ASU Scholarship Showcase

Phase-change materials (PCMs) are of broad interest for thermal storage and management applications. For energy-dense storage with fast thermal charging/discharging rates, a PCM should have a suitable melting temperature, large enthalpy of fusion, and high thermal conductivity. To simultaneously accomplish these traits, we custom design nanocomposites consisting of phase-change Bi nanoparticles embedded in an Ag matrix. We precisely control nanoparticle size, shape, and volume fraction in the composite by separating the nanoparticle synthesis and nanocomposite formation steps. We demonstrate a 50–100% thermal energy density improvement relative to common organic PCMs with equivalent volume fraction. We also tune the melting temperature from 236–252 °C by varying nanoparticle diameter from 8.1–14.9 nm. Importantly, the silver matrix successfully prevents nanoparticle coalescence, and no melting changes are observed during 100 melt–freeze cycles. The nanocomposite’s Ag matrix also leads to very high thermal conductivities. For example, the thermal conductivity of a composite with a 10% volume fraction of 13 nm Bi nanoparticles is 128 ± 23 W/m-K, which is several orders of magnitude higher than typical thermal storage materials. We complement these measurements with calculations using a modified effective medium approximation for nanoscale thermal transport. These calculations predict that the thermal conductivity of composites with 13 nm Bi nanoparticles varies from 142 to 47 W/m-K as the nanoparticle volume fraction changes from 10 to 35%. Larger nanoparticle diameters and/or smaller nanoparticle volume fractions lead to larger thermal conductivities.

It is known that in classical fluids turbulence typically occurs at high Reynolds numbers. But can turbulence occur at low Reynolds numbers? Here we investigate the transition to turbulence in the classic Taylor-Couette system in which the rotating fluids are manufactured ferrofluids with magnetized nanoparticles embedded in liquid carriers. We find that, in the presence of a magnetic field transverse to the symmetry axis of the system, turbulence can occur at Reynolds numbers that are at least one order of magnitude smaller than those in conventional fluids. This is established by extensive computational ferrohydrodynamics through a detailed investigation of transitions in the flow structure, and characterization of behaviors of physical quantities such as the energy, the wave number, and the angular momentum through the bifurcations. A finding is that, as the magnetic field is increased, onset of turbulence can be determined accurately and reliably. Our results imply that experimental investigation of turbulence may be feasible by using ferrofluids. Our study of transition to and evolution of turbulence in the Taylor-Couette ferrofluidic flow system provides insights into the challenging problem of turbulence control.

We have produced stretchable lithium-ion batteries (LIBs) using the concept of kirigami, i.e., a combination of folding and cutting. The designated kirigami patterns have been discovered and implemented to achieve great stretchability (over 150%) to LIBs that are produced by standardized battery manufacturing. It is shown that fracture due to cutting and folding is suppressed by plastic rolling, which provides kirigami LIBs excellent electrochemical and mechanical characteristics. The kirigami LIBs have demonstrated the capability to be integrated and power a smart watch, which may disruptively impact the field of wearable electronics by offering extra physical and functionality design spaces.

A relatively unexplored issue in cybersecurity science and engineering is whether there exist intrinsic patterns of cyberattacks. Conventional wisdom favors absence of such patterns due to the overwhelming complexity of the modern cyberspace. Surprisingly, through a detailed analysis of an extensive data set that records the time-dependent frequencies of attacks over a relatively wide range of consecutive IP addresses, we successfully uncover intrinsic spatiotemporal patterns underlying cyberattacks, where the term “spatio” refers to the IP address space. In particular, we focus on analyzing macroscopic properties of the attack traffic flows and identify two main patterns with distinct spatiotemporal characteristics: deterministic and stochastic. Strikingly, there are very few sets of major attackers committing almost all the attacks, since their attack “fingerprints” and target selection scheme can be unequivocally identified according to the very limited number of unique spatiotemporal characteristics, each of which only exists on a consecutive IP region and differs significantly from the others. We utilize a number of quantitative measures, including the flux-fluctuation law, the Markov state transition probability matrix, and predictability measures, to characterize the attack patterns in a comprehensive manner. A general finding is that the attack patterns possess high degrees of predictability, potentially paving the way to anticipating and, consequently, mitigating or even preventing large-scale cyberattacks using macroscopic approaches.

Supply-demand processes take place on a large variety of real-world networked systems ranging from power grids and the internet to social networking and urban systems. In a modern infrastructure, supply-demand systems are constantly expanding, leading to constant increase in load requirement for resources and consequently, to problems such as low efficiency, resource scarcity, and partial system failures. Under certain conditions global catastrophe on the scale of the whole system can occur through the dynamical process of cascading failures. We investigate optimization and resilience of time-varying supply-demand systems by constructing network models of such systems, where resources are transported from the supplier sites to users through various links. Here by optimization we mean minimization of the maximum load on links, and system resilience can be characterized using the cascading failure size of users who fail to connect with suppliers.

