Browsing by Subject "Microfabrication"

The primary goals of this study were to demonstrate and fully characterize a microscale ionization source (i.e. micro-ion source) and to determine the validity of impact ionization theory for microscale devices and pressures up to 100 mTorr. The field emission properties of carbon nanotubes (CNTs) along with Micro-Electro-Mechanical Systems (MEMS) design processes were used to achieve these goals. Microwave Plasma-enhanced CVD was used to grow vertically aligned Multi-Walled Carbon Nanotubes (MWNTs) on the microscale devices. A 4-dimensional parametric study focusing on CNT growth parameters confirmed that Fe catalyst thickness had a strong effect on MWNT diameter. The MWNT growth rate was seen to be a strong function of the methane-to-ammonia gas ratio during MWNT growth. A high methane-to-ammonia gas ratio was selected for MWNT growth on the MEMS devices in order to minimize growth time and ensure that the thermal budget of those devices was met.

A CNT-enabled microtriode device was fabricated and characterized. A new aspect of this device was the inclusion of a 10 micron-thick silicon dioxide electrical isolation layer. This thick oxide layer enabled anode current saturation and performance improvements such as an increase in dc amplification factor from 27 to 600. The same 3-panel device was also used as an ionization source. Ion currents were measured in the 3-panel micro-ion source for helium, argon, nitrogen and xenon in the 0.1 to 100 mTorr pressure range. A linear increase in ion current was observed for an increase in pressure. However, simulations indicated that the 3-panel design could be modified to improve performance as well as better understand device behavior. Thus, simulations and literature reports on electron impact ionization sources were used to design a new 4-panel micro-ion source. The 4-panel micro-ion source showed an approximate 10-fold performance improvement compared to the 3-panel ion source device. The improvement was attributed to the increased electron current and improved ion collection efficiency of the 4-panel device. Further, the same device was also operated in a 3-panel mode and showed superior performance compared to the original 3-panel device, mainly because of increased ion collection efficiency.

The effect of voltages applied to the different electrodes in the 4-panel micro-ion source on ion source performance was studied to better understand device behavior. The validity of the ion current equation (which was developed for macroscale ion sources operating at low pressures) in the 4-panel micro-ion source was studied. Experimental ion currents were measured for helium, argon and xenon in the 3 to 100 mTorr pressure range. For comparison, theoretical ion currents were calculated using the ion current equation for the 4-panel micro-ion source utilizing values calculated from SIMION simulations and measured electron currents. The measured ion current values in the 3 to 20 mTorr pressure range followed the calculated ion currents quite closely. A significant deviation was observed in the 20-100 mTorr pressure range. The experimental ion current values were used to develop a corrected empirical model for the 4-panel micro-ion source in this high pressure range (i.e., 3 to 100 mTorr). The role of secondary electrons and electron path lengths at higher pressures is discussed.

High density electrode arrays that can record spatially and temporally detailed neural information provide a new horizon for the scientific exploration of the brain. Chief amongst these new tools is micro-electrocorticography (µECoG), which has grown in usage over the past two decades. As µECoG arrays increase in contact number, density, and complexity, the form factors of arrays will also have to change in tandem – particularly the size and spacing (pitch) of electrode contacts on the array. The continued growth of the field of µECoG research and innovation is hampered by a lack of understanding of how fundamental design aspects of the arrays may impact the information obtained from µECoG in different recording bands of interest and animal models. Utilizing thin-film fabrication to create novel experimental arrays and novel analysis techniques, the work in this dissertation provides an understanding of how differences in electrode contact size and spacing can impact neural metric acquisition in four experimentally and clinically relevant frequency bands of local field potential (LFP), high gamma (HGB), spike band power (SBP), and high frequency broadband (HFB). This dissertation provides innovative arrays that allow for experimental variation within a recording session, unlike much of the work previously published comparing contact size and pitch.

This dissertation shows my work of designing, testing, and implementing novel designs of μECoG arrays to explore the questions of how contact size and pitch may impact neural metrics in rodents and non-human primates (NHPs). In Chapter 2, I used a novel 60-channel array with four different contact size diameters in rodents to explore how contact size, impedance, and noise may impact neural metrics we collect in auditory experiments. We determined that contact size may selectively play a role in neural metric information content acquisition, and that the factors of impedance and noise can impact them significantly in higher frequency bands. This work also showed the ability to resolve multi-unit spiking activity from the surface of the brain. In Chapter 3, I show results obtained using a 61-channel array with different contact pitch in rodents, giving clarity to how the spatial sampling of the neural field may be impacted by the pitch of the electrode contacts used. These results suggest the neural field in higher frequency bands show greater changes at shorter field lengths than lower frequency bands. In Chapter 4, I utilized a larger 244-channel array in a NHP with varied contact sizes to explore how contact size may impact information content obtained from NHPs in the motor-related areas of the brain. Chapter 5 concludes the investigation of how design characteristics may impact neural information content by using an array with a local reference electrode contact to explore how local re-referencing can improve the neural metrics obtained.

