A density-functional theory study of the Al/AlOx/Al tunnel junction
The aluminum oxide tunnel junction is a key component of the majority of superconducting quantum devices. For high-quality, reproducible, and scalably manufacturable qubits, the ability to fabricate Josephson junctions (JJs) with a targeted critical current and high uniformity is essential. We use f...
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creator | Kim, Chang-Eun Ray, Keith G. Lordi, Vincenzo |
description | The aluminum oxide tunnel junction is a key component of the majority of superconducting quantum devices. For high-quality, reproducible, and scalably manufacturable qubits, the ability to fabricate Josephson junctions (JJs) with a targeted critical current and high uniformity is essential. We use first-principles modeling to assess fundamental aspects of the atomic structure of both amorphous and crystalline aluminum oxide tunnel junctions and relate the structure to predicted performance metrics. We use modified ab initio molecular dynamics to develop realistic models of the tunnel junction, from which interface roughness and local thickness fluctuations are analyzed in an unbiased manner by training a neural network to identify the boundary between metal and oxide. We show that the effective thickness of the insulating part of the junction can be different from the apparent physical thickness. We calculate the rate of Cooper pair tunneling for the atomically resolved electrostatic potential using direct numerical solution in 3D, which shows a channeling effect that impacts the junction critical current. The predicted critical current is a useful JJ design parameter that can be accessed from the ab initio calculations without fitting parameters. To assess the limits of uniformity and fabrication choices (e.g., oxidation vs epitaxy), we compare the amorphous junctions to crystalline models, which show order of magnitude more efficient tunneling compared to the amorphous case, underlining the connection between atomistic structure and Cooper pair tunneling efficiency. Further, this work provides a foundation for ab initio materials design and evaluation to help accelerate future development of improved tunnel junctions. |
doi_str_mv | 10.1063/5.0020292 |
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(LLNL), Livermore, CA (United States)</creatorcontrib><description>The aluminum oxide tunnel junction is a key component of the majority of superconducting quantum devices. For high-quality, reproducible, and scalably manufacturable qubits, the ability to fabricate Josephson junctions (JJs) with a targeted critical current and high uniformity is essential. We use first-principles modeling to assess fundamental aspects of the atomic structure of both amorphous and crystalline aluminum oxide tunnel junctions and relate the structure to predicted performance metrics. We use modified ab initio molecular dynamics to develop realistic models of the tunnel junction, from which interface roughness and local thickness fluctuations are analyzed in an unbiased manner by training a neural network to identify the boundary between metal and oxide. We show that the effective thickness of the insulating part of the junction can be different from the apparent physical thickness. We calculate the rate of Cooper pair tunneling for the atomically resolved electrostatic potential using direct numerical solution in 3D, which shows a channeling effect that impacts the junction critical current. The predicted critical current is a useful JJ design parameter that can be accessed from the ab initio calculations without fitting parameters. To assess the limits of uniformity and fabrication choices (e.g., oxidation vs epitaxy), we compare the amorphous junctions to crystalline models, which show order of magnitude more efficient tunneling compared to the amorphous case, underlining the connection between atomistic structure and Cooper pair tunneling efficiency. Further, this work provides a foundation for ab initio materials design and evaluation to help accelerate future development of improved tunnel junctions.</description><identifier>ISSN: 0021-8979</identifier><identifier>EISSN: 1089-7550</identifier><identifier>DOI: 10.1063/5.0020292</identifier><identifier>CODEN: JAPIAU</identifier><language>eng</language><publisher>Melville: American Institute of Physics</publisher><subject>ab-initio methods ; ab-initio molecular dynamics ; Aluminum oxide ; Applied physics ; artificial neural networks ; Atomic structure ; atomistic simulations ; Channeling ; CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY ; Critical current (superconductivity) ; Crystal structure ; Crystallinity ; Density functional theory ; Design parameters ; First principles ; Interface roughness ; Josephson junctions ; Mathematical models ; Molecular dynamics ; Neural networks ; Oxidation ; Performance measurement ; quantum computing ; quantum tunneling ; Qubits (quantum computing) ; Schrodinger equations ; solid solid interfaces ; superconducting devices ; Thickness ; Tunnel junctions</subject><ispartof>Journal of applied physics, 2020-10, Vol.128 (15)</ispartof><rights>Author(s)</rights><rights>2020 Author(s). Published under license by AIP Publishing.