Nickel silicide is one of the electrical contact materials widely used on very large scale integration (VLSI) of Si devices in microelectronic industry. This is because the silicide/silicon interface can be formed in a highly controlled manner to ensure reproducibility of optimal structural and electrical properties of the metal-Si contacts. These advantages can be inherited to Si nanowire (NW) field-effect transistors (FET) device. Due to the technological importance of nickel silicides, fundamental materials science of nickel silicides formation (Ni-Si reaction), especially in nanoscale, has raised wide interest and stimulate new insights and understandings. In this dissertation, in-situ transmission electron microscopy (TEM) in combination with FET device characterization will be demonstrated as useful tools in nano-device fabrication as well as in gaining insights into the process of nickel silicide formation. The shortest transistor channel length (17 nm) fabricated on a vapor-liquid-solid (VLS) grown silicon nanowire (NW) has been demonstrated by controlled reaction with Ni leads on an in-situ transmission electron microscope (TEM) heating stage at a moderate temperature of 400 ºC. NiSi2 is the leading phase, and the silicide-silicon interface is an atomically sharp type-A interface. At such channel lengths, high maximum on-currents of 890 (μA/μm) and a maximum transconductance of 430 (μS/μm) were obtained, which pushes forward the performance of bottom-up Si NW Schottky barrier field-effect transistors (SB-FETs). Through accurate control over the silicidation reaction, we provide a systematic study of channel length dependent carrier transport in a large number of SB-FETs with channel lengths in the range of (17 nm - 3.6 μm). Our device results corroborate with our transport simulations and reveal a characteristic type of short channel effects in SB-FETs, both in on- and off-state, which is different from that in conventional MOSFETs, and that limits transport parameter extraction from SB-FETs using the conventional field-effect transconductance measurements.

In addition to application of silicide in Si NW devices, the fundamental materials science of Ni-Si reaction is also of interest, and in-situ TEM has been shown to be a useful tool in obtaining dynamical phase transformation information and therefore providing insights into the new phase formation process. By using in-situ TEM techniques, a new gold catalyzed solid-liquid-solid (SLS) silicide phase growth mechanism in Si NWs is observed for the first time, which shows the liquid mediating growth can be also used in synthesis of metallic silicide nanowires. SLS is analogous to the VLS in both being liquid-mediated, but is fundamentally different in terms of nucleation and mass transport. In our SLS growth at 700 ºC, the Ni atoms are supplied from remote Ni particles by interstitial diffusion through Si NW into the pre-existing Au particle at the tip. Upon supersaturation of both Ni and Si in Au, octahedral shape of Ni disilicide phase nucleates in the middle of the Au liquid alloy, which thereafter sweeps through the Si NW and transform Si into NiSi2. Dissolution of Si by Au(Si,Ni) liquid mediating layer and growth of NiSi2 are shown to proceed in different manners.

Using in-situ TEM technique, we also have the chance to present direct evidence that Si (111) twin boundaries and Si grain boundaries on Si NW surface can be efficient heterogeneous nucleation site for the silicide growth. By analyzing the nucleation site favorability, unlike other typical FCC materials like Cu or Si, we infer (111) twin defects in NiSi2 may have high interfacial energy. These results may provide valuable insights into the MOSFET source/drain (S/D) contact silicide formation process when defects are either unintentionally formed during the process or intentionally introduced to engineering the strain along the channel.

This study uses latent class modeling (LCM) to explore the effects of channel-specific perceptions, along with other variables, on purchase channel intention. Using data on book purchases collected from an Internet-based survey of two university towns in Northern California, we develop a latent class model with two segments (final N=373). Age turns out to be the only observed determinant of class membership, and in the intention model, the mostly-younger segment is more cost-sensitive and the mostly-older segment appears to be more conveni¬ence-sensitive. The results clearly demonstrate the effects on purchase intention of chan¬nel-specific perceptions, purchase experience, context and socio¬demographics. Comparing the LCM to the unsegmented model and to models deterministically segmented on age indicates that the LCM is slightly better from the statistical perspective, but arguably weaker from the conceptual perspective. However, a model that interacts age with the explanatory variables in the conventional unsegmented model outperforms all the others (though not overwhelmingly so), including the LCM. Thus, our results suggest that using LCM as an initial stage in model exploration allows us to more intelligently specify a model where the taste heterogeneity is (potentially) specified deterministically in the end, which often yields a more parsimonious model, and may in fact fit the data better.

This study uses latent class modeling (LCM) to explore the effects of channel-specific perceptions, along with other variables, on purchase channel intention. Using data on book purchases collected from an Internet-based survey of two university towns in Northern California, we develop a latent class model with two segments (final N=373). Age turns out to be the only observed determinant of class membership, and in the intention model, the mostly-younger segment is more cost-sensitive and the mostly-older segment appears to be more convenience-sensitive. The results clearly demonstrate the effects on purchase intention of channel-specific perceptions, purchase experience, context and sociodemographics. Comparing the LCM to the unsegmented model and to models deterministically segmented on age indicates that the LCM is slightly better from the statistical perspective, but arguably weaker from the conceptual perspective. However, a model that interacts age with the explanatory variables in the conventional unsegmented model outperforms all the others (though not overwhelmingly so), including the LCM. Thus, our results suggest that using LCM as an initial stage in model exploration allows us to more intelligently specify a model where the taste heterogeneity is (potentially) specified deterministically in the end, which often yields a more parsimonious model, and may in fact fit the data better.

Working at home is widely viewed as a useful travel-reduction strategy, and partly for that reason, considerable research related to telecommuting and home-based work has been conducted in the last two decades. The contribution of this study is to examine the effect of residential neighborhood built environment (BE) factors on working at home. Using data from a survey of eight neighborhoods in Northern California, we develop a multinomial logit (MNL) model of work-at-home (WAH) frequency. Potential explanatory variables include sociodemo­graphic traits, neighborhood preferences and perceptions, objective neighborhood characteristics, and travel attitudes and behavior. The results clearly demonstrate the contribution of built environment variables to WAH choices, in addition to previously-identified influences such as sociodemo­graphic predictors and commute time. The findings suggest that land use and transportation strategies that are desirable from some perspectives will tend to weaken the motivation to work at home, and conversely, some factors that seem to increase the motivation to work at home are widely viewed as less sustainable. Accordingly, this research points to the complexity of trying to find the right balance among demand management strategies that sometimes act in competition rather than in synergy.

Working at home is widely viewed as a useful travel-reduction strategy, and partly for that reason, considerable research related to telecommuting and home-based work has been conducted in the last two decades. The contribution of this study is to examine the effect of residential neighborhood built environment (BE) factors on working at home. Using data from a survey of eight neighborhoods in Northern California, we develop a multinomial logit (MNL) model of work-at-home (WAH) frequency. Potential explanatory variables include sociodemo­graphic traits, neighborhood preferences and perceptions, objective neighborhood characteristics, and travel attitudes and behavior. The results clearly demonstrate the contribution of built environment variables to WAH choices, in addition to previously-identified influences such as sociodemo­graphic predictors and commute time. The findings suggest that land use and transportation strategies that are desirable from some perspectives will tend to weaken the motivation to work at home, and conversely, some factors that seem to increase the motivation to work at home are widely viewed as less sustainable. Accordingly, this research points to the complexity of trying to find the right balance among demand management strategies that sometimes act in competition rather than in synergy.