The role of trace Ag in the synthesis of Au nanorods.

One of the more useful syntheses of single crystalline, uniform Au nanorods from Au spherical seeds relies on the addition of trace Ag ions, yet the role that Ag+ plays has remained both elusive and controversial, due in part to lack of knowledge of how the Ag distribution in the nanorod evolves over time. In this work, we fill in this knowledge gap by correlating the spatial distribution of Ag within Au nanorods with nanorod anisotropic growth through time-course X-ray absorption spectroscopy (XAFS)-derived atomic-level elemental coordination paired with electron microscopy for nanoscale morphological analysis. Using this method, a plausible pathway for the conversion of spherical seeds into Au nanorods is proposed. Evidence shows that the nanorod anisotropic growth is directly related to the Ag surface coverage. Anisotropy is induced early in the reaction when Ag first deposits onto the nanoparticle surface, but growth occurs more isotropically as the reaction progresses and Ag diffuses into the nanorod bulk. The results of this investigation and methods employed should be extendable to many anisotropic nanoparticle syntheses that make use of trace elemental species as shape-control additives.

A map of the inorganic ternary metal nitrides.

Exploratory synthesis in new chemical spaces is the essence of solid-state chemistry. However, uncharted chemical spaces can be difficult to navigate, especially when materials synthesis is challenging. Nitrides represent one such space, where stringent synthesis constraints have limited the exploration of this important class of functional materials. Here, we employ a suite of computational materials discovery and informatics tools to construct a large stability map of the inorganic ternary metal nitrides. Our map clusters the ternary nitrides into chemical families with distinct stability and metastability, and highlights hundreds of promising new ternary nitride spaces for experimental investigation-from which we experimentally realized seven new Zn- and Mg-based ternary nitrides. By extracting the mixed metallicity, ionicity and covalency of solid-state bonding from the density functional theory (DFT)-computed electron density, we reveal the complex interplay between chemistry, composition and electronic structure in governing large-scale stability trends in ternary nitride materials.

Understanding crystallization pathways leading to manganese oxide polymorph formation.

Hydrothermal synthesis is challenging in metal oxide systems with diverse polymorphism, as reaction products are often sensitive to subtle variations in synthesis parameters. This sensitivity is rooted in the non-equilibrium nature of low-temperature crystallization, where competition between different metastable phases can lead to complex multistage crystallization pathways. Here, we propose an ab initio framework to predict how particle size and solution composition influence polymorph stability during nucleation and growth. We validate this framework using in situ X-ray scattering, by monitoring how the hydrothermal synthesis of MnO2 proceeds through different crystallization pathways under varying solution potassium ion concentrations ([K+] = 0, 0.2, and 0.33 M). We find that our computed size-dependent phase diagrams qualitatively capture which metastable polymorphs appear, the order of their appearance, and their relative lifetimes. Our combined computational and experimental approach offers a rational and systematic paradigm for the aqueous synthesis of target metal oxides.

Complex surface structure of (110) terminated strontium titanate nanododecahedra.

The surface structure of (110) faceted strontium titanate nanoparticles synthesized via solvothermal method has been resolved using high-resolution electron microscopy (HREM). We demonstrate that the surface is a titania-rich structure containing tetrahedrally coordinated TiO4 units similar to the family of (n × 1) reconstructions observed on (110) surfaces of bulk crystalline strontium titanate. When compared with prior results for (001) terminated strontium titanate single crystals made with traditional transmission electron microscopy (TEM) sample preparation techniques, the results demonstrate that many models for oxide nanoparticles need to be revisited. This work serves as a reminder that attention must be paid to the surface of nanoparticles. Even with a simple perovskite as the starting point the end result can be very complex. As more materials are synthesized on the nanoscale, this will become increasingly important to take into consideration.

Design and control of a bio-inspired soft wearable robotic device for ankle-foot rehabilitation.