The results from this dissertation provide a comprehensive understanding to how the information in the neural field may be impacted by the electrode designs chosen. The utilization of novel in-house fabricated arrays provides a method to explore these neuroscience questions rapidly and at low-cost.

For the past several decades, the discoveries, development, and improvement of microscale and nanoscale techniques and tools have been a major momentum driving the rapid technological advances across many areas of modern sciences and engineering, especially in multidisciplinary fields such as nucleic acid research. Owing to the remarkable programmability, long-term stability, and excellent coding capacity, nucleic acids have received much attention as a promising substrate for constructing next-generation data storage and computing systems at the molecular scale. These emerging applications bridge the knowledge from multiple disciplines including computer science, materials science, and biological science. Advances in nucleic acid technologies have also made significant contributions to life sciences and healthcare, leading to innovations that continue to improve disease prevention, diagnosis, and treatment. For example, techniques such as nucleic acid isothermal amplification hold great promises to enable widespread low-cost molecular testing of pathogens and infectious diseases without expensive instrumentation. The rapidly advancing field of nucleic acid research have given rise to a broad range of practical applications, many of which rely on the development and innovations of supporting technologies such as microscale and nanoscale fabrication techniques, which continue to help pave the way for designing and prototyping better and useful tools such as microfluidics and microarrays. Collectively, this dissertation focuses on these several distinct yet interconnected areas of research around nucleic acid technologies and contributes several novel techniques with applications spanning molecular computing, DNA data storage, molecular diagnostics, and benchtop microfabrication.

This dissertation is organized as follows. Chapter 1 presents an overview of recent advances in nucleic-acid-based molecular data storage and computing systems. DNA outperforms most conventional storage media in terms of information retention time, physical density, and volumetric coding capacity. Advances in synthesis and sequencing technologies have enabled implementations of large synthetic DNA storage with impressive storage capacity and reliable data recovery. Several robust DNA storage architectures featuring random access, error correction, and content-rewritability have been constructed with the potential for scalability and cost reduction. This chapter surveys these recent achievements and discusses alternative routes for overcoming the hurdles of engineering practical DNA storage systems. This chapter also reviews recent exciting work on in vivo DNA memory including intracellular recorders constructed by programmable genome editing tools. Besides information storage, DNA could serve as a versatile molecular computing substrate. Several state-of-the-art DNA computing techniques such as strand displacement, localized hybridization chain reactions, and enzymatic reaction networks are introduced. These simple primitives have facilitated rational designs and implementations of in vitro DNA reaction networks that emulate digital/analog circuits, artificial neural networks, or nonlinear dynamic systems. This chapter also highlights in vivo DNA computing modules such as CRISPR logic gates for building scalable genetic circuits in living cells. The chapter concludes with a discussion of applications and challenges of DNA-based data storage and computing and their far-reaching implications in biocomputing, security, and medicine.

Chapter 2 presents the design, modeling, and simulation of a novel molecular data storage architecture that enables highly efficient, scalable, multidimensional data organization and random access in large DNA storage systems. With impressive physical density and molecular-scale coding capacity, DNA is a promising substrate for building long-lasting data archival storage systems. To retrieve data from DNA storage, recent implementations typically rely on large libraries of meticulously designed orthogonal PCR primers, which fundamentally limit the capacity and scalability of practical DNA storage. This work combines nested and semi-nested PCR to enable multidimensional data organization and random access in large DNA storage. Our strategy effectively pushes the limit of DNA storage capacity and dramatically reduces the number of orthogonal primers needed for efficient PCR random access. Our design uses only k*n primers to uniquely address n^k data-encoding oligos. The architecture inherently supports various well-defined PCR random-access patterns that can be tailored to organize and preserve the underlying DNA-encoded data structures and relations in simple database-like formats such as rows, columns, tables, and blocks of data entries. We design in silico PCR experiments of a four-dimensional DNA storage to illustrate the mechanisms of sixteen different random-access patterns each requiring no more than two PCR reactions to selectively amplify a target dataset of various sizes. To better approximate the physical system, we formulate mathematical models based on empirical distributions to analyze the effect of pipetting, PCR bias, and PCR stochasticity on the performance of multidimensional data queries from large DNA storage.