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0002-8698-018X ; 0000-0002-6241-7472 ; 0000-0003-2415-4656 ; 0000000262417472 ; 0000000324154656 ; 000000028698018X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://pubs.aip.org/jap/article-lookup/doi/10.1063/5.0020292$$EHTML$$P50$$Gscitation$$H</linktohtml><link.rule.ids>230,314,780,784,794,885,4512,27924,27925,76384</link.rule.ids><backlink>$$Uhttps://www.osti.gov/servlets/purl/1738913$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Kim, Chang-Eun</creatorcontrib><creatorcontrib>Ray, Keith G.</creatorcontrib><creatorcontrib>Lordi, Vincenzo</creatorcontrib><creatorcontrib>Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)</creatorcontrib><title>A density-functional theory study of the Al/AlOx/Al tunnel junction</title><title>Journal of applied physics</title><description>The aluminum oxide tunnel junction is a key component of the majority of superconducting quantum devices. For high-quality, reproducible, and scalably manufacturable qubits, the ability to fabricate Josephson junctions (JJs) with a targeted critical current and high uniformity is essential. We use first-principles modeling to assess fundamental aspects of the atomic structure of both amorphous and crystalline aluminum oxide tunnel junctions and relate the structure to predicted performance metrics. We use modified ab initio molecular dynamics to develop realistic models of the tunnel junction, from which interface roughness and local thickness fluctuations are analyzed in an unbiased manner by training a neural network to identify the boundary between metal and oxide. We show that the effective thickness of the insulating part of the junction can be different from the apparent physical thickness. We calculate the rate of Cooper pair tunneling for the atomically resolved electrostatic potential using direct numerical solution in 3D, which shows a channeling effect that impacts the junction critical current. The predicted critical current is a useful JJ design parameter that can be accessed from the ab initio calculations without fitting parameters. To assess the limits of uniformity and fabrication choices (e.g., oxidation vs epitaxy), we compare the amorphous junctions to crystalline models, which show order of magnitude more efficient tunneling compared to the amorphous case, underlining the connection between atomistic structure and Cooper pair tunneling efficiency. Further, this work provides a foundation for ab initio materials design and evaluation to help accelerate future development of improved tunnel junctions.</description><subject>ab-initio methods</subject><subject>ab-initio molecular dynamics</subject><subject>Aluminum oxide</subject><subject>Applied physics</subject><subject>artificial neural networks</subject><subject>Atomic structure</subject><subject>atomistic simulations</subject><subject>Channeling</subject><subject>CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY</subject><subject>Critical current (superconductivity)</subject><subject>Crystal structure</subject><subject>Crystallinity</subject><subject>Density functional theory</subject><subject>Design parameters</subject><subject>First principles</subject><subject>Interface roughness</subject><subject>Josephson junctions</subject><subject>Mathematical models</subject><subject>Molecular dynamics</subject><subject>Neural networks</subject><subject>Oxidation</subject><subject>Performance measurement</subject><subject>quantum computing</subject><subject>quantum tunneling</subject><subject>Qubits (quantum computing)</subject><subject>Schrodinger equations</subject><subject>solid solid interfaces</subject><subject>superconducting devices</subject><subject>Thickness</subject><subject>Tunnel junctions</subject><issn>0021-8979</issn><issn>1089-7550</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kE9Lw0AQxRdRsFYPfoOgNyHtzG42yR5DsSoUetHzst0_NCVma3Yj5tub0II3LzPM8JvHvEfIPcICIWdLvgCgQAW9IDOEUqQF53BJZuMW01IU4prchHAAQCyZmJFVlRjbhjoOqetbHWvfqiaJe-u7IQmxN0Pi3TQnVbOsmu3PWJLYt61tksP54JZcOdUEe3fuc_Kxfn5fvaab7cvbqtqkniGPqXE7i7nWKjcFpVbxArTLlNgVNNfMoHYOqDZlzhQwK0Y7pXHaALeYIc1yNicPJ10fYi2DrqPVe-3HX3SUWLBSIBuhxxN07PxXb0OUB993o6kgacaRggAxUU8nalJRkwl57OpP1Q0SQU5JSi7PSf4Hf_vuD5RH49gvcZpy2w</recordid><startdate>20201021</startdate><enddate>20201021</enddate><creator>Kim, Chang-Eun</creator><creator>Ray, Keith G.