Active Learning of Piecewise Gaussian Process Surrogates

Active learning of Gaussian process (GP) surrogates has been useful for optimizing experimental designs for physical/computer simulation experiments, and for steering data acquisition schemes in machine learning. In this paper, we develop a method for active learning of piecewise, Jump GP surrogates. Jump GPs are continuous within, but discontinuous across, regions of a design space, as required for applications spanning autonomous materials design, configuration of smart factory systems, and many others. Although our active learning heuristics are appropriated from strategies originally designed for ordinary GPs, we demonstrate that additionally accounting for model bias, as opposed to the usual model uncertainty, is essential in the Jump GP context. Toward that end, we develop an estimator for bias and variance of Jump GP models. Illustrations, and evidence of the advantage of our proposed methods, are provided on a suite of synthetic benchmarks, and real-simulation experiments of varying complexity.Comment: The main algorithm of this work is protected by a provisional patent pending with application number 63/386,82

Strong Fiber from Uniaxial Fullerene Supramolecules Aligned with Carbon Nanotubes

Carbon nanotube (CNT) wires approach copper's specific conductivity and surpass carbon fiber's strength, with further improvement anticipated with greater aspect ratios and incorporation of dopants with long-range structural order. Fullerenes assemble into multitudes of process-dependent supramolecular crystals and, while initially insulating, they become marginally conductive (up to 0.05 MSm$^{-1}$) and superconductive ($T_c=18^\circ$K with K and 28$^\circ$K with Rb) after doping. These were small (100's $\mu$m long), soft (hardness comparable to indium), and typically unaligned, which hindered development of fullerene based wires. Individual fullerenes were previously incorporated into CNT fibers, although randomly without self-assembly into supramolecules. Here, a simple variation in established CNT acid extrusion creates a fiber composed of uniaxial chains of aligned fullerene supramolecules, self-assembled between aligned few-walled CNT bundles. This will provide a testbed for novel fullerene wire transport and prospects in CNT wire advancement

Study on the optical and electrical properties of tetracyanoethylene doped bilayer graphene stack for transparent conducting electrodes

We report the optical and electrical properties of chemically-doped bilayer graphene stack by tetracyanoethylene, a strong electron acceptor. The Tetracyanoethylene doping on the bilayer graphene via charge transfer was confirmed by Raman spectroscopy and Infrared Fourier transform spectroscopy. Doped graphene shows a significant increase in the sheet carrier concentration of up to 1.520 × 1013 cm−2 with a concomitant reduction of the sheet resistance down to 414.1 Ω/sq. The high optical transmittance (ca. 84%) in the visible region in combination with the low sheet resistance of the Tetracyanoethylene-doped bilayer graphene stack opens up the possibility of making transparent conducting electrodes for practical applications

Non-isothermal Chemical Vapor Deposition for Increasing Carbon Nanotube Yield

Increasing the yield of single-walled carbon nanotubes (CNTs) during growth is critical to their use in widespread applications. Here, we show that we can increase the CNT yield significantly by using a simple non-isothermal, continuous cooling procedure during CNT growth. While our typical isothermal growth conditions produce sparse bundled mats, our non-isothermal growth protocol results in high-density tall forests without the need for growth promoters, additional source materials, or additional processing. In situ experiments revealed that cooling rate and temperature difference are critical and were optimized for the highest increase in CNT yield. Moreover, the general applicability of the process was demonstrated by performing chemical vapor deposition growth experiments in a tube furnace on a variety of catalyst compositions and thicknesses. The observed improvement in the non-isothermal process across all experimental platforms and catalysts occurs due to a decline in particle coarsening and to the formation of smaller particles with an order of magnitude higher density compared to isothermal growth. We 1 attribute this to the de-stabilization of the catalyst films during continuous cooling. Non- isothermal growth provides a path forward for improving SWCNT yields while retaining all other growth conditions

Etude de la croissance catalytique des nanotubes de carbone par spectroscopie Raman in situ

National audience

Etude de la croissance catalytique des nanotubes de carbone par spectroscopie Raman in situ

National audience