us to focus on these prefactors. Our measured prefactors vary by twenty five orders of magnitude, and they are smaller than those predicted by previous theories for particles of this size. They become so small as to reach unphysically short timescales. We attribute these unexpectedly small prefactors to our magnetic particles being multidomain and undergoing transitions before the particles have time to reach thermal equilibrium. We show that our particles have a higher probability of transitioning the less time they have been in a state which we attribute to the magnetization spending most of its time near the barrier allowing faster transitions.