<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bajpai, Abhinav</style></author><author><style face="normal" font="default" size="100%">Mehta, Shweta</style></author><author><style face="normal" font="default" size="100%">Joshi, Kavita</style></author><author><style face="normal" font="default" size="100%">Kumar, Sushant</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Hydrogen from catalytic non-thermal plasma-assisted steam methane reforming reaction</style></title><secondary-title><style face="normal" font="default" size="100%">International Journal of Hydrogen Energy</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">DFT</style></keyword><keyword><style  face="normal" font="default" size="100%">Dielectric barrier discharge</style></keyword><keyword><style  face="normal" font="default" size="100%">Non-thermal plasma</style></keyword><keyword><style  face="normal" font="default" size="100%">selectivity</style></keyword><keyword><style  face="normal" font="default" size="100%">Specific energy input</style></keyword><keyword><style  face="normal" font="default" size="100%">Steam methane reforming</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JUL</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">48</style></volume><pages><style face="normal" font="default" size="100%">24328-24341</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	Steam methane reforming reaction was carried out in a dielectric barrier plasma reactor. A systematic study is conducted to understand the influence of input power, flow rate, and water for the conversion, yield, and selectivity of the reaction over strategically designed catalysts. In particular, the production rate and selectivity of the products (H2, CO and C2 hydrocarbons) are monitored. CeO2 was used as packing material, mixed with oxides of manganese or copper and their combination. The optimum Cu/CeO2 catalyst illustrated the production rate of 248.7 mmolg-1h-1 and 11.25 mmolg-1h-1 for H2, and CO, respectively at specific energy input of 19.8 JL-1. DFT calculations exhibit apparent change in electronic structure of the CeO2 after inclusion of oxides of manganese and copper that enhance interaction with methane. Based on these findings, a plausible mechanism is elucidatedSteam methane reforming reaction was carried out in a dielectric barrier plasma reactor. A systematic study is conducted to understand the influence of input power, flow rate, and water for the conversion, yield, and selectivity of the reaction over strategically designed catalysts. In particular, the production rate and selectivity of the products (H2, CO and C2 hydrocarbons) are monitored. CeO2 was used as packing material, mixed with oxides of manganese or copper and their combination. The optimum Cu/CeO2 catalyst illustrated the production rate of 248.7 mmolg-1h-1 and 11.25 mmolg-1h-1 for H2, and CO, respectively at specific energy input of 19.8 JL-1. DFT calculations exhibit apparent change in electronic structure of the CeO2 after inclusion of oxides of manganese and copper that enhance interaction with methane. Based on these findings, a plausible mechanism is elucidated which can help to design catalyst for other applications in non-thermal plasma atmosphere. &amp;amp; COPY; 2023 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">63</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;
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</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Wilson, Nikhil</style></author><author><style face="normal" font="default" size="100%">Verma, Ashwini</style></author><author><style face="normal" font="default" size="100%">Maharana, Piyush Ranjan</style></author><author><style face="normal" font="default" size="100%">Sahoo, Ameeya Bhusan</style></author><author><style face="normal" font="default" size="100%">Joshi, Kavita</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">HyStor: an experimental database of hydrogen storage properties for various metal alloy classes</style></title><secondary-title><style face="normal" font="default" size="100%">International Journal of Hydrogen Energy</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Databases</style></keyword><keyword><style  face="normal" font="default" size="100%">machine learning</style></keyword><keyword><style  face="normal" font="default" size="100%">Metal hydrides</style></keyword><keyword><style  face="normal" font="default" size="100%">Solid-state hydrogen storage</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">NOV </style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">90</style></volume><pages><style face="normal" font="default" size="100%">460-469</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	In this work, we introduce the HyStor database, consisting of 1282 metal alloys along with their maximum hydrogen storage capacity (H2wt%) at a given absorption temperature. The curated HydPark database consist of 831 entries. We sourced compositions from research articles and various patent documents, resulting in addition of 451 compositions to the HydPark database. The addition is reflected in the data across all existing classes of alloys. Further, low entropy alloys (LEA), medium entropy alloys (MEA) and high entropy alloys (HEA) have been newly included classes. This has broadened the scope of the database to encompass the latest materials of interest for hydrogen storage. HyStor contains representation of 54 elements, with a temperature range of 200-800 K, and H2wt% ranging from 0.1 to 7.19. We conducted thorough checks for duplicate entries, erroneous data, and conflicting compositions within the database to ensure data quality. Furthermore, we conducted multiple tests to identify potential outlier compositions. The data curation and updation reflects into slight improved error metrics of the HYST model, reducing the Mean Absolute Error (MAE) from 0.31 to 0.29 and increasing the R2 score from 0.77 to 0.79.&lt;/p&gt;
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	7.2&lt;/p&gt;
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