ASU Scholarship Showcase

Zeolitic Imidazolate Frameworks (ZIFs) are one of the potential candidates as highly conducting networks with surface area with a possibility to be used as catalyst support. In the present study, highly active state-of-the-art Pt-NCNTFs catalyst was synthesized by pyrolyzing ZIF-67 along with Pt precursor under flowing Ar-H₂ (90-10 %) gas at 700 °C. XRD analysis indicated the formation of Pt-Co alloy on the surface of the nanostructured catalyst support. The high resolution TEM examination showed the particle size range of 7 to 10 nm. Proton exchange membrane fuel cell performance was evaluated by fabricating membrane electrode assemblies using Nafion-212 electrolyte using H₂/O₂ gases (100 % RH) at various temperatures. The peak power density of 630 mW.cm² was obtained with Pt-NCNTFs cathode catalyst and commercial Pt/C anode catalyst at 70 °C at ambient pressure.

Photosynthesis, a process catalysed by plants, algae and cyanobacteria converts sunlight to energy thus sustaining all higher life on Earth. Two large membrane protein complexes, photosystem I and II (PSI and PSII), act in series to catalyse the light-driven reactions in photosynthesis. PSII catalyses the light-driven water splitting process, which maintains the Earth’s oxygenic atmosphere. In this process, the oxygen-evolving complex (OEC) of PSII cycles through five states, S₀ to S₄, in which four electrons are sequentially extracted from the OEC in four light-driven charge-separation events. Here we describe time resolved experiments on PSII nano/microcrystals from Thermosynechococcus elongatus performed with the recently developed technique of serial femtosecond crystallography. Structures have been determined from PSII in the dark S₁ state and after double laser excitation (putative S₃ state) at 5 and 5.5 Å resolution, respectively. The results provide evidence that PSII undergoes significant conformational changes at the electron acceptor side and at the Mn₄CaO₅ core of the OEC. These include an elongation of the metal cluster, accompanied by changes in the protein environment, which could allow for binding of the second substrate water molecule between the more distant protruding Mn (referred to as the ‘dangler’ Mn) and the Mn₃CaO_x cubane in the S₂ to S₃ transition, as predicted by spectroscopic and computational studies. This work shows the great potential for time-resolved serial femtosecond crystallography for investigation of catalytic processes in biomolecules.

We present results from experiments at the Linac Coherent Light Source (LCLS) demonstrating that serial femtosecond crystallography (SFX) can be performed to high resolution (~2.5 Å) using protein microcrystals deposited on an ultra-thin silicon nitride membrane and embedded in a preservation medium at room temperature. Data can be acquired at a high acquisition rate using x-ray free electron laser sources to overcome radiation damage, while sample consumption is dramatically reduced compared to flowing jet methods. We achieved a peak data acquisition rate of 10 Hz with a hit rate of ~38%, indicating that a complete data set could be acquired in about one 12-hour LCLS shift using the setup described here, or in even less time using hardware optimized for fixed target SFX. This demonstration opens the door to ultra low sample consumption SFX using the technique of diffraction-before-destruction on proteins that exist in only small quantities and/or do not produce the copious quantities of microcrystals required for flowing jet methods.

Myoelectric artificial limbs can significantly advance the state of the art in prosthetics, since they can be used to control mechatronic devices through muscular activity in a way that mimics how the subjects used to activate their muscles before limb loss. However, surveys indicate that dissatisfaction with the functionality of terminal devices underlies the widespread abandonment of prostheses. We believe that one key factor to improve acceptability of prosthetic devices is to attain human likeness of prosthesis movements, a goal which is being pursued by research on social and human–robot interactions. Therefore, to reduce early abandonment of terminal devices, we propose that controllers should be designed so as to ensure effective task accomplishment in a natural fashion. In this work, we have analyzed and compared the performance of three types of myoelectric controller algorithms based on surface electromyography to control an underactuated and multi-degrees of freedom prosthetic hand, the SoftHand Pro.

The goal of the present study was to identify the myoelectric algorithm that best mimics the native hand movements. As a preliminary step, we first quantified the repeatability of the SoftHand Pro finger movements and identified the electromyographic recording sites for able-bodied individuals with the highest signal-to-noise ratio from two pairs of muscles, i.e., flexor digitorum superficialis/extensor digitorum communis, and flexor carpi radialis/extensor carpi ulnaris. Able-bodied volunteers were then asked to execute reach-to-grasp movements, while electromyography signals were recorded from flexor digitorum superficialis/extensor digitorum communis as this was identified as the muscle pair characterized by high signal-to-noise ratio and intuitive control. Subsequently, we tested three myoelectric controllers that mapped electromyography signals to position of the SoftHand Pro. We found that a differential electromyography-to-position mapping ensured the highest coherence with hand movements. Our results represent a first step toward a more effective and intuitive control of myoelectric hand prostheses.

