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Electric Field and Neural Network in Catalysis: Amine Acylation in the Scanning Tunneling Microscope-Break Junction and Oxadiazoliums in Stetter Catalysis
Electric Field and Neural Network in Catalysis: Amine Acylation in the Scanning Tunneling Microscope-Break Junction and Oxadiazoliums in Stetter Catalysis
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211152828
- ISBN
- 9798384086987
- DDC
- 540
- 저자명
- Wang, Xiye.
- 서명/저자
- Electric Field and Neural Network in Catalysis: Amine Acylation in the Scanning Tunneling Microscope-Break Junction and Oxadiazoliums in Stetter Catalysis
- 발행사항
- [Sl] : Columbia University, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 240 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-03, Section: B.
- 주기사항
- Advisor: Rovis, Tomislav.
- 학위논문주기
- Thesis (Ph.D.)--Columbia University, 2024.
- 초록/해제
- 요약Electric fields influence reactions by stabilization of charge-separated transition states. While this has been a longstanding hypothesis supported computationally, recent experimental confirmations highlight the potential for leveraging electric field effects to drive small molecule reactions far from equilibrium. Herein we report electric-field catalysis of an alkane solvent-derived acylation reaction in the scanning tunneling microscope-break junction (STM-BJ), providing additional support for this hypothesis. Additionally, the design and reactivity of an internally charged zwitterionic ligand are disclosed. Synthetic access of metal ligands bearing opposing charged functional groups permitted the examination of stochiometric metalation and catalytic behavior of electric field-bearing ligands.While traditionally computation has been used to rationalize why a particular catalyst is successful descriptively, it has been rarely used to screen candidates and prescriptively provide optimal catalyst structure. We report a neural network-enabled catalyst screening platform that dramatically reduce the resource intensity for examining a large chemical space. We leverage this platform to examine azolium N-heterocyclic carbene (NHC) precursors to address the lack of compatibility for electron-rich aryl aldehydes in the NHC-catalyzed Stetter reaction. This led to the discovery of a new class of azolium NHC precursor: oxadiazoliums that proved competent in achieving the target reaction addressing current limitations in Stetter catalysis.
- 일반주제명
- Chemistry
- 일반주제명
- Analytical chemistry
- 키워드
- Electric fields
- 키워드
- Oxadiazoliums
- 키워드
- Metal ligands
- 기타저자
- Columbia University Chemistry
- 기본자료저록
- Dissertations Abstracts International. 86-03B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■00520250211152828
■006m o d
■007cr#unu||||||||
■020 ▼a9798384086987
■035 ▼a(MiAaPQ)AAI31560316
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a540
■1001 ▼aWang, Xiye.
■24510▼aElectric Field and Neural Network in Catalysis: Amine Acylation in the Scanning Tunneling Microscope-Break Junction and Oxadiazoliums in Stetter Catalysis
■260 ▼a[Sl]▼bColumbia University▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a240 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-03, Section: B.
■500 ▼aAdvisor: Rovis, Tomislav.
■5021 ▼aThesis (Ph.D.)--Columbia University, 2024.
■520 ▼aElectric fields influence reactions by stabilization of charge-separated transition states. While this has been a longstanding hypothesis supported computationally, recent experimental confirmations highlight the potential for leveraging electric field effects to drive small molecule reactions far from equilibrium. Herein we report electric-field catalysis of an alkane solvent-derived acylation reaction in the scanning tunneling microscope-break junction (STM-BJ), providing additional support for this hypothesis. Additionally, the design and reactivity of an internally charged zwitterionic ligand are disclosed. Synthetic access of metal ligands bearing opposing charged functional groups permitted the examination of stochiometric metalation and catalytic behavior of electric field-bearing ligands.While traditionally computation has been used to rationalize why a particular catalyst is successful descriptively, it has been rarely used to screen candidates and prescriptively provide optimal catalyst structure. We report a neural network-enabled catalyst screening platform that dramatically reduce the resource intensity for examining a large chemical space. We leverage this platform to examine azolium N-heterocyclic carbene (NHC) precursors to address the lack of compatibility for electron-rich aryl aldehydes in the NHC-catalyzed Stetter reaction. This led to the discovery of a new class of azolium NHC precursor: oxadiazoliums that proved competent in achieving the target reaction addressing current limitations in Stetter catalysis.
■590 ▼aSchool code: 0054.
■650 4▼aChemistry
■650 4▼aAnalytical chemistry
■653 ▼aElectric fields
■653 ▼aOxadiazoliums
■653 ▼aMetal ligands
■653 ▼aZwitterionic ligand
■653 ▼aStetter catalysis
■690 ▼a0485
■690 ▼a0486
■71020▼aColumbia University▼bChemistry.
■7730 ▼tDissertations Abstracts International▼g86-03B.
■790 ▼a0054
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17164069▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
