Mid-infrared (MIR) spectroscopy has been recognized as an important analytical technique, and is widely applied for qualitative and quantitative analysis of materials with an increasing interest in addressing complex organic or biologic constituents. In the presented thesis, (a) the fundamental principles for IR spectroscopic applications via in vivo catheters in combination with multivariate data analysis technique were developed, and (b) the combination with a second analytical technique ¨C scanning electrochemical microscopy (SECM) - for enhancing the information obtained at complex or frequently changing matrices was demonstrated. The first part of this thesis focused on the combination of different MIR measurment techniques with specific focus on evanescent field absorption spectroscopy along with multivariate data analysis methods, for the discrimination of atherosclerotic and normal rabbit aorta tissues. Atherosclerotic and normal rabbit aorta tissues are characterized by marked differences in chemical composition governed by their water, lipid, and protein content. Strongly overlapping infrared absorption features of the different constituents and the complexity of the tissue matrix render the direct evaluation of molecular spectroscopic characteristics obtained from IR measurements challenging for classification. We have successfully applied multivariate data analysis and classification techniques based on principal component analysis (PCA), partial least squares regression (PLS), and linear discriminant analysis (LDA) to IR spectroscopic data obtained by infrared attenuated total reflectance (IR-ATR) measurements, reflection IR microscopy, and a recently developed IR-ATR catheter prototype for future in vivo diagnostic applications. Training and test data were collected ex vivo at atherosclerotic and normal rabbit aorta samples. The successful classification results at atherosclerotic and normal aorta samples utilizing the developed data evaluation routines reveals the potential of IR spectroscopy combined with multivariate classification strategies for in vitro, and ¨C in future - in vivo applications. The second part of this thesis aimed at the development of a novel multifunctional analytical platform by combining SECM with single-bounce IR-ATR spectroscopy for in situ studies of electrochemically active or electrochemically induced processes at the IR waveguide surface via simultaneous evanescent field absorption spectroscopy. The utility of the developed SECM-IR-ATR platform was demonstrated by spectroscopically monitoring microstructured polymer depositions induced via feedback mode SECM experiments using a 25μm Pt disk ultramicroelectrode (UME). The surface of a ZnSe ATR crystal was coated with a thin layer of 2,5-di-(2-thienyl)-pyrrole (SNS), which was then polymerized in a Ru(bpy) ₃ ² ⁺-mediated feedback mode SECM experiment. The polymerization reaction was simultaneously spectroscopically monitored by recording the absorption intensity changes of specific IR bands characteristic for SNS, thereby providing information on the polymerization progress, mechanism, and level of surface modification. Furthermore, a novel current-independent approach mechanism for positioning the UME in aqueous electrolyte solution was demonstrated by monitoring IR absorption changes of borosilicate glass (BSG) shielding the UME, and of water within the penetration depth of the evanescent field.

