Advanced Nanostructured Electro-Catalysts for Electricity Generation and Biorenewable Alcohol Conversion

In my Ph.D research, a wet chemistry-based organic solution phase reduction method was developed, and was successfully applied in the preparation of a series of advanced electro-catalysts, including 0-dimensional (0-D) Pt, Pd, Au, and Pd-Ni nanoparticles (NPs), 1-D Pt-Fe nanowires (NWs) and 2-D Pd-Fe nanoleaves (NLs), with controlled size, shape, and morphology. These nanostructured catalysts have demonstrated unique electro-catalytic functions towards electricity production and biorenewable alcohol conversion. The molecular oxygen reduction reaction (ORR) is a long-standing scientific issue for fuel cells due to its sluggish kinetics and the poor catalyst durability. The activity and durability of an electro-catalyst is strongly related with its composition and structure. Based on this point, Pt-Fe NWs with a diameter of 2 - 3 nm were accurately prepared. They have demonstrated a high durability in sulfuric acid due to its 1-D structure, as well as a high ORR activity attributed to its tuned electronic structure. By substituting Pt with Pd using a similar synthesis route, Pd-Fe NLs were prepared and demonstrated a higher ORR activity than Pt and Pd NPs catalysts in the alkaline electrolyte. Recently, biomass-derived alcohols have attracted enormous attention as promising fuels (to replace H2) for low-temperature fuel cells. From this point of view, Pd-Ni NPs were prepared and demonstrated a high electro-catalytic activity towards ethanol oxidation. Comparing to ethanol, the biodiesel waste glycerol is more promising due to its low price and high reactivity. Glycerol (and crude glycerol) was successfully applied as the fuel in an Au-anode anion-exchange membrane fuel cell (AEMFC). By replacing Au with a more active Pt catalyst, simultaneous generation of both high power-density electricity and value-added chemicals (glycerate, tartronate, and mesoxalate) from glycerol was achieved in an AEMFC. To investigate the production of valuable chemicals from glycerol electro-oxidation, two anion-exchange membrane electro-catalytic reactors were designed. The research shows that the electro-oxidation product distribution is strongly dependent on the anode applied potential. Reaction pathways for the electro-oxidation of glycerol on Au/C catalyst have been elucidated: continuous oxidation of OH groups (to produce tartronate and mesoxalate) is predominant at lower potentials, while C-C cleavage (to produce glycolate) is the dominant reaction path at higher potentials.

Long-term pallidal deep brain stimulation in patients with advanced Parkinson disease: 1-year follow-up study

OBJECT: The goal of this study was to investigate the efficacy of long-term deep brain stimulation (DBS) of the posteroventral lateral globus pallidus internus (GPi) accomplished using a single-contact monopolar electrode in patients with advanced Parkinson disease (PD). METHODS: Sixteen patients suffering from severe PD and levodopa-induced side effects such as dyskinesias and on-off fluctuations were enrolled in a prospective study protocol. There were six women and 10 men and their mean age at surgery was 65 years. All patients underwent implantation of a monopolar electrode in the posteroventral lateral GPi. Initially, nine patients received unilateral stimulation. Three of these patients underwent contralateral surgery at a later time. Ten patients received bilateral stimulation (contemporaneous bilateral surgery was performed in seven patients and staged bilateral surgery in the three patients who had received unilateral stimulation initially). Formal assessments were performed during both off-medication and on-medication (levodopa) periods preoperatively, and at 3 and 12 months postoperatively. There were no serious complications related to surgery or to DBS. Two transient adverse events occurred: in one patient a small pallidal hematoma developed, resulting in a prolonged micropallidotomy effect, and in another patient a subcutaneous hemorrhage occurred at the site of the pacemaker. In patients who received unilateral DBS, the Unified Parkinson's Disease Rating Scale activities of daily living (ADL) score during the off-levodopa period decreased from 30.8 at baseline to 20.4 at 3 months (34% improvement) and 20.6 at 12 months (33% improvement) postoperatively. The motor score during the off period improved from 57.2 at baseline to 35.2 at 3 months (38% improvement) and 35.3 at 12 months (38% improvement) postoperatively. Bilateral DBS resulted in a reduction in the ADL score during the off period from 34.9 at baseline to 22.3 at 3 months (36% improvement) and 22.9 at 12 months (34% improvement). The motor score for the off period changed from 63.4 at baseline to 40.3 at 3 months (36% improvement) and 37.5 at 12 months (41% improvement). In addition, there were significant improvements in patients' symptoms during the on period and in on-off motor fluctuations. CONCLUSIONS: Pallidal DBS accomplished using a monopolar electrode is a safe and effective procedure for treatment of advanced PD. Compared with pallidotomy, the advantages of pallidal DBS lie in its reversibility and the option to perform bilateral surgery in one session. Comparative studies in which DBS is applied to other targets are needed.