We describe the design and control of a wearable robotic device powered by pneumatic artificial muscle actuators for use in ankle-foot rehabilitation. The design is inspired by the biological musculoskeletal system of the human foot and lower leg, mimicking the morphology and the functionality of the biological muscle-tendon-ligament structure. A key feature of the device is its soft structure that provides active assistance without restricting natural degrees of freedom at the ankle joint. Four pneumatic artificial muscles assist dorsiflexion and plantarflexion as well as inversion and eversion. The prototype is also equipped with various embedded sensors for gait pattern analysis. For the subject tested, the prototype is capable of generating an ankle range of motion of 27° (14° dorsiflexion and 13° plantarflexion). The controllability of the system is experimentally demonstrated using a linear time-invariant (LTI) controller. The controller is found using an identified LTI model of the system, resulting from the interaction of the soft orthotic device with a human leg, and model-based classical control design techniques. The suitability of the proposed control strategy is demonstrated with several angle-reference following experiments.

A web-based system for home monitoring of patients with Parkinson's disease using wearable sensors.

This letter introduces MercuryLive, a platform to enable home monitoring of patients with Parkinson's disease (PD) using wearable sensors. MercuryLive contains three tiers: a resource-aware data collection engine that relies upon wearable sensors, web services for live streaming and storage of sensor data, and a web-based graphical user interface client with video conferencing capability. Besides, the platform has the capability of analyzing sensor (i.e., accelerometer) data to reliably estimate clinical scores capturing the severity of tremor, bradykinesia, and dyskinesia. Testing results showed an average data latency of less than 400 ms and video latency of about 200 ms with video frame rate of about 13 frames/s when 800 kb/s of bandwidth were available and we used a 40% video compression, and data feature upload requiring 1 min of extra time following a 10 min interactive session. These results indicate that the proposed platform is suitable to monitor patients with PD to facilitate the titration of medications in the late stages of the disease.

Longitudinal monitoring of patients with Parkinson's disease via wearable sensor technology in the home setting.

Objective longitudinal monitoring of symptoms related motor fluctuations can provide valuable information for the clinical management of patients with Parkinson's disease. Current methods for long-term monitoring of motor fluctuations, such as patient diaries, are ineffective due to their time consuming and subjective nature. Researchers have shown that wearable sensors such as accelerometers can be used to gather objective information about a patient's motor symptoms. In this paper, we present preliminary results from our analysis on wearable sensor data gathered during longitudinal monitoring of 5 patients with PD. Our results indicate that it is possible to track longitudinal changes in motor symptoms by training a regression model based on Random Forests.

Development of a platform to combine sensor networks and home robots to improve fall detection in the home environment.

Over the last decade, significant progress has been made in the development of wearable sensor systems for continuous health monitoring in the home and community settings. One of the main areas of application for these wearable sensor systems is in detecting emergency events such as falls. Wearable sensors like accelerometers are increasingly being used to monitor daily activities of individuals at a risk of falls, detect emergency events and send alerts to caregivers. However, such systems tend to have a high rate of false alarms, which leads to low compliance levels. Home robots can enable caregivers with the ability to quickly make an assessment and intervene if an emergency event is detected. This can provide an additional layer for detecting false positives, which can lead to improve compliance. In this paper, we present preliminary work on the development of a fall detection system based on a combination sensor networks and home robots. The sensor network architecture comprises of body worn sensors and ambient sensors distributed in the environment. We present the software architecture and conceptual design home robotic platform. We also perform preliminary characterization of the sensor network in terms of latencies and battery lifetime.

Home monitoring of patients with Parkinson's disease via wearable technology and a web-based application.

Objective long-term health monitoring can improve the clinical management of several medical conditions ranging from cardiopulmonary diseases to motor disorders. In this paper, we present our work toward the development of a home-monitoring system. The system is currently used to monitor patients with Parkinson's disease who experience severe motor fluctuations. Monitoring is achieved using wireless wearable sensors whose data are relayed to a remote clinical site via a web-based application. The work herein presented shows that wearable sensors combined with a web-based application provide reliable quantitative information that can be used for clinical decision making.