Weak optical signals have to be measured in different fields of sciences including chemistry and biology. For example, very low levels of fluorescence emission should be detected from the spots on a DNA microarray that correspond to weakly expressed genes. High sensitivity charge-coupled devices (CCDs) are used in these applications. CCDs require special fabrication and are difficult to integrate with other circuits. CMOS is the technology used for fabrication of CPUs and other widely used digital components. CMOS is not optimized for light detection. CMOS circuits are however cheap, low power and can integrate several components. Active pixel sensor (APS) is the most common pixel structure for CMOS photodetector arrays. In this work we provide an accurate analysis of the APS signal using new models for the capacitance of the photodiode. We also provide a complete noise analysis of the pixel to calculate the SNR of the pixel and provide optimum operation points. We propose a new mode of operation for APS that can achieve at least l 0 dB higher SNR, than conventional APS, at light levels of less than 1 μW/cm^2. We fabricated several APS pixels in CMOS 0.18 μm technology and measured them to confirm the proposed analyzes. There are applications like fluorescence lifetime imaging that require both sensitivity and fast response. Photomultiplier tubes (PMTs) are commonly used in these applications to detect single photons in pico- to nano-seconds regime. PMTs are bulky and require high voltage levels. Avalanche photodiodes (APDs) are the semiconductor equivalent of PMTs. We have fabricated different APDs along with different peripheral circuitries in CMOS 0.18 μm technology. Our APDs have a 5.5 percent peak probability of detection of a photon at an excess bias of 2 V, and a 30 ns dead time, which is less than the previously reported results. The low price of CMOS makes modem diagnosis devices more available. The low power of CMOS leads to battery-driven hand-held imaging solutions, and its high integration leads to miniaturized imaging and diagnosis systems. A low-light-level CMOS imager paves the way for the future generation of biomedical diagnosis solutions. / Thesis / Doctor of Philosophy (PhD)

Nanoparticles are used in various applications like medical diagnostics, drug delivery, energy technology, electronics, catalysis etc. Although particles of such small dimensions can be synthesized through various methods, the liquid phase synthesis methods stands out for their simplicity. Typically, these methods involve reaction of precursors to form solute. At high concentration of solute, nucleation commences and nuclei are formed. These nuclei grow in size by assimilating solute from the bulk. Stabilizers or capping agents compete with solute for adsorption on the surface of a growing particle. Two partially protected particles can form bigger particle by coagulation. Uncontrolled turbulent flow field in laboratory scale reactors combined with all the above quite fast and poorly understood steps often lead to poorly controlled synthesis of particles. In many a systems, it also leads to very poor reproducibility. Any attempt to synthesis nanoparticles at engineering scale, with good control on mean size and polydispersity, requires quantitative understanding of the synthesis process. It can then be combined with description of other transport processes in reactors to optimize synthesis protocols. Two main factors hinder progress in this direction: complex and often poorly understood chemistry, and inefficient tools to simulate particle synthesis. In the first part of the thesis, a quantitative model is developed for tannic acid method of synthesis of gold nanoparticles. It showcases the approach used to model a system with poorly understood chemistry and which defies an understanding through the widely used homogeneous nucleation based mechanism for particle synthesis. An organizer based mechanism in which tannic acid brings together nucleating species to facilitate nucleation is invoked. Simple reaction network based models however fail to explain the experimental findings. The underlying chemistry is explored to develop a comprehensive reaction network. This network is used as a guide to seek pathways which can mimic burst of nucleation, a characteristic of homogeneous nucleation based mechanism, through self-limiting nucleation, and various other features present in the experimental data. After successful prediction of all the features of the experimental data through this network, a minimal organizer based mechanism which leads to self-limiting nucleation is developed. The minimal organizer model offers itself as a competing and alternative mechanism to explain nanoparticle synthesis. A few new predictions made by the new model are verified by others in our group. Monte-Carlo (MC) simulations are used as a powerful tool to simulate stochastic processes. Their application to nanoparticle synthesis is limited by three problems: (i) zero initial rate of stochastic processes which leads to infinite time step at the beginning of the simulation, (ii) sensitively time dependent rate of stochastic processes, and (iii) computation intensive simulations. We propose a new approach to carry out MC simulations. It makes use of simulation results obtained with systems of extremely small sizes. These system size dependent predictions, obtained at substantially reduced computational cost are used to construct results for system of infinite size. The approach is based on a new power law scaling that we have found in this work. An efficient implementation of MC simulation for time dependent rate processes is also developed. In this method, an additional variable is introduced for inter-event evolution. It increases the number of differential equation by one, but significantly reduces the computational effort required to estimate the interval of quiescence for time dependent rate processes. All the above ideas are combined in the new approach to simulate complete size distribution for simultaneous nucleation and growth of nanoparticles for a system of infinite size from erroneous simulations carried out with three extremely small size systems. A new framework for solving multidimensional population balance equations (PBEs) which routinely arise in modeling of nanoparticle synthesis is also developed. The new framework advances the concept of minimal internal consistency of discretization. It suggests that an n dimensional PBE is a statement of evolution of population of particles while accounting for how n internal attributes of particles change in particulate events. Thus, a minimum of n + 1 attributes of particles, instead of 2n attributes used hitherto, need to be represented perfectly in discrete representation. This is termed as the concept of minimum internal consistency of discretization in this work. The elements used for discretization should therefore be triangles for 2-d, tetrahedrons for 3-d, and an object with n + 1 vertices in n-d space for the solution of a n-d PBE. The results presented for the solutions for 2-d and 3-d PBEs show the superiority of this framework over the earlier framework. The present work also shows that directionality of elements plays a critical role in the solution of multi-dimensional PBEs. A mere change in connectivity of pivots in space, which changes their directionality, is shown to influence numerical results. This work led to new radial discretization of space, which has been followed up by others in the group and demonstrated to be quite powerful. A physical model is developed to understand digestive ripening of nanoparticles, a technique which is in extensive use in the literature to improve monodispersity of nanoparticles. The physical model is based on critical analysis of the large body of experimental findings available in the literature on several variations of this technique. The physical model is the first one to consistently and qualitatively explain all the reported experimental findings.