Gas seeps emanating from Yanartaş (Chimera), Turkey, have been documented for thousands of years. Active serpentinization produces hydrogen and a range of carbon gases that may provide fuel for life. Here we report a newly discovered, ephemeral fluid seep emanating from a small gas vent at Yanartaş. Fluids and biofilms were sampled at the source and points downstream. We describe site conditions, and provide microbiological data in the form of enrichment cultures, Scanning electron microscopy (SEM), carbon and nitrogen isotopic composition of solids, and PCR screens of nitrogen cycle genes. Source fluids are pH 11.95, with a Ca:Mg of ~200, and sediments under the ignited gas seep measure 60°C. Collectively, these data suggest the fluid is the product of active serpentinization at depth. Source sediments are primarily calcite and alteration products (chlorite and montmorillonite). Downstream, biofilms are mixed with montmorillonite. SEM shows biofilms distributed homogeneously with carbonates. Organic carbon accounts for 60% of the total carbon at the source, decreasing downstream to <15% as inorganic carbon precipitates. δ¹³C ratios of the organic carbon fraction of solids are depleted (−25 to −28‰) relative to the carbonates (−11 to −20‰). We conclude that heterotrophic processes are dominant throughout the surface ecosystem, and carbon fixation may be key down channel. δ¹⁵N ratios ~3‰, and absence of nifH in extracted DNA suggest that nitrogen fixation is not occurring in sediments. However, the presence of narG and nirS at most locations and in enrichments indicates genomic potential for nitrate and nitrite reduction. This small seep with shallow run-off is likely ephemeral, but abundant preserved microterracettes in the outflow and the surrounding area suggest it has been present for some time. This site and others like it present an opportunity for investigations of preserved deep biosphere signatures, and subsurface-surface interactions.

Introduction: Options currently available to individuals with upper limb loss range from prosthetic hands that can perform many movements, but require more cognitive effort to control, to simpler terminal devices with limited functional abilities. We attempted to address this issue by designing a myoelectric control system to modulate prosthetic hand posture and digit force distribution.

Methods: We recorded surface electromyographic (EMG) signals from five forearm muscles in eight able-bodied subjects while they modulated hand posture and the flexion force distribution of individual fingers. We used a support vector machine (SVM) and a random forest regression (RFR) to map EMG signal features to hand posture and individual digit forces, respectively. After training, subjects performed grasping tasks and hand gestures while a computer program computed and displayed online feedback of all digit forces, in which digits were flexed, and the magnitude of contact forces. We also used a commercially available prosthetic hand, the i-Limb (Touch Bionics), to provide a practical demonstration of the proposed approach’s ability to control hand posture and finger forces.

Results: Subjects could control hand pose and force distribution across the fingers during online testing. Decoding success rates ranged from 60% (index finger pointing) to 83–99% for 2-digit grasp and resting state, respectively. Subjects could also modulate finger force distribution.

Discussion: This work provides a proof of concept for the application of SVM and RFR for online control of hand posture and finger force distribution, respectively. Our approach has potential applications for enabling in-hand manipulation with a prosthetic hand.

The concept of postural synergies of the human hand has been shown to potentially reduce complexity in the neuromuscular control of grasping. By merging this concept with soft robotics approaches, a multi degrees of freedom soft-synergy prosthetic hand [SoftHand-Pro (SHP)] was created. The mechanical innovation of the SHP enables adaptive and robust functional grasps with simple and intuitive myoelectric control from only two surface electromyogram (sEMG) channels. However, the current myoelectric controller has very limited capability for fine control of grasp forces. We addressed this challenge by designing a hybrid-gain myoelectric controller that switches control gains based on the sensorimotor state of the SHP. This controller was tested against a conventional single-gain (SG) controller, as well as against native hand in able-bodied subjects. We used the following tasks to evaluate the performance of grasp force control: (1) pick and place objects with different size, weight, and fragility levels using power or precision grasp and (2) squeezing objects with different stiffness. Sensory feedback of the grasp forces was provided to the user through a non-invasive, mechanotactile haptic feedback device mounted on the upper arm. We demonstrated that the novel hybrid controller enabled superior task completion speed and fine force control over SG controller in object pick-and-place tasks. We also found that the performance of the hybrid controller qualitatively agrees with the performance of native human hands.