</creator><creator>Lordi, Vincenzo</creator><general>American Institute of Physics</general><general>American Institute of Physics (AIP)</general><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope><scope>OIOZB</scope><scope>OTOTI</scope><orcidid>https://orcid.org/0000-0002-8698-018X</orcidid><orcidid>https://orcid.org/0000-0002-6241-7472</orcidid><orcidid>https://orcid.org/0000-0003-2415-4656</orcidid><orcidid>https://orcid.org/0000000262417472</orcidid><orcidid>https://orcid.org/0000000324154656</orcidid><orcidid>https://orcid.org/000000028698018X</orcidid></search><sort><creationdate>20201021</creationdate><title>A density-functional theory study of the Al/AlOx/Al tunnel junction</title><author>Kim, Chang-Eun ; Ray, Keith G. ; Lordi, Vincenzo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-o315t-dfbe16cca6d722ea570cf4a9b726c3d1cff02cd863a03e91068dfcd05e1412463</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>ab-initio methods</topic><topic>ab-initio molecular dynamics</topic><topic>Aluminum oxide</topic><topic>Applied physics</topic><topic>artificial neural networks</topic><topic>Atomic structure</topic><topic>atomistic simulations</topic><topic>Channeling</topic><topic>CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY</topic><topic>Critical current (superconductivity)</topic><topic>Crystal structure</topic><topic>Crystallinity</topic><topic>Density functional theory</topic><topic>Design parameters</topic><topic>First principles</topic><topic>Interface roughness</topic><topic>Josephson junctions</topic><topic>Mathematical models</topic><topic>Molecular dynamics</topic><topic>Neural networks</topic><topic>Oxidation</topic><topic>Performance measurement</topic><topic>quantum computing</topic><topic>quantum tunneling</topic><topic>Qubits (quantum computing)</topic><topic>Schrodinger equations</topic><topic>solid solid interfaces</topic><topic>superconducting devices</topic><topic>Thickness</topic><topic>Tunnel junctions</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kim, Chang-Eun</creatorcontrib><creatorcontrib>Ray, Keith G.</creatorcontrib><creatorcontrib>Lordi, Vincenzo</creatorcontrib><creatorcontrib>Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)</creatorcontrib><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>OSTI.GOV - Hybrid</collection><collection>OSTI.GOV</collection><jtitle>Journal of applied physics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kim, Chang-Eun</au><au>Ray, Keith G.</au><au>Lordi, Vincenzo</au><aucorp>Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A density-functional theory study of the Al/AlOx/Al tunnel junction</atitle><jtitle>Journal of applied physics</jtitle><date>2020-10-21</date><risdate>2020</risdate><volume>128</volume><issue>15</issue><issn>0021-8979</issn><eissn>1089-7550</eissn><coden>JAPIAU</coden><abstract>The aluminum oxide tunnel junction is a key component of the majority of superconducting quantum devices. For high-quality, reproducible, and scalably manufacturable qubits, the ability to fabricate Josephson junctions (JJs) with a targeted critical current and high uniformity is essential. We use first-principles modeling to assess fundamental aspects of the atomic structure of both amorphous and crystalline aluminum oxide tunnel junctions and relate the structure to predicted performance metrics. We use modified ab initio molecular dynamics to develop realistic models of the tunnel junction, from which interface roughness and local thickness fluctuations are analyzed in an unbiased manner by training a neural network to identify the boundary between metal and oxide. We show that the effective thickness of the insulating part of the junction can be different from the apparent physical thickness. We calculate the rate of Cooper pair tunneling for the atomically resolved electrostatic potential using direct numerical solution in 3D, which shows a channeling effect that impacts the junction critical current. The predicted critical current is a useful JJ design parameter that can be accessed from the ab initio calculations without fitting parameters. To assess the limits of uniformity and fabrication choices (e.g., oxidation vs epitaxy), we compare the amorphous junctions to crystalline models, which show order of magnitude more efficient tunneling compared to the amorphous case, underlining the connection between atomistic structure and Cooper pair tunneling efficiency. Further, this work provides a foundation for ab initio materials design and evaluation to help accelerate future development of improved tunnel junctions.</abstract><cop>Melville</cop><pub>American Institute of Physics</pub><doi>10.1063/5.0020292</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0002-8698-018X</orcidid><orcidid>https://orcid.org/0000-0002-6241-7472</orcidid><orcidid>https://orcid.org/0000-0003-2415-4656</orcidid><orcidid>https://orcid.org/0000000262417472</orcidid><orcidid>https://orcid.org/0000000324154656</orcidid><orcidid>https://orcid.org/000000028698018X</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | ab-initio methods ab-initio molecular dynamics Aluminum oxide Applied physics artificial neural networks Atomic structure atomistic simulations Channeling CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY Critical current (superconductivity) Crystal structure Crystallinity Density functional theory Design parameters First principles Interface roughness Josephson junctions Mathematical models Molecular dynamics Neural networks Oxidation Performance measurement quantum computing quantum tunneling Qubits (quantum computing) Schrodinger equations solid solid interfaces superconducting devices Thickness Tunnel junctions |
title | A density-functional theory study of the Al/AlOx/Al tunnel junction |
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