Chapter 3 presents the design, modeling, and simulation of a renewable DNA logic computing scheme. An important achievement in the field of DNA computing has been the development of experimental protocols for evaluation of Boolean logic circuits. These protocols for DNA circuits generally take as inputs single-stranded DNA molecules that encode Boolean values, and via a series of DNA hybridization reactions then release ssDNA strands to indicate Boolean output values. However, most of these DNA circuits protocols are use-once only, and there remains the major challenge of designing DNA circuits to be renewable for use with multiple sets of inputs. Prior proposed schemes to make DNA gates renewable suffered from multiple problems, including waste accumulation, signal restoration, noise tolerance, and limited scalable complexity. In this work, we propose a scalable design and in silico demonstration of photoregulated renewable DNA seesaw logic circuits, which after processing a given set of inputs, can be repeatedly reset to reliably process other distinct inputs. To achieve renewability, specific toeholds in the system are labeled with photoresponsive molecules such as azobenzene to modulate the effective rate constants of toehold-mediated strand displacement (TMSD) reactions. Our proposed design strategy of leveraging the collective effect of TMSD and azobenzene-mediated dehybridization provides new perspectives on achieving synchronized and localized control of DNA hybridizations in complex and scalable reaction networks efficiently and economically. Various devices such as molecular walkers and motors could potentially be engineered reusable, be simulated and subsequently implemented using our simplified design strategy.

Chapter 4 present the design and experimental validation of a rapid, inexpensive, high-performance molecular home test kit for self-administered diagnosis of COVID-19 and other infectious diseases without instrumentation or trained personnel. To curb and monitor the spread of SARS-CoV-2, simple, affordable, accurate home tests are urgently needed for global population-scale surveillance. We report a rapid, low-cost (~2 USD), simple-to-use molecular test kit for self-administered at-home testing with high sensitivity and specificity. A one-pot lyophilization protocol was developed and optimized to preserve all required biochemical reagents of the test in a single microtube, facilitating long-term storage, inexpensive distribution, and simple testing without specialized instrumentation or trained personnel. The entire sample-to-answer workflow takes <60 minutes, including noninvasive sample collection, one-step RNA isolation, reverse-transcription loop-mediated isothermal amplification (RT-LAMP) in a thermos, and finally a direct visual inspection of colorimetric test result. Our test kit remains stable for ≥30 days at typical home-refrigeration temperature (4 °C) and ≥10 days at room temperature (~20 to 22 °C), achieving ≥95% analytical sensitivity and >99% specificity with a reproducible limit of detection down to at least five copies of viral RNA per microliter under both storage conditions. Notably, the lyophilized RT-LAMP assay demonstrated reduced false positives and enhanced tolerance to a wider range of incubation temperatures compared to conventional solution-based RT-LAMP reactions. Validation tests conducted using simulated SARS-CoV-2 infected samples confirmed rapid detection of SARS-CoV-2 virus from both anterior nasal swabs and gingival swabs. Our test successfully detected multiple SARS-CoV-2 variants and can be easily adapted to enable inexpensive near-patient/at-home molecular testing solutions for other pathogens and infectious diseases.

Chapter 5 presents the invention of a rapid, low-cost, benchtop microfabrication method termed UV-micropatterned miniaturization. Shrink lithography is a promising top-down micro/nanofabrication technique capable of miniaturizing patterns/structures to scales much smaller than the initial mold, however, rapid inexpensive fabrication of high-fidelity shrinkable microfeatures remains challenging. This work reports the discovery and characterization of a simple, fast, low-cost method for replicating and miniaturizing intricate micropatterns/structures on commodity heat-shrinkable polymers. Large-area permanent micropatterning on polystyrene and polyolefin shrink film is attained in one step under ambient conditions through brief irradiation by a shortwave UV pencil lamp. After baking briefly in an oven, the film shrinks biaxially and the miniaturized micropatterns emerge with significantly reduced surface area (up to 95%) and enhanced depth profile. The entire UV-micropatterned miniaturization process is highly reproducible and achievable on benchtop under a few minutes without chemicals or sophisticated apparatus. A variety of microgrid patterns are replicated and miniaturized with high yield and resolution on both planar and curved surfaces. Sequential UV exposures enable easy and rapid engineering of sophisticated microtopography with miniaturized, multi-scale, multi-dimensional microstructures. UV-ozone micropatterned polystyrene surfaces are well-suited for lab-on-a-chip analytical applications owing to the inherent biocompatibility and enhanced surface hydrophilicity. Miniaturization of dense, periodic micropatterns may facilitate low-cost prototyping of functional devices/surfaces such as micro-optics/sensors and tunable metamaterials.