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For the encapsulation of biomolecules in inorganic materials, we have developed a unique enzyme-silicate conjugate material that consists of a self-assembled molecularly thin silicate layer on the surface of each individual enzyme molecule. The enzyme-silicate conjugate materials, called single enzyme caged nanoparticles (SECNs), were synthesized via the silica polymerization on the surface of enzyme molecule after solubilizing each enzyme molecule in hexane by using a tiny amount of surfactant, called “ion-pairing”. SECNs possess near native enzyme activity in aqueous media with minimal substrate diffusional limitations, and are highly stable under the protection of silicate network cage. Due to their nearly molecular size, SECNs can also be adsorbed into mesoporous silica materials to yield robust and easily-recyclable enzymatic systems that can be used in a number of potential biocatalytic applications such as diagnostics, biosensors, biotransformations, biofuel production, bioremediation and CO2 capture.

Protein digestion, using an enzyme called trypsin (TR), is one of the key steps in proteomic analysis. The current technology of protein digestion in proteomic analysis is time-consuming, tedious and not-automated due to the poor stability and autolysis of trypsin. To improve the protein digestion process, trypsin was immobilized and stabilized on polymer nanofibers entrapping superparamagnetic nanoparticles (magnetic nanofibers, NP-NFs). By electrospinning the homogeneous mixture of superparamagnetic nanoparticles (NPs) and polystyrene-poly(styrene-co-maleic anhydride), NPs could be effectively entrapped within polymer nanofibers, generating magnetically-separable nanofibers with high surface area for trypsin immobilization via the approach of enzyme coatings. Trypsin coatings on magnetic nanofibers (EC-TR/NP-NFs; EC-TR), fabricated via simple attachment of crosslinked trypsin molecules onto NP-NFs, were highly stable and could be recycled via facile magnetic separation. EC-TR showed negligible loss of trypsin activity even after incubation in an aqueous buffer under rigorous shaking (200 rpm) for 80 days, while the control samples of covalently-attached trypsin on NP-NFs (CA-TR/NP-NFs; CA-TR) and free trypsin lost more than 90% of their initial activities within 11 and 6 days, respectively. When highly-stable and magnetically-separable EC-TR was employed for the repetitive digestions of enolase under recycled uses for the duration of 50 days and even after treatment with another protease (chymotrypsin) for 32 h, the performance of enolase digestion was successfully maintained. The use of EC-TR for the enolase digestion in the ultra-sonication system resulted in fast (∼10 min) and efficient digestions with reproducible performance under recycled uses.

A control oriented model of the Lean NOx trap (LNT) was developed to determine the timing of NOx regeneration. The LNT model consists of NOx storage and reduction model. Once NOx is stored (NOx storage model), at the right timing NOx should be released and then reduced (NOx reduction model) with reductants on the catalyst active sites, called regeneration. The NOx storage model simulates the degree of stored NOx in the LNT. It is structured by an instantaneous NOx storage efficiency and the NOx storage capacity model. The NOx storge capacity model was modeled to have a Gaussian distribution with a function of exhaust gas temperature. NOx release and reduction reactions for the NOx reduction model were modeled as Arrhenius equations. The parameter identification was optimally performed by the data of the bench flow reactor test results at space velocity 50,000/hr, 80,000/hr, and temperature of 250 - 500°C. The LNT model state, storage fraction indicates the degree of stored NO x in the LNT and thus, the timing of the regeneration can be determined based on it. For practical purpose, this model will be verified more completely by engine test data which simulate the NEDC transient mode.

Automatic swing door for an automotive application is considered. The equation of motion for a driver side swing door is introduced and gravity cancellation control scheme is adapted. The control scheme supposed to cancel the moment due to the tilt of the car. A speed control is suggested for door operation automation but the output of the speed control is not suppose to be precise as for the manufacturing system control. In the frame of the velocity control of the door, feedback linearization was applied for collision detection. The collision detection performance is satisfactory. The estimate of the magnitude of disturbance due to the collision is close to the actual magnitude of disturbance. Simulation study has been performed to gain insight into the system behavior. Also real test on the prototype hardware has been performed for verification purpose.

Trypsin-coated magnetic nanoparticles (EC-TR/NPs), prepared via a simple multilayer random crosslinking of the trypsin molecules onto magnetic nanoparticles, were highly stable and could be easily captured using a magnet after the digestion was complete. EC-TR/NPs showed a negligible loss of trypsin activity after multiple uses and continuous shaking, whereas the conventional immobilization of covalently attached trypsin on NPs resulted in a rapid inactivation under the same conditions due to the denaturation and autolysis of trypsin. A single model protein, a five-protein mixture, and a whole mouse brain proteome were digested at atmospheric pressure and 37°C for 12 h or in combination with pressure cycling technology at room temperature for 1 min. In all cases, EC-TR/NPs performed equally to or better than free trypsin in terms of both the identified peptide/protein number and the digestion reproducibility. In addition, the concomitant use of EC-TR/NPs and pressure cycling technology resulted in very rapid (∼1 min) and efficient digestions with more reproducible digestion results.