We consider two representative classes of supply schemes: load driven supply and fix fraction supply. Our findings are: (1) optimized systems are more robust since relatively smaller cascading failures occur when triggered by external perturbation to the links; (2) a large fraction of links can be free of load if resources are directed to transport through the shortest paths; (3) redundant links in the performance of the system can help to reroute the traffic but may undesirably transmit and enlarge the failure size of the system; (4) the patterns of cascading failures depend strongly upon the capacity of links; (5) the specific location of the trigger determines the specific route of cascading failure, but has little effect on the final cascading size; (6) system expansion typically reduces the efficiency; and (7) when the locations of the suppliers are optimized over a long expanding period, fewer suppliers are required. These results hold for heterogeneous networks in general, providing insights into designing optimal and resilient complex supply-demand systems that expand constantly in time.

Catalytic nanomaterials play a major role in chemical conversions and energy transformations. Understanding how materials control and regulate surface reactions is a major objective for fundamental research on heterogeneous catalysts. In situ environmental transmission electron microscopy (ETEM) is a powerful technique for revealing the atomic structures of materials at elevated temperatures in the presence of reactive gases. This approach can allow the structure–reactivity relations underlying catalyst functionality to be investigated. Thus far, ETEM has been limited by the absence of in situ measurements of gas-phase catalytic products. To overcome this deficiency, operando TEM techniques are being developed that combine atomic characterization with the simultaneous measurement of catalytic products. This article provides a short review of the current status and major developments in the application of ETEM to gas-phase catalysis over the past 10 years.

The R-specific alcohol dehydrogenase (ADH) from Lactobacillus brevis LB19 (LbADH) was studied with respect to its ability to reduce a series of 3- through 5-carbon 2-alkanones and aldehydes of relevance as biofuel precursors. Although active on all substrates tested, LbADH displays a marked preference for longer chain substrates. Interestingly, however, 2-alkanones were found to impose substrate inhibition towards LbADH, whereas aldehyde substrates rendered no such effect. Inhibition caused by 2-alkanones was furthermore found to intensify with increasing chain length. Despite demonstrating both primary and secondary ADH activities, a preliminary sequence analysis suggests that LbADH remains distinct from other, previously characterized primary-secondary ADHs. In addition to further characterizing the substrate range of this industrially important enzyme, this study suggests that LbADH has the potential to serve as a useful enzyme for the engineering of various novel alcohol biofuel pathways.

Presented in this paper is a bi-directional out-of-plane actuator which combines the merits of the electrostatic repulsive principle and the electrostatic attractive principle. By taking advantage of the electrostatic repulsive mode, the common “pull-in” instability can be lessened to enlarge the displacement, and by applying the electrostatic attractive mode, the out-of-plane displacement is further enlarged. The implications of changing the actuator’s physical dimensions are discussed, along with the two-layer polysilicon surface microfabrication process used to fabricate such an actuator. The static characteristics of the out-of-plane displacement versus the voltage of both modes are tested, and displacements of 1.4 μm and 0.63 μm are obtained at 130 V and 15 V, respectively. Therefore, a total stroke of 2.03 μm is achieved, more than 3 fold that of the electrostatic attractive mode, making this actuator useful in optical Micro-Electro-Mechanical Systems (MEMS) and Radio Frequency (RF) MEMS applications.

This paper aims to contribute to the evolving literature on the new landscape of scholarly journals. It builds on a series of experiences as a journal editor which span the print and digital eras, and focuses on two current activities with new journals. One was designed as a synoptic journal in a broad multidisciplinary field, supported by a commercial publisher; the other a non-revenue journal which aims to showcase the work of undergraduates in the author’s institution. Despite the uniqueness of goals and delivery, some of the experiences—and challenges—have proved remarkably similar.

Recent studies have reported a greater prevalence of spin turns, which are more unstable than step turns, in older adults compared to young adults in laboratory settings. Currently, turning strategies can only be identified through visual observation, either in-person or through video. This paper presents two unique methods and their combination to remotely monitor turning behavior using three uniaxial gyroscopes. Five young adults performed 90° turns at slow, normal, and fast walking speeds around a variety of obstacles while instrumented with three IMUs (attached on the trunk, left and right shank). Raw data from 360 trials were analyzed. Compared to visual classification, the two IMU methods’ sensitivity/specificity to detecting spin turns were 76.1%/76.7% and 76.1%/84.4%, respectively. When the two methods were combined, the IMU had an overall 86.8% sensitivity and 92.2% specificity, with 89.4%/100% sensitivity/specificity at slow speeds. This combined method can be implemented into wireless fall prevention systems and used to identify increased use of spin turns. This method allows for longitudinal monitoring of turning strategies and allows researchers to test for potential associations between the frequency of spin turns and clinically relevant outcomes (e.g., falls) in non-laboratory settings.