東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Understanding and Predicting the Kin...

Trottier, Ryan Michael.

FindBook

Google Book

Amazon

博客來

Understanding and Predicting the Kinetic Behavior of Metal Oxide Materials for Solar Thermochemical Hydrogen Production.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Understanding and Predicting the Kinetic Behavior of Metal Oxide Materials for Solar Thermochemical Hydrogen Production./
作者:	Trottier, Ryan Michael.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:	144 p.
附註:	Source: Dissertations Abstracts International, Volume: 82-07, Section: B.
Contained By:	Dissertations Abstracts International82-07B.
標題:	Chemical engineering. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28255493
ISBN:	9798557024914

Understanding and Predicting the Kinetic Behavior of Metal Oxide Materials for Solar Thermochemical Hydrogen Production.
Trottier, Ryan Michael.

Understanding and Predicting the Kinetic Behavior of Metal Oxide Materials for Solar Thermochemical Hydrogen Production. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 144 p.

Source: Dissertations Abstracts International, Volume: 82-07, Section: B.

Thesis (Ph.D.)--University of Colorado at Boulder, 2020.

This item must not be sold to any third party vendors.

Solar thermochemical hydrogen production (STCH) is a promising technology that enables the production of hydrogen H2 from H2O and renewable solar energy. There are still many barriers to overcome in deploying this technology at scale, but one of the most significant is the need for functional materials. These materials must not only be capable of undergoing the necessary STCH reactions but be capable of undergoing such reactions fast enough to be practical. In this work, we study the reactions which underpin the STCH process, with a particular focus on the oxygen vacancy (VO) diffusion reaction. This study is performed through multiple scales of investigation, from an in-depth study on a single material, hercynite, to developing a high-throughput machine-learned model predicting VO diffusion barriers from material properties available from only the unit cell. The former investigation into hercynite required understanding the effect of disorder caused by spinel inversion. We examined 11 of the most common cation arrangements and found a near 1:1 correlation between the diffusion barrier and VO formation energy. We also show that uncompensated Fe antisite defects provide redox flexibility that stabilizes the charged VO and thereby increase the rate of VO diffusion. To model additional materials, we detail an approach to accelerate the computational screening of the diffusion barrier for solid state reactions. This is done by reliably and rapidly identifying upper and lower bounds to the transition state (TS) energy. This method is a modified single iteration of the synchronous transit (MSIST) approach. Applying MSIST in a high-throughput manner allowed the investigation of more than 500 diffusion pathways in 97 different materials, the average difference between the upper and lower bounds was 0.33 eV. The MSIST approach produces explicit errors, i.e., the difference between the upper and lower bounds, therefore even predicted barrier ranges with large errors could be reliably modeled with weighted regression techniques. This allows us to use machine-learned models to analyze our data. We do this using the SISSO algorithm and calculate diffusion barriers for STCH materials to a RMSE of 0.55 eV using only material properties calculable from a unit cell.

ISBN: 9798557024914Subjects--Topical Terms:

560457
Chemical engineering.
Subjects--Index Terms:

Solar thermochemical hydrogen production (STCH)

Understanding and Predicting the Kinetic Behavior of Metal Oxide Materials for Solar Thermochemical Hydrogen Production.
LDR:03669nmm a2200433 4500 001 2279637
005 20210823080303.5
008 220723s2020 ||||||||||||||||| ||eng d
020 $a 9798557024914
035 $a (MiAaPQ)AAI28255493
035 $a AAI28255493
040 $a MiAaPQ $c MiAaPQ
100 1 $a Trottier, Ryan Michael. $0 (orcid)0000-0002-7424-3975 $3 3558100
245 1 0 $a Understanding and Predicting the Kinetic Behavior of Metal Oxide Materials for Solar Thermochemical Hydrogen Production.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2020
300 $a 144 p.
500 $a Source: Dissertations Abstracts International, Volume: 82-07, Section: B.
500 $a Advisor: Musgrave, Charles B.
502 $a Thesis (Ph.D.)--University of Colorado at Boulder, 2020.
506 $a This item must not be sold to any third party vendors.
520 $a Solar thermochemical hydrogen production (STCH) is a promising technology that enables the production of hydrogen H2 from H2O and renewable solar energy. There are still many barriers to overcome in deploying this technology at scale, but one of the most significant is the need for functional materials. These materials must not only be capable of undergoing the necessary STCH reactions but be capable of undergoing such reactions fast enough to be practical. In this work, we study the reactions which underpin the STCH process, with a particular focus on the oxygen vacancy (VO) diffusion reaction. This study is performed through multiple scales of investigation, from an in-depth study on a single material, hercynite, to developing a high-throughput machine-learned model predicting VO diffusion barriers from material properties available from only the unit cell. The former investigation into hercynite required understanding the effect of disorder caused by spinel inversion. We examined 11 of the most common cation arrangements and found a near 1:1 correlation between the diffusion barrier and VO formation energy. We also show that uncompensated Fe antisite defects provide redox flexibility that stabilizes the charged VO and thereby increase the rate of VO diffusion. To model additional materials, we detail an approach to accelerate the computational screening of the diffusion barrier for solid state reactions. This is done by reliably and rapidly identifying upper and lower bounds to the transition state (TS) energy. This method is a modified single iteration of the synchronous transit (MSIST) approach. Applying MSIST in a high-throughput manner allowed the investigation of more than 500 diffusion pathways in 97 different materials, the average difference between the upper and lower bounds was 0.33 eV. The MSIST approach produces explicit errors, i.e., the difference between the upper and lower bounds, therefore even predicted barrier ranges with large errors could be reliably modeled with weighted regression techniques. This allows us to use machine-learned models to analyze our data. We do this using the SISSO algorithm and calculate diffusion barriers for STCH materials to a RMSE of 0.55 eV using only material properties calculable from a unit cell.
590 $a School code: 0051.
650 4 $a Chemical engineering. $3 560457
650 4 $a Materials science. $3 543314
650 4 $a Hydrologic sciences. $3 3168407
650 4 $a Thermodynamics. $3 517304
650 4 $a Computational chemistry. $3 3350019
650 4 $a Organic chemistry. $3 523952
653 $a Solar thermochemical hydrogen production (STCH)
653 $a Hydrogen production
653 $a Machine learning
653 $a Spinel inversion
653 $a Formation energy
653 $a Diffusion barrier
653 $a Hercynite
690 $a 0542
690 $a 0794
690 $a 0388
690 $a 0348
690 $a 0219
690 $a 0490
710 2 $a University of Colorado at Boulder. $b Chemical and Biological Engineering. $3 3428945
773 0 $t Dissertations Abstracts International $g 82-07B.
790 $a 0051
791 $a Ph.D.
792 $a 2020
793 $a English
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28255493