SD (Smart Door) is a human friendly power-assisted door system initially targeted for passenger car doors. The Smart Door offers comfort and safety to passengers or/and drivers by supplying additional power. Amount of power supplied by the Smart Door system is depend on the environment where the automotive is situated. It realizes comfort, for example, when the force applied by the passenger to the door is expected to be abnormal, the SD system tries to compensate passenger's effort by supplying additional force. In this study, to enhance the ease of opening and closing the doors of the passenger vehicle, a Smart Door with a power assist mechanism consisting of a motor was developed and analysed. A power assist mechanism mounted within the vehicle’s door is designed and modeled for simulation purpose. The required force necessary to control the designed mechanism during the vehicle’s roll, pitch and the opening angle of the door has been considered. To this end, we propose a power-assisting control strategy called "gravity cancellation". The system is analysed by numerical simulation with the gravity cancellation control algorithm.

The objective of the research is two fold. The first is to design and propose a stable and robust learning control algorithm. The controller is CMAC Learning Controller which consists of a model-based controller, such as LQR or PID, as a reference control and a CMAC. The second objective is to implement a reference control and CMAC at two different sampling rates. Generally, a conventional controller is designed based on a mathematical plant model. However, increasing complexity of the plant and accuracy requirement on mathematical models nearly prohibits the application of the conventional controller design approach. To avoid inherent complexity and unavoidable uncertainty in modeling, biology mimetic methods have been developed. One of such attempts is Cerebellar Model Articulation Computer(CMAC) developed by Albus. CMAC has two main disadvantages. The first disadvantage of CMAC is increasing memory requirement with increasing number of input variables and with increasing accuracy demand. The memory needs can be solved with cheap memories due to recent development of new memory technology. The second disadvantage is a demand for processing powers which could be an obstacle especially when CMAC should be implemented in real-time. To overcome the disadvantages of CMAC, we propose CMAC learning controller with multiple sampling rates. With this approach a conventional controller which is a reference to CMAC at high enough sampling rate but CMAC runs at the processor's unoccupied time. To show efficiency of the proposed method, an inverted pendulum controller is designed and implemented. We also demonstrate it's possibility as an industrial control solution and robustness against a modeling uncertainty.

Subtilisin Carlsberg (SC) was immobilized and stabilized on magnetically-separable mesoporous silica (Mag-MSU-F) in the form of nanoscale enzyme reactors (NERs) based on the ship-in-a-bottle mechanism. Stabilized NERs of SC (NER-SC) were freeze-dried and successfully used for the transesterification of N-acetyl-L-phenylalanine ethyl ester with n-propanol in isooctane. Magnetic separation of Mag-MSU-F facilitated the repeated usages of stable NER-SC. This is the first demonstration for the use of stable and magnetically-separable NERs in an organic solvent, which has the potential for environmentally-friendly synthesis using enzymes in organic solvents.

A magnetically-separable and highly-stable enzyme system was developed by adsorption of enzymes in superparamagnetic hierarchically ordered mesocellular mesoporous silica (M-HMMS) and subsequent enzyme crosslinking. Superparamagnetic nanoparticles were homogeneously incorporated into hierarchically-ordered mesocellular mesoporous silica (HMMS) by the decomposition of a preformed iron propionate complex. The size of the incorporated superparamagnetic nanoparticles was around 5 nm, generating a magnetically separable host with high pore volumes and large pores (M-HMMS). α-chymotrypsin (CT) was adsorbed into M-HMMS with high loading (∼30 wt%) in less than 30 minutes. Glutaraldehyde (GA) treatment of adsorbed CT resulted in nanometer scale crosslinked enzyme aggregates in M-HMMS (CLEA-M). The activity of these CT aggregates in M-HMMS (CLEA-M-CT) was 34 times than that of simply adsorbed CT in M-HMMS, due to an effective prevention of enzyme leaching during washing via a ship-in-a-bottle approach. CLEA-M-CT maintained the initial activity not only under shaking (250 rpm) for 30 days, but also under recycled uses of 35 times. The same approach was employed for the synthesis of CLEA-M of lipase (CLEA-M-LP), and proven to be effective in improving the loading, activity, and stability of enzyme when compared to those of adsorbed LP in M-HMMS.