Human-centric intelligent systems for exploration and knowledge discovery

This speculative article discusses research and development relating to computational intelligence (CI) technologies comprising powerful machine-based search and exploration techniques that can generate, extract, process and present high-quality information from complex, poorly understood biotechnology domains. The integration and capture of user experiential knowledge within such CI systems in order to support and stimulate knowledge discovery and increase scientific and technological understanding is of particular interest. The manner in which appropriate user interaction can overcome problems relating to poor problem representation within systems utilising evolutionary computation (EC), machine-learning and software agent technologies is investigated. The objective is the development of user-centric intelligent systems that support an improving knowledge-base founded upon gradual problem re-definition and reformulation. Such an approach can overcome initial lack of understanding and associated uncertainty

X-ray generation using carbon nanotubes

Since the discovery of X-rays over a century ago the techniques applied to the engineering of X-ray sources have remained relatively unchanged. From the inception of thermionic electron sources, which, due to simplicity of fabrication, remain central to almost all X-ray applications, there have been few fundamental technological advances. However, with the emergence of ever more demanding medical and inspection techniques, including computed tomography and tomosynthesis, security inspection, high throughput manufacturing and radiotherapy, has resulted in a considerable level of interest in the development of new fabrication methods. The use of conventional thermionic sources is limited by their slow temporal response and large physical size. In response, field electron emission has emerged as a promising alternative means of deriving a highly controllable electron beam of a well-defined distribution. When coupled to the burgeoning field of nanomaterials, and in particular, carbon nanotubes, such systems present a unique technological opportunity. This review provides a summary of the current state-of-the-art in carbon nanotube-based field emission X-ray sources. We detail the various fabrication techniques and functional advantages associated with their use, including the ability to produce ever smaller electron beam assembles, shaped cathodes, enhanced temporal stability and emergent fast-switching pulsed sources. We conclude with an overview of some of the commercial progress made towards the realisation of an innovative and disruptive technology.Clare Collins is studying for the MRes in Ultra Precision, funded by the EPSRC, at the University of Cambridge.This is the final published version. It first appeared at http://www.nanoconvergencejournal.com/content/2/1/1

Towards graphane field emitters.

We report on the improved field emission performance of graphene foam (GF) following transient exposure to hydrogen plasma. The enhanced field emission mechanism associated with hydrogenation has been investigated using Fourier transform infrared spectroscopy, plasma spectrophotometry, Raman spectroscopy, and scanning electron microscopy. The observed enhanced electron emissionhas been attributed to an increase in the areal density of lattice defects and the formation of a partially hydrogenated, graphane-like material. The treated GF emitter demonstrated a much reduced macroscopic turn-on field (2.5 V μm-1), with an increased maximum current density from 0.21 mA cm-2 (pristine) to 8.27 mA cm-2 (treated). The treated GFs vertically orientated protrusions, after plasma etching, effectively increased the local electric field resulting in a 2.2-fold reduction in the turn-on electric field. The observed enhancement is further attributed to hydrogenation and the subsequent formation of a partially hydrogenated structured 2D material, which advantageously shifts the emitter work function. Alongside augmentation of the nominal crystallite size of the graphitic superstructure, surface bound species are believed to play a key role in the enhanced emission. The hydrogen plasma treatment was also noted to increase the emission spatial uniformity, with an approximate four times reduction in the per unit area variation in emission current density. Our findings suggest that plasma treatments, and particularly hydrogen and hydrogen-containing precursors, may provide an efficient, simple, and low cost means of realizing enhanced nanocarbon-based field emission devices via the engineered degradation of the nascent lattice, and adjustment of the surface work function.For assistance in ATR FTIR and EDXRF measurements we thank Dr Bob Keighley and Dr Ralph Vokes of Shimadzu Corp; and for plasma optical spectrophotometry analysis, Dr Thomas Schűtte of PLASUS GmbH. This work is supported by National Key Basic Research Program 973(2010CB327705), National Natural Science Foundation Project (51120125001, 51002031, 61101023, 51202028), Foundation of Doctoral Program of Ministry of Education (20100092110015), an EPSRC Impact Acceleration grant, and the Research Fund for International Young Scientists from NSFC (510501101 42, 51350110232). MT Cole thanks the Oppenheimer Trust for their generous financial support.This is the author accepted manuscript. The final version is available from the Royal Society of Chemistry via http://dx.doi.org/10.1039/C5RA20771