MODEL UPDATING AND STRUCTURAL HEALTH MONITORING OF HORIZONTAL AXIS WIND TURBINES VIA ADVANCED SPINNING FINITE ELEMENTS AND STOCHASTIC SUBSPACE IDENTIFICATION METHODS

Wind energy has been one of the most growing sectors of the nation’s renewable energy portfolio for the past decade, and the same tendency is being projected for the upcoming years given the aggressive governmental policies for the reduction of fossil fuel dependency. Great technological expectation and outstanding commercial penetration has shown the so called Horizontal Axis Wind Turbines (HAWT) technologies. Given its great acceptance, size evolution of wind turbines over time has increased exponentially. However, safety and economical concerns have emerged as a result of the newly design tendencies for massive scale wind turbine structures presenting high slenderness ratios and complex shapes, typically located in remote areas (e.g. offshore wind farms). In this regard, safety operation requires not only having first-hand information regarding actual structural dynamic conditions under aerodynamic action, but also a deep understanding of the environmental factors in which these multibody rotating structures operate. Given the cyclo-stochastic patterns of the wind loading exerting pressure on a HAWT, a probabilistic framework is appropriate to characterize the risk of failure in terms of resistance and serviceability conditions, at any given time. Furthermore, sources of uncertainty such as material imperfections, buffeting and flutter, aeroelastic damping, gyroscopic effects, turbulence, among others, have pleaded for the use of a more sophisticated mathematical framework that could properly handle all these sources of indetermination. The attainable modeling complexity that arises as a result of these characterizations demands a data-driven experimental validation methodology to calibrate and corroborate the model. For this aim, System Identification (SI) techniques offer a spectrum of well-established numerical methods appropriated for stationary, deterministic, and data-driven numerical schemes, capable of predicting actual dynamic states (eigenrealizations) of traditional time-invariant dynamic systems. As a consequence, it is proposed a modified data-driven SI metric based on the so called Subspace Realization Theory, now adapted for stochastic non-stationary and timevarying systems, as is the case of HAWT’s complex aerodynamics. Simultaneously, this investigation explores the characterization of the turbine loading and response envelopes for critical failure modes of the structural components the wind turbine is made of. In the long run, both aerodynamic framework (theoretical model) and system identification (experimental model) will be merged in a numerical engine formulated as a search algorithm for model updating, also known as Adaptive Simulated Annealing (ASA) process. This iterative engine is based on a set of function minimizations computed by a metric called Modal Assurance Criterion (MAC). In summary, the Thesis is composed of four major parts: (1) development of an analytical aerodynamic framework that predicts interacted wind-structure stochastic loads on wind turbine components; (2) development of a novel tapered-swept-corved Spinning Finite Element (SFE) that includes dampedgyroscopic effects and axial-flexural-torsional coupling; (3) a novel data-driven structural health monitoring (SHM) algorithm via stochastic subspace identification methods; and (4) a numerical search (optimization) engine based on ASA and MAC capable of updating the SFE aerodynamic model.