Nanoindentation is an increasingly used tool to investigate the mechanical properties of very small volumes of material. Gold single crystals were chosen as a model system for surface modification studies, because of the electrochemical advantages and the simple structure of the material. Experiments on these samples displayed a spectrum of residual deformation, with measured hardness values on the same surface differing by over a factor of two. The yield point also exhibited considerable variation, but the depth of penetration was independent of this elastic–plastic transition. The onset of plastic deformation in these tests is observed at stress levels on the order of the theoretical yield strength. There are a limited number of defects in a single crystal specimen of gold, especially on the length scale required to influence nearly every indentation experiment. A test matrix was designed to change the concentrations of possible defects in a sample (dislocations, vacancies, and structural features), by altering some of the surface preparation parameters. The results of these experiments were extremely consistent. Observed trends within the matrix, combined with the observations of reduced hardness and earlier plasticity when compared to the preliminary testing, indicate a decline in the structural continuity of the sample. This is surprising considering the extensive material removal and thermal history of some of these surfaces. There is no indication of a cause for the dramatic inconsistencies in mechanical properties observed in preliminary testing, but a consistent surface enables the study of intentional modifications. Changes in contact area that were undetectable in preliminary results now demonstrate predictable shifts in hardness values. The deposition of a single monolayer of gold oxide raised the average load at yield by a factor of three and increased the hardness by over 26%. Attributing this change to the oxide is corroborated by the reduction of hardness when the oxide is stripped. Similar behavior is observed when a lead monolayer is deposited and tested ex-situ. It is surprising that layers <0.5 nm in thickness would have such a dramatic influence on indentation tests at least 35 nm deep. This indicates that no surface layer can be ignored at this scale. These experiments demonstrate that there is still much to be learned about nanoscale deformation mechanisms. / Ph. D.

Transfer-appropriate processing (TAP) proposes that retrieval success is based on the match between processing at encoding and retrieval. We propose that the processing described by TAP determines the contextual cues that are encoded with an event. At retrieval, the presence or absence of contextual cues matching the encoding cues will influence success. To implement these principles as a strategy to improve memory, the nature of future retrieval processing or cues must be known during encoding. As this is unlikely in real-world memory function, we propose that increased encoding variability – increasing the range of encoded cues – increases the likelihood of TAP when the retrieval scenario is unknown. The larger the set of encoded cues, the more likely those cues will recur during retrieval and therefore achieve TAP. Preliminary research in our lab (Diana, unpublished data) has found that increased encoding variability improves memory for item information in a novel retrieval context. To test whether this benefit to memory is due to the increased likelihood of TAP, the current experiment compared the effects of encoding variability under conditions that emphasize TAP to conditions that reduce TAP. We found main effects of encoding variability and TAP, but no interaction between the two. Planned comparisons between high and low variability encoding contexts within matching and non-matching retrieval contexts did not produce a significant difference between high and low variability when encoding-retrieval processing matched. We conclude that further studies are necessary to determine whether encoding variability has mechanisms that benefit memory beyond TAP. / M.S. / It is well accepted within the episodic memory literature that successful memory retrieval is often driven by context cues. Specifically, the cues that are stored with the memory of the event. To develop a better understanding of how episodic memory works, we must understand how manipulating context cues changes memory performance. One way to investigate the effects of context manipulation is using encoding variability, which refers to the amount of variability (i.e., change) in context cues from one repetition of an item or event, to the next. Preliminary research in our lab (Diana, unpublished data) has found that increased encoding variability improves memory retrieval in a novel context, but it is unclear why this is the case. We proposed that the mental processing described by transfer-appropriate processing (TAP) – a principle stating that memory retrieval success is determined by the match, or overlap, between the mental processing at encoding (i.e., memory formation) and memory retrieval – determines the contextual cues that are stored with the memory at encoding. We hypothesized that encoding variability works even when TAP has already been achieved by matching the processing and cues at encoding to those at retrieval. Alternatively, we hypothesized that encoding variability works by specifically achieving TAP, so that encoding variability is only helpful when the encoding and retrieval contexts do not match. Results indicated partial support for the alternative hypothesis, suggesting that encoding variability works by achieving TAP. However, these results were not sufficiently conclusive, and it is likely that there are other mechanisms that allow for encoding variability to improve memory. This study establishes the groundwork for future work examining encoding variability and its effects on memory.

