IIn-situ Liquid-Cell TEM Studies of Nucleation and Growth at Nanoscale

The chemical reactions leading to precipitation or nucleation of new phase in liquid solution is of interest in many applications ranging from materials synthesis to biologically-induced materials and energy storage systems. A better understanding of these reactions at the nanoscale level requires imaging and spectroscopy of nucleation and growth events in the liquid media. The development of nanotechnology, especially the liquid-cell transmission electron microscopy (TEM) provides new opportunities for direct visualization of dynamic processes in solution in real-time. Liquid phase processes are important in various aspects such as mineral growth, biomineralization process, and even electrochemical reactions. In this thesis, we studied the in-situ liquid cell mineralization of calcium based-minerals including gypsum (CaSO4•2H2O) and hydroxyapatite (HA), as well as electrochemical deposition in lithium-oxygen (Li-O2) batteries. We observed that both classical and non-classical nucleation and growth events can happen during the formation of calcium-based minerals. We showed that the fabrication of gypsum microneedles can bypass the formation of intermediate basanite (CaSO4•0.5H2O). We were able to show the complete pathways for HA formation following both classical and non-classical theories. Interesting, we observed that the growth of HA crystals depended on the dissolution rate of amorphous calcium phosphate phases. For the electrochemical battery study, the (electro)chemical fundamentals in a working Li-O2 battery is explored. This work revealed further details of underlying mechanisms in a working Li-O2 battery and identifies various limiting factors controlling the discharge and charge processes

The cryo-thermal therapy-induced IL-6-rich acute pro-inflammatory response promoted DCs phenotypic maturation as the prerequisite to CD4⁺ T cell differentiation

<p>In our previous studies, a novel tumour therapeutic modality of the cryo-thermal therapy has been developed leading to long-term survival in 4T1 murine mammary carcinoma model. The cryo-thermal therapy induced the strong acute inflammatory response and IL-6 was identified in an acute profile. In this study, we found that the cryo-thermal therapy triggered robust acute inflammatory response with high expression of IL-6 locally and systemically. The phenotypic maturation of dendritic cells (DCs) was induced by acute IL-6 following the treatment. The mature DCs promoted CD4⁺ T cell differentiation. Moreover, the production of interferon γ (IFN γ) in the serum and CD4⁺ T cells were both abrogated by IL-6 neutralisation following the treatment. Our findings revealed that the cryo-thermal therapy-induced acute IL-6 played an important role in initiating the cascading innate and adaptive anti-tumour immune responses, resulting in CD4⁺ T cell differentiation. It would be interesting to investigate acute IL-6 as an early indicator in predicating tumour therapeutic effect.</p

Passenger flow in the URT networks.

<p>(a) In the San Francisco URT network, the colors indicate the passenger flow of URT segment . (b) Same as (a) but for the Boston URT network. (c) The passenger flow follows a power-law distribution () with () in San Francisco (Boston). (d) In San Francisco, the betweenness centrality can be approximated by a Gaussian distribution (). In Boston, the betweenness centrality can also be approximated by a Gaussian distribution (). (e) Low correlations were observed between passenger flow and the betweenness centrality . The topology of the Boston URT network was found to have a greater effect on shaping the passenger flow distribution than that of the San Francisco URT network did (<i>PCC</i> = 0.79).</p

Vulnerability Analysis and Passenger Source Prediction in Urban Rail Transit Networks

<div><p>Based on large-scale human mobility data collected in San Francisco and Boston, the morning peak urban rail transit (URT) ODs (origin-destination matrix) were estimated and the most vulnerable URT segments, those capable of causing the largest service interruptions, were identified. In both URT networks, a few highly vulnerable segments were observed. For this small group of vital segments, the impact of failure must be carefully evaluated. A bipartite URT usage network was developed and used to determine the inherent connections between urban rail transits and their passengers' travel demands. Although passengers' origins and destinations were easy to locate for a large number of URT segments, a few show very complicated spatial distributions. Based on the bipartite URT usage network, a new layer of the understanding of a URT segment's vulnerability can be achieved by taking the difficulty of addressing the failure of a given segment into account. Two proof-of-concept cases are described here: Possible transfer of passenger flow to the road network is here predicted in the cases of failures of two representative URT segments in San Francisco.</p></div

Alternative routes in the road network.

<p>(a) The color of a road segment represents the potential passenger flows transferring to it when the URT segment from Market St. and Buchanan St. to Market St. and South Van Ness Ave. fails. (b) Same as (a) but for an actual disconnection of the URT segment from Duboce Ave. and Noe St. to Church St. and Duboce Ave. during a maintenance project in San Francisco. (c) The potential alternative bus routes when the URT segment from Market St. and Buchanan St. to Market St. and South Van Ness Ave. breaks down (red lines) and the potential alternative bus routes that were available during the maintenance project (blue lines). (d) The distribution of passenger flow indicates different patterns of travel demand put on the San Francisco road network.</p

Locating major passenger sources (MPS) and major passenger destination (MPD).

<p>(a) In the San Francisco URT network, the census tracts in yellow, orange, and red indicate the MPS passenger production values of the most vulnerable segment. The census tracts shown in shades of blue represent the segments' MPD passenger attraction values. Black links indicate the connections between each selected URT segment and its MPS. (b) In the Boston URT network, the census tracts in yellow, orange, and red indicate the MPS values of the most vulnerable segment. The census tracts shown in shades of blue represent the segments' MPD values. Black links indicate the connections between each selected URT segment and its MPS. (c) The color of each segment represents its number of MPS (). (d) The color of each segment represents its number of MPS (). (e) The distribution of the number of major sources of passengers in San Francisco. (f) The distribution of the number of major passenger destinations in San Francisco. (g) The distribution of the number of major sources of passengers in Boston. (h) The distribution of the number of major passenger destinations in Boston.</p

Distribution of the trip travel time.

<p>In San Francisco, the duration of a URT trip showed a double Gaussian distribution (). In Boston, the duration of a URT trip showed a Gaussian distribution ().</p

The URT network data and the human mobility data.

<p>(a) The black arrow points to the geographical center of the San Francisco URT network. The URT segments with directions heading to the geographical center are here considered “inbound” segments, and the URT segments with directions leaving away from the geographical center are considered “outbound” segments. (b) The geographic center and outbound segments in the Boston URT network. (c) The blue polygons on the San Francisco map indicate the census tracts, and the light gray dots indicate the centers of the city blocks. The San Francisco daily commuting OD data are recorded in a city-block resolution. (d) The blue polygons on the Boston map indicate the census tracts, and the light gray dots indicate the locations of mobile phone users detected during the three-week observational period.</p

Phylogenetic relationships among basal Hexapods inferred from Bayesian analysis of 13 protein-coding sequences.

<p>1 Protura species, 10 Collembola species and 3 Diplura species were used as the outgroup. Numbers denoted posterior probabilities of nodes.</p

Phylogenetic tree yielded by G12 dataset.

<p>All conserved regions after being aligned were retained. Phylogenetic analyses were based on first and second codon positions of 13 protein-coding genes. The tree was rooted with the sequences of two outgroup species: <i>Onychiurus orientalis</i> and <i>Campodea lubbocki</i>. Almost the same topologies were obtained in G12 dataset compared with W12 dataset.</p