Research has shown that construction projects in Saudi Arabia have exhibited poor performance for the past three decades. The traditional risk management practices have been ineffective at helping contractors deliver projects on time and within budget while meeting quality expectations. Studies have identified that client decision making is one of the main causes of risks that occur on projects in Saudi Arabia. This paper proposes a new risk management model that can minimize client decision making, and enable the client to utilize expertise, thereby improving project quality and performance. The model is derived from the Information Measurement Theory (IMT) and Performance Information Procurement System (PIPS), both developed at Arizona State University in the United States (U.S.). The model has been tested over 1800 times in both construction and non-construction projects, showing a decrease in required management by owner by up to 80% and an increase in efficiency up to 40%.

A typical building construction process runs through three main consecutive phases: design, construction and operation. Currently, architects and engineers both engage in the creation of environmental designs that adequately reflect high performance through sustainability and energy efficiency in new buildings. Occupants of buildings have also recently demonstrated a dramatic increase in awareness regarding building operation, energy usage, and indoor air quality. The process of building construction is chronologically located between both the design and the operation phases. However, this phase has not yet been addressed in either understanding contractor behavior or developing innovative sustainable techniques. These two vital aspects have the potential to levy a dramatic impact on enhancing building performance and operational costs.

Repeatedly causing apprehension to the construction industry is a question that posits, “Why is there a gap/delta/inconsistency between the designed EUI, Energy Use Intensity, and the operational EUI”? Building occupants shall not be the only party that bears blame for the delta in energy. It is true, nonetheless, that occupants are part of the reason, but the contractor – as well as the entire construction phase - also remain prime suspects worth investigating. In the present time, research is predominantly focused on occupants (post-occupancy) and designers to educate and control the gap between designed and operational EUI. This research has succeeded in the identification of the construction phase, in conjunction with contractor behavior, as another main factor for initiating this energy gap. Therefore, not only is the coupling of sustainable strategies to the construction drivers crucial to attaining a sustainable project, but also it is integral to analyzing contractor behavior within each of the construction phases that play a vital role in successfully serving sustainability. Various techniques and approaches will assist contractors in amending their method statements to ensure a sustainable project.

This research correlates an existing project to the two proposed sustainable concepts: 1) Identify cost-saving strategies that may have been implemented or avoided during the construction process, and 2) Evaluate the impacts of implementing these strategies on overall performance. The adopted contexts are to partially foster sustainable architecture concepts to the Contractor process, and then proceed to analyze its cost implication on overall project performance. Results of the validation of this approach verify that when contractors embrace a sustainable construction process the overall project will yield various financial savings. A mixed-use project was utilized to validate these concepts, which indicated three outcomes: firstly, a 25% decrease in manpower for tiling while maintaining the same productivity, thus reflecting a saving of $3,500; next, increasing the productivity of concrete activity, which would shorten the duration of the construction by 45 days and reflect a saving of $1.5 million, and last of all, reducing the overhead costs of labor camps by efficiently orienting temporary shelters, which reveals a reduction in cooling and heating that returned a saving of approximately $10,000. This research develops a comprehensive evidence-based study that addresses the above-mentioned gap in the construction phase, which targets to yield a multi-dimensional tool that will allow: 1) integrating critical thinking and decision-making approaches regarding contractor behavior, and 2) adopting innovative sustainable construction methods that reflect reduction in operating costs.

The estimation of energy demand (by power plants) has traditionally relied on historical energy use data for the region(s) that a plant produces for. Regression analysis, artificial neural network and Bayesian theory are the most common approaches for analysing these data. Such data and techniques do not generate reliable results. Consequently, excess energy has to be generated to prevent blackout; causes for energy surge are not easily determined; and potential energy use reduction from energy efficiency solutions is usually not translated into actual energy use reduction. The paper highlights the weaknesses of traditional techniques, and lays out a framework to improve the prediction of energy demand by combining energy use models of equipment, physical systems and buildings, with the proposed data mining algorithms for reverse engineering. The research team first analyses data samples from large complex energy data, and then, presents a set of computationally efficient data mining algorithms for reverse engineering. In order to develop a structural system model for reverse engineering, two focus groups are developed that has direct relation with cause and effect variables. The research findings of this paper includes testing out different sets of reverse engineering algorithms, understand their output patterns and modify algorithms to elevate accuracy of the outputs.