The Arctic sea-ice cover plays an important role for the global climate system. Sea ice and the overlying snow cover reflect up to eight times more of the solar radiation than the underlying ocean. Hence, they are important for the global energy budget, and changes in the sea-ice cover can have a large impact on the Arctic climate and beyond. In the past 36 years the ice cover reduced significantly. The largest decline is observed in September, with a rate of more than 12% per decade. The negative trend is accompanied by large inter-annual sea-ice variability: in September the sea-ice extent varies by up to 27% between years. The processes controlling the large variability are not well understood. In this thesis the atmospheric contribution to the inter-annual sea-ice variability is explored. The focus is specifically on the thermodynamical effects: processes that are associated with a temperature change of the ice cover and sea-ice melt. Atmospheric reanalysis data are used to identify key processes, while experiments with a state-of-the-art climate model are conducted to understand their relevance throughout different seasons. It is found that in years with a very low September sea-ice extent more heat and moisture is transported in spring into the area that shows the largest ice variability. The increased transport is often associated with similar atmospheric circulation patterns. Increased heat and moisture over the Arctic result in positive anomalies of water vapor and clouds. These alter the amount of downward radiation at the surface: positive cloud anomalies allow for more longwave radiation and less shortwave radiation. In spring, when the solar inclination is small, positive cloud anomalies result in an increased surface warming and an earlier seasonal melt onset. This reduces the ice cover early in the season and allows for an increased absorption of solar radiation by the surface during summer, which further accelerates the ice melt. The modeling experiments indicate that cloud anomalies of similar magnitude during other seasons than spring would likely not result in below-average September sea ice. Based on these results a simple statistical sea-ice prediction model is designed, that only takes into account the downward longwave radiation anomalies or variables associated with it. Predictive skills are similar to those of more complex models, emphasizing the importance of the spring atmosphere for the annual sea-ice evolution. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Manuscript. Paper 4: Manuscript.</p>

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A linear multiple regression statistical model is applied to estimate the solar induced component of odd nitrogen variability in the stratosphere and lower mesosphere using UARS HALOE data for 1991–2003. Consistent with earlier studies, evidence is obtained for a decadal NOx variation at the highest available latitudes (50° – 70°) that projects positively onto the solar cycle. This variation, which is most statistically significant in the Southern Hemisphere, also correlates positively with the auroral Ap index. It is therefore probably caused by downward transport during the polar night of thermospheric and mesospheric odd nitrogen. In addition, at low latitudes near and above the stratopause, evidence is obtained for an inverse solar cycle NOx variation. It is suggested that this low-latitude response may be caused primarily by increased photolysis of NO under solar maximum conditions. Throughout most of the rest of the stratosphere, no statistically significant response is obtained.

A promising technique for the large-scale manufacture of micro-fluidic devices and photonic devices is hot embossing of polymers such as PMMA. Micro-embossing is a deformation process where the workpiece material is heated to permit easier material flow and then forced over a planar patterned tool. While there has been considerable, attention paid to process feasibility very little effort has been put into production issues such as process capability and eventual process control. In this paper, we present initial studies aimed at identifying the origins and magnitude of variability for embossing features at the micron scale in PMMA. Test parts with features ranging from 3.5- 630 µm wide and 0.9 µm deep were formed. Measurements at this scale proved very difficult, and only atomic force microscopy was able to provide resolution sufficient to identify process variations. It was found that standard deviations of widths at the 3-4 µm scale were on the order of 0.5 µm leading to a coefficient of variation as high as 13%. Clearly, the transition from test to manufacturing for this process will require understanding the causes of this variation and devising control methods to minimize its magnitude over all types of parts. / Singapore-MIT Alliance (SMA)

Embedded SRAMs can occupy the majority of the chip area in SOCs. The increase in process variation and aging degradation due to technology scaling can severely compromise the integrity of SRAM memory cells, hence resulting in cell failures. Enough cell failures in a memory can lead to it being rejected during initial testing, and hence decrease the manufacturing yield. Or, as a result of long-term applied stress, lead to in-field system failures. Certain types of cell failures can be mitigated through improved timing control. Post-fabrication programmable timing can allow for after-the-fact calibration of timing signals on a per die basis. This allows for a SRAM's timing signals to be generated based on the characteristics specific to the individual chip, thus allowing for an increase in yield and reduction in in-field system failures. In this thesis, a delay line based SRAM timing block with digitally programmable timing signals has been implemented in a 180 nm CMOS technology. Various timing-related cell failure mechanisms including: 1). Operational Read Failures, 2). Cell Stability Failures, and 3). Power Envelope Failures are investigated. Additionally, the major contributing factors for process variation and device aging degradation are discussed in the context of SRAMs. Simulations show that programmable timing can be used to reduce cell failure rates by over 50%.

Via the delivery of blood, heart transfers oxygen and nutrients to various organs and is thus a highly influential for circulatory system. To adapt to the variation of physiological conditions, the intensity and frequency of heart beats change with time. Careful observation finds that the time intervals between heartbeats are often different even if the body is at rest. Such heart rate variability (HRV) has been used to estimate the activity of the autonomic nervous system which can be divided into sympathetic and parasympathetic subsystems both of which can significantly affect the physiology of the human body. As a result, HRV has been used as a physiological indicator to assist doctors in making diagnostic decisions. Many studies have used HRV to analyze the ECG signal via studying the QRS complex waveform to determine the time intervals between R-peaks and analyze the R-R intervals from time and frequency domains. Different from the conventional R-R Interval based approach, this work introduces new HRV feature variables by computing spectrogram of the ECG signal waveform. In particular, based on the harmonics of the spectrum, we introduce the concepts of modes. By find the relative amount of energy associated with each mode and degree-of-energy-concentration associated with each mode, this work introduces two sets of new HRV features. In addition, we also investigate how these variables change with time and the correlations between these features. To demonstrate the potential of the proposed features, the differences of the values of the proposed features are compared for healthy individuals versus OSA patients, young versus old and male versus female. The experimental results show the differences between many of the tested features are statistically significant.