ENERGETIC BIOCIDAL MATERIALS AND SPORE NEUTRALIZATION

The objective of this dissertation is to explore a more accurate and versatile approach to investigating the neutralization of spores suffered from ultrafast heating and biocide based stresses, and further to explore and understand novel methods to supply ultrafast heating and biocides through nanostructured energetic materials A surface heating method was developed to apply accurate (± 25 ˚C), high heating rate thermal energy (200 - 800 ˚C, ~103 - ~105 ˚C/s). Uniform attachment of bacterial spores was achieved electrophoretically onto fine wires in liquids, which could be quantitatively detached into suspension for spore enumeration. The spore inactivation increased with temperature and heating rate, and fit a sigmoid response. The neutralization mechanisms of peak temperature and heating rate were correlated to the DNA damage at ~104 ˚C/s, and to the coat rupture by ultrafast vapor pressurization inside spores at ~105 ˚C/s. Humidity was found to have a synergistic effect of rapid heating and chlorine gas to neutralization efficiency. The primary neutralization mechanism of Cl2 and rapid heat is proposed to be chlorine reacting with the spore surface. The stress-kill correlation above provides guidance to explore new biocidal thermites, and to probe mechanisms. Results show that nano-Al/K2S2O8 released more gas at a lower temperature and generated a higher maximum pressure than the other nano-Al/oxysalts. Given that this thermite formulation generates the similar amount of SO2 as O2, it can be considered as a potential candidate for use in energetic biocidal applications. The reaction mechanisms of persulfate and other oxysalts containing thermites can be divided into two groups, with the reactive thermites (e.g. Al/K2S2O8) that generate ~10× higher of pressure and ~10× shorter of burn time ignited via a solid-gas Al/O2 reaction, while the less reactive thermites (e.g. Al/K2SO4) following a condensed phase Al/O reaction mechanism. These different ignition mechanisms were further re-evaluated by investigating the roles of free and bound oxygen. A constant critical reaction rate for ignition was found which is independent to ignition temperature, heating rate and free vs. bound oxygen.

Thermal Tracking and Estimation for Microprocessors

Due to increasing integration density and operating frequency of today's high performance processors, the temperature of a typical chip can easily exceed 100 degrees Celsius. However, the runtime thermal state of a chip is very hard to predict and manage due to the random nature in computing workloads, as well as the process, voltage and ambient temperature variability (together called PVT variability). The uneven nature (both in time and space) of the heat dissipation of the chip could lead to severe reliability issues and error-prone chip behavior (e.g. timing errors). Many dynamic power/thermal management techniques have been proposed to address this issue such as dynamic voltage and frequency scaling (DVFS), clock gating and etc. However, most of such techniques require accurate knowledge of the runtime thermal state of the chip to make efficient and effective control decisions. In this work we address the problem of tracking and managing the temperature of microprocessors which include the following sub-problems: (1) how to design an efficient sensor-based thermal tracking system on a given design that could provide accurate real-time temperature feedback; (2) what statistical techniques could be used to estimate the full-chip thermal profile based on very limited (and possibly noise-corrupted) sensor observations; (3) how do we adapt to changes in the underlying system's behavior, since such changes could impact the accuracy of our thermal estimation. The thermal tracking methodology proposed in this work is enabled by on-chip sensors which are already implemented in many modern processors. We first investigate the underlying relationship between heat distribution and power consumption, then we introduce an accurate thermal model for the chip system. Based on this model, we characterize the temperature correlation that exists among different chip modules and explore statistical approaches (such as those based on Kalman filter) that could utilize such correlation to estimate the accurate chip-level thermal profiles in real time. Such estimation is performed based on limited sensor information because sensors are usually resource constrained and noise-corrupted. We also took a further step to extend the standard Kalman filter approach to account for (1) nonlinear effects such as leakage-temperature interdependency and (2) varying statistical characteristics in the underlying system model. The proposed thermal tracking infrastructure and estimation algorithms could consistently generate accurate thermal estimates even when the system is switching among workloads that have very distinct characteristics. Through experiments, our approaches have demonstrated promising results with much higher accuracy compared to existing approaches. Such results can be used to ensure thermal reliability and improve the effectiveness of dynamic thermal management techniques.