Leo Chau-Kuang Liau

Expert system of a crude oil distillation unit for process optimization using neural networks

Abstract An expert system of crude oil distillation unit (CDU) was developed to carry out the process optimization on maximizing oil production rate under the required oil product qualities. The expert system was established using the expertise of a practical CDU operating system provided by a group of experienced engineers. The input operating variables of the CDU system were properties of crude oil and manipulated variables; while the system output variables were defined as oil product qualities. The knowledge database of the CDU operating model can be built using the input–output data with an approach of artificial neural networks (ANN). The built ANN model can be applied on predicting the oil product qualities with respect to the system input variables. In addition, a design of experiment was implemented to analyze the effect of the system input variables on the oil product qualities. Optimal operating conditions were then found using the knowledge database with an optimization method according to a defined objective function. The built expert system can provide on-line optimal operating information of the CDU process to the operators corresponding to the change of crude oil properties.

Process optimization of sedimentation self-assembly of opal photonic crystals under relative humidity-controlled environments

Minimum time of fabricating high quality of opal photonic band gap (PBG) crystal films was obtained by adjusting the relative humidity (RH)-controlled environments using the process optimization approach developed in this study. A three-stage process of silica particle (380nm) deposition was proposed for the PBG crystal fabrication. The stop band intensity of the produced PBG film was determined using a spectrometer to represent the quality of the film. A process model of the film quality associated with the RH environments at the three stages was constructed using a design of experiment (DOE) and an artificial neural networks (ANN) methods. Results show that the quality of the PBG films was most influenced by the RH environment in the final deposition stage. The optimization approach with the built ANN model was used to estimate the optimal RH-controlled conditions to minimize the fabrication time of required PBG films. Moreover, the predicted optimal operating conditions were verified by experimental tests which results agree with the estimated quality of the PBG films.

Process optimization of gold stud bump manufacturing using artificial neural networks

The optimal operating conditions of a gold stud bumping process were determined using a process optimization scheme for a microelectronic packaging foundry. The schematic procedure of the process optimization is first to evaluate effects of the operating parameters on bump size and height, and shear stress, using a design of experimental method. Several operating parameters, such as compression force (bonding load) and electronic flame off (EFO) current and time, were analyzed to affect the formation of the stud bump significantly in the bumping process. Artificial neural networks (ANN) modeling was adopted to establish the relationship between the operating parameters and the bump properties with the experimental data. Some optimization cases of the bumping process with constraints were evaluated using the optimization scheme.

Fabrication of field-effect transistors based on Fe3+-doped titania by sol–gel methods

TiO2-based field-effect transistors (FETs) were designed and fabricated using nano-TiO2 and Fe3+-doped TiO2 samples prepared by sol–gel methods. Homo-junction characteristics of nano-TiO2/Fe3+-doped TiO2 films, which perform as a semiconductor diode, were analyzed by current–voltage (I–V) data. Two designs of the metal–semiconductor field effect transistors (MESFETs), back and front gate cases, were fabricated and characterized by I–V measurements. The FET devices were evaluated by analyzing the data of source-drain current versus voltage (Ids–Vds) which are controlled by the gate voltage (Vg). In addition, the effects of the junction diode behavior on the transistor were discussed according to the energy band diagrams of TiO2 and Fe3+-doped TiO2 semiconductors.

Design and fabrication of ZnO/TiO2-based thin-film inverter circuits using solution processing techniques

Novel and cost-effective ceramic-based thin-film inverter circuits, based on two layers of TiO2 and ZnO films to construct junction field-effect transistors (FETs), were designed and fabricated by solution coating techniques. The double layers of the sol–gel ZnO and TiO2 films were coated and characterized as a diode according to the current–voltage performance. Two types of FETs, the p-channel (p-FET) and the n-channel (n-FET) devices, were produced using different coating sequences of ZnO and TiO2 layers. Both of the transistor performances were evaluated by analyzing the source–drain current versus voltage (Ids–Vds) data with the control of the gate voltage (Vg). The ZnO/TiO2-based inverter circuits, such as the complementary-FET device, were further fabricated using the integration of the p-FET and the n-FET. The voltage transfer characteristics of the inverters were estimated by the tests of the input voltage (Vin) versus the output voltage (Vout) for the thin-film inverter circuits.

Effects of spherical titania particle electrodes on dye-sensitized solar cells

Effects of spherical titania particles used to fabricate the electrodes of dye-sensitized solar cells (DSSCs) were evaluated from the data analysis of solar simulation systems. Monodispersed spherical titania colloids, particle size between 150 and 300 nm, were uniformly synthesized by sol-gel methods. The prepared titania samples were deposited on substrates to fabricate the electrodes as a component of the solar cell. After annealing, the titania film was immersed in a dye solution and assemblied as a DSSC. Results show that the efficiency of the DSSCs fabricated using the titania particles were higher, although incident photons to photocurrent conversion efficiency (IPCE) value was lower than the one prepared by commercial TiO2 (p25) cases.

Stability evaluation of UV-exposure on multiple dye/nano-TiO2 layers

A device of multiple nano-TiO2 layers was proposed and fabricated to prevent great damage of a dye/nano-TiO2 region in the dye-sensitized solar cells (DSC) from photodegradation. The top of the dye/TiO2 region was designed to be coated with sol-gel nano-TiO2 thin films against UV irradiation to alleviate the photodegradation effect. The sol-gel TiO2 was prepared in a low temperature (75 M) and verified as nano-sized particles and an anatase crystalline structure. The samples of different layers fabricated using different compositions of nano-TiO2 were prepared and exposed for UV-irradiation tests. Results show that the presence of the sol-gel TiO2 films coated on top of the dye/TiO2 region can significantly protect the dye photo-degradation from UV irradiation. This multi-layer device can effectively improve the photo-stability of the dye in a UV-exposure environment