Anthony O'Neill

Bio: Anthony O'Neill is an academic researcher from Newcastle University. The author has contributed to research in topics: Monocrystalline silicon & Machining. The author has an hindex of 2, co-authored 5 publications receiving 26 citations.

The Neural Engine: A Reprogrammable Low Power Platform for Closed-Loop Optogenetics

Abstract: Brain-machine Interfaces (BMI) hold great potential for treating neurological disorders such as epilepsy. Technological progress is allowing for a shift from open-loop, pacemaker-class, intervention towards fully closed-loop neural control systems. Low power programmable processing systems are therefore required which can operate within the thermal window of 2° C for medical implants and maintain long battery life. In this work, we have developed a low power neural engine with an optimized set of algorithms which can operate under a power cycling domain. We have integrated our system with a custom-designed brain implant chip and demonstrated the operational applicability to the closed-loop modulating neural activities in in-vitro and in-vivo brain tissues: the local field potentials can be modulated at required central frequency ranges. Also, both a freely-moving non-human primate (24-hour) and a rodent (1-hour) in-vivo experiments were performed to show system reliable recording performance. The overall system consumes only 2.93 mA during operation with a biological recording frequency 50 Hz sampling rate (the lifespan is approximately 56 hours). A library of algorithms has been implemented in terms of detection, suppression and optical intervention to allow for exploratory applications in different neurological disorders. Thermal experiments demonstrated that operation creates minimal heating as well as battery performance exceeding 24 hours on a freely moving rodent. Therefore, this technology shows great capabilities for both neuroscience in-vitro/in-vivo applications and medical implantable processing units.

W:Ti Flexible Transversal Electrode Array for Peripheral Nerve Stimulation: A Feasibility Study

Abstract: The development of hardware for neural interfacing remains a technical challenge. We introduce a flexible, transversal intraneural tungsten:titanium electrode array for acute studies. We characterize the electrochemical properties of this new combination of tungsten and titanium using cyclic voltammetry and electrochemical impedance spectroscopy. With an in-vivo rodent study, we show that the stimulation of peripheral nerves with this electrode array is possible and that more than half of the electrode contacts can yield a stimulation selectivity index of 0.75 or higher at low stimulation currents. This feasibility study paves the way for the development of future cost-effective and easy-to-fabricate neural interfacing electrodes for acute settings, which ultimately can inform the development of technologies that enable bi-directional communication with the human nervous system.

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

A review on micro-milling: recent advances and future trends

Abstract: Recently, mechanical micro-milling is one of the most promising micro-manufacturing processes for productive and accurate complex-feature generation in various materials including metals, ceramics, polymers and composites. The micro-milling technology is widely adapted already in many high-tech industrial sectors; however, its reliability and predictability require further developments. In this paper, micro-milling related recent results and developments are reviewed and discussed including micro-chip removal and micro-burr formation mechanisms, cutting forces, cutting temperature, vibrations, surface roughness, cutting fluids, workpiece materials, process monitoring, micro-tools and coatings, and process-modelling. Finally, possible future trends and research directions are highlighted in the micro-milling and micro-machining areas.

In Situ Investigation of Chemomechanical Effects in Thiophosphate Solid Electrolytes

Abstract: Summary Solid-state batteries can suffer from catastrophic failure at high current densities due to solid electrolyte fracture, interface decomposition, or lithium filament growth. Failure is linked to chemomechanical material transformations that can manifest during electrochemical cycling. We systematically investigate how solid electrolyte microstructure and interfacial decomposition (e.g., interphase) affect failure mechanisms in lithium thiophosphates (Li3PS4, LPS) electrolytes. Kinetically metastable interphases are engineered with iodine doping, and microstructural control is achieved using milling and annealing processing techniques. In situ transmission electron microscopy reveals iodine diffusion to the interphase, and upon electrochemical cycling, pores are formed in the interphase region. In situ synchrotron tomography reveals that interphase pore formation drives edge fracture events, which are the origin of through-plane fracture failure. Fractures in thiophosphate electrolytes actively grow toward regions of higher porosity and are affected by heterogeneity in microstructure (e.g., porosity factor). This work provides fundamental design guidelines for high-performance solid-state batteries.

MEAM potential for Al, Si, Mg, Cu, and Fe alloys

Abstract: A set of modified embedded atom method (MEAM) potentials for the interactions between Al, Si, Mg, Cu, and Fe was developed from a combination of each element’s MEAM potential in order to study metal alloying. Previously published MEAM parameters of single elements have been improved for better agreement to the generalized stacking fault energy (GSFE) curves when compared with ab initio generated GSFE curves. The MEAM parameters for element pairs were constructed based on the structural and elastic properties of element pairs in the NaCl reference structure garnered from ab initio calculations, with adjustment to reproduce the ab initio heat of formation of the most stable binary compounds. The new MEAM potentials were validated by comparing the formation energies of defects, equilibrium volumes, elastic moduli, and heat of formation for several binary compounds with ab initio simulations and experiments. Single elements in their ground state crystal structure were subjected to heating to test the potentials at elevated temperatures. An Al potential was modified to avoid formation of an unphysical solid structure at high temperatures. The thermal expansion coefficient of a compound with the composition of AA 6061 alloy was evaluated and compared with experimental values. MEAM potential tests performed in this work, utilizing the universal atomistic simulation environment (ASE), are distributed to facilitate reproducibility of the results.