Towards graphane field emitters

We report on the improved field emission performance of graphene foam (GF) following transient exposure to hydrogen plasma. The enhanced field emission mechanism associated with hydrogenation has been investigated using Fourier transform infrared spectroscopy, plasma spectrophotometry, Raman spectroscopy, and scanning electron microscopy. The observed enhanced electron emissionhas been attributed to an increase in the areal density of lattice defects and the formation of a partially hydrogenated, graphane-like material. The treated GF emitter demonstrated a much reduced macroscopic turn-on field (2.5 V μm-1), with an increased maximum current density from 0.21 mA cm-2 (pristine) to 8.27 mA cm-2 (treated). The treated GFs vertically orientated protrusions, after plasma etching, effectively increased the local electric field resulting in a 2.2-fold reduction in the turn-on electric field. The observed enhancement is further attributed to hydrogenation and the subsequent formation of a partially hydrogenated structured 2D material, which advantageously shifts the emitter work function. Alongside augmentation of the nominal crystallite size of the graphitic superstructure, surface bound species are believed to play a key role in the enhanced emission. The hydrogen plasma treatment was also noted to increase the emission spatial uniformity, with an approximate four times reduction in the per unit area variation in emission current density. Our findings suggest that plasma treatments, and particularly hydrogen and hydrogen-containing precursors, may provide an efficient, simple, and low cost means of realizing enhanced nanocarbon-based field emission devices via the engineered degradation of the nascent lattice, and adjustment of the surface work function.</p

Biomorpher: interactive evolution for parametric design

Combining graph-based parametric design with metaheuristic solvers has to date focussed solely on performance based criteria and solving clearly defined objectives. In this paper, we outline a new method for combining a parametric modelling environment with an interactive Cluster-Orientated Genetic Algorithm (COGA). In addition to performance criteria, evolutionary design exploration can be guided through choice alone, with user motivation that cannot be easily defined. As well as numeric parameters forming a genotype, the evolution of whole parametric definitions is discussed through the use of genetic programming. Visualisation techniques that enable mixing small populations for interactive evolution with large populations for performance-based optimisation are discussed, with examples from both academia and industry showing a wide range of applications

Normal parameter reduction algorithm in soft set based on hybrid binary particle swarm and biogeography optimizer

© 2019, Springer-Verlag London Ltd., part of Springer Nature. Existing classification techniques that are proposed previously for eliminating data inconsistency could not achieve an efficient parameter reduction in soft set theory, which effects on the obtained decisions. Meanwhile, the computational cost made during combination generation process of soft sets could cause machine infinite state, which is known as nondeterministic polynomial time. The contributions of this study are mainly focused on minimizing choices costs through adjusting the original classifications by decision partition order and enhancing the probability of searching domain space using a developed Markov chain model. Furthermore, this study introduces an efficient soft set reduction-based binary particle swarm optimized by biogeography-based optimizer (SSR-BPSO-BBO) algorithm that generates an accurate decision for optimal and sub-optimal choices. The results show that the decision partition order technique is performing better in parameter reduction up to 50%, while other algorithms could not obtain high reduction rates in some scenarios. In terms of accuracy, the proposed SSR-BPSO-BBO algorithm outperforms the other optimization algorithms in achieving high accuracy percentage of a given soft dataset. On the other hand, the proposed Markov chain model could significantly represent the robustness of our parameter reduction technique in obtaining the optimal decision and minimizing the search domain.Published versio

Evolutionary and adaptive computing in engineering design

xvi, 286 p. : ill. ; 24 cm