We review the synthesis, characterization, and applications of one-dimensional palladium-based nanostructures and provide perspectives on future directions in this field.

We present a unique three-dimensional palladium (Pd)-decorated crumpled reduced graphene oxide ball (Pd-CGB) nanocomposite for hydrogen (H 2 ) detection in air at room temperature. Pd-CGB nanocomposites were synthesized using a rapid continuous flame aerosol technique. Graphene oxide reduction and metal decoration occurred simultaneously in a high-temperature reducing jet (HTRJ) process to produce Pd nanoparticles that were below 5 nm in average size and uniformly dispersed in the crumpled graphene structure. The sensors made from these nanocomposites were sensitive over a wide range of H 2 concentrations (0.0025−2%) with response value, response time, and recovery time of 14.8%, 73 s, and 126 s, respectively, at 2% H 2 . Moreover, they were sensitive to H 2 in both dry and humid conditions. The sensors were stable and recoverable after 20 cycles at 2% H 2 with no degradation associated with volume expansion of Pd. Unlike two-step methods for fabricating Pd-decorated graphene sensors, the HTRJ process enables single-step formation of Pd-and other metal-decorated graphene nanocomposites with great potential for creating various gas sensors by simple drop-casting onto low-cost electrodes.

Palladium has long been explored for use in gas sensors because of its excellent catalytic properties and its unique property of forming hydrides in the presence of H 2 . However, pure Pd-based sensors usually suffer from low response and a relatively high limit of detection. Palladium nanosheets (PdNS) are of particular interest for gas sensing applications due to their high surface area and excellent electrical conductivity. Here, we demonstrate the design and fabrication of low-cost PdNS-based dual gas sensors for room-temperature detection of H 2 and CO over a wide concentration range. We fabricated sensors using multiwalled carbon nanotube@PdNS (MWCNT@PdNS) composites and compared their performance against pure PdNS devices for hydrogen sensing based on electrical resistive response. Devices using PdNS alone had a response and response time of 0.4% and 50 s, respectively, to 1% H 2 in air. MWCNT@PdNS (1:5 mass ratio) showed enhanced performance at a lower hydrogen concentration with a limit of detection (LOD H 2 ) of 5 ppm. Nearly an order of magnitude increase in response was observed on increasing the amount of MWCNT to 50 mass % in the nanocomposite, but the response fell off at low H 2 concentration. Overall, these PdNS-based sensors were found to show good repeatability, stability, and performance under humid conditions. Their response was selective for H 2 versus CH 4 , CO 2 , and NH 3 ; the response to CO was comparable in magnitude but opposite in sign to the response to H 2 . Upon simultaneous exposure to equal concentrations (10 ppm each) of H 2 and CO, the response to CO was dominant. The PdNS showed high sensitivity to CO, detecting as little as 1 ppm CO in air at room temperature. The sensitivity to CO could be used either in a stand-alone room-temperature CO detector, where H 2 is known not to be present, or in combination with CO and combustible gas detectors to distinguish H 2 from other combustible gases.

This manuscript presents a new single-step flame route to making multicomponent metal-decorated crumpled reduced graphene oxide balls.

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The adsorption energies of intermediates of the dry reforming of methane reaction (DRM CH4 + CO2 ⇔ 2CO + 2H2) using Rh(111) are approximated. Graph theory creates descriptors of the intermediates. The information recorded in these descriptors includes the elemental identities of each atom, its neighbors, and its next-nearest neighbors. Graph theory is employed because it is a rapid approximation of more expensive density functional theory (DFT) calculations and because the descriptors created by graph theory are both human and machine interpretable. DRM contains a significant number of adsorbates, and side reactions, including reverse water–gas shift, may occur simultaneously. Therefore, DRM is well-poised for analysis by a graph theory model to predict large numbers of adsorption energies. A portion of adsorbates were calculated with DFT. Then, predictions were reported for the remaining adsorption energies not calculated with DFT.