<p>Noble metal nanostructures display collective oscillation of the surface conduction electrons upon light irradiation as a form of localized surface plasmon resonance (LSPR) properties. Size, shape and the refractive index of surrounding environment are the key features that controls the LSPR properties. Surface passivating ligands have the ability to modify the charge density of nanostructures to allow resonant wavelength to match that of the incident light, a phenomenon called “plasmoelectric effect,”. According to the drude model Red and blue shifts of LSPR peak of nanostructures are observed in the event of reducing and increasing charge density, respectively. However, herein we report unusual LSPR properties of gold triangular nanoprisms (Au TNPs) upon functionalization with para-substituted thiophenols (X-Ph-SH, X = -NH₂, -OCH₃, -CH₃, -H, -Cl, -CF₃, and -NO₂). Accordingly, we hypothesized that an appropriate energy level alignment between the Au Fermi energy and the HOMO or LUMO of ligands allows delocalization of surface plasmon excitation at the hybrid inorganic-organic interface, and thus provides a thermodynamically driven plasmoelectric effect. We further validated our hypothesis by calculating the HOMO and LUMO levels and also work function changes of Au TNPs upon functionalization with para substituted thiol. We further utilized our unique finding to design ultrasensitive plasmonic substrate for biosensing of cancer microRNA in bladder cancer and owe to unpresidential sensitivity of the developed Au TNPs based LSPR sensor, for the first time we have been utilized to analysis the tumor suppressor microRNA for more accurate diagnosis of BC. Additionally, we have been advancing our sensing platform to mitigate the false positive and negative responses of the sensing platform using surface enhanced fluorescence technique. This noninvasive, highly sensitive, highly specific, also does not have false positives technique provide strong key to detect cancer at very early stage, hence increase the cancer survival rate. Moreover, the electromagnetic field enhancement of Surface-Enhanced Raman Scattering (SERS) and other related surface-enhanced spectroscopic processes resulted from the LSPR property. This dissertation describes the design and development of entirely new SERS nanosensors using flexible SERS substrate based on unique LSPR property of Au TNPs and developed sensors shows excellent SERS activity (enhancement factor = ~6.0 x 106) and limit of detection (as low as 56 parts-per-quadrillions) with high selectivity by chemometric analyses among three commonly used explosives (TNT, RDX, and PETN). Further we achieved the programable self-assembly of Au TNPs using molecular tailoring to form a 3D supper lattice array based on the substrate effect. Here we achieved the highest reported sensitivity for potent drug analysis, including opioids and synthetic cannabinoids from human plasma obtained from the emergency room. This exquisite sensitivity is mainly due to the two reasons, including molecular resonance of the adsorbate molecules and the plasmonic coupling among the nanoparticles. Altogether we are highly optimistic that our research will not only increase the patient survival rate through early detection of cancer but also help to battle the “war against drugs” that together is expected to enhance the quality of human life. </p> <p> </p>