Lab::Measurement - A portable and extensible framework for controlling lab equipment and conducting measurements

Lab::Measurement is a framework for test and measurement automatization using Perl 5. While primarily developed with applications in mesoscopic physics in mind, it is widely adaptable. Internally, a layer model is implemented. Communication protocols such as IEEE 488, USB Test & Measurement, or, e.g., VXI-11 are addressed by the connection layer. The wide range of supported connection backends enables unique cross-platform portability. At the instrument layer, objects correspond to equipment connected to the measurement PC (e.g., voltage sources, magnet power supplies, multimeters, etc.). The high-level sweep layer automates the creation of measurement loops, with simultaneous plotting and data logging. An extensive unit testing framework is used to verify functionality even without connected equipment. Lab::Measurement is distributed as free and open source software.Comment: Published version (open access, CC BY 4.0). 7 pages; refers to Lab::Measurement 3.660, see https://www.labmeasurement.de

Broken SU(4) symmetry in a Kondo-correlated carbon nanotube

Understanding the interplay between many-body phenomena and non-equilibrium in systems with entangled spin and orbital degrees of freedom is a central objective in nano-electronics. We demonstrate that the combination of Coulomb interaction, spin-orbit coupling and valley mixing results in a particular selection of the inelastic virtual processes contributing to the Kondo resonance in carbon nanotubes at low temperatures. This effect is dictated by conjugation properties of the underlying carbon nanotube spectrum at zero and finite magnetic field. Our measurements on a clean carbon nanotube are complemented by calculations based on a new approach to the non-equilibrium Kondo problem which well reproduces the rich experimental observations in Kondo transport.Comment: 8 pages, 6 figures; appendix of 14 pages, 7 figure

Lab::Measurement — A portable and extensible framework for controlling lab equipment and conducting measurements

Lab::Measurement is a framework for test and measurement automatization using Pert 5. While primarily developed with applications in mesoscopic physics in mind, it is widely adaptable. Internally, a layer model is implemented. Communication protocols such as IEEE 488 [1], USB Test & Measurement [2], or, e.g., VXI-11 [3] are addressed by the connection layer. The wide range of supported connection backends enables unique cross-platform portability. At the instrument layer, objects correspond to equipment connected to the measurement PC (e.g., voltage sources, magnet power supplies, multimeters, etc.). The high-level sweep layer automates the creation of measurement loops, with simultaneous plotting and data logging. An extensive unit testing framework is used to verify functionality even without connected equipment. Lab::Measurement is distributed as free and open source software. (C) 2018 The Author(s). Published by Elsevier B.V

Magnetic field control of the Franck-Condon coupling of few-electron quantum states

Suspended carbon nanotubes display at cryogenic temperatures a distinct interaction between the quantized longitudinal vibration of the macromolecule and its embedded quantum dot, visible via Franck-Condon conductance sidebands in transport spectroscopy. We present data on such sidebands at known absolute number N-el = 1 and N-el = 2 of conduction band electrons and, consequently, well-defined electronic ground and excited states in a clean nanotube device. The interaction evolves only at a finite axial magnetic field and displays a distinct magnetic-field dependence of the Franck-Condon coupling parameter, different for different electronic base states and indicating a valley dependence. Reshaping of the electronic wave function by the magnetic field is discussed as a possible cause of our observations; its impact is demonstrated in a model calculation reproducing the field-dependent coupling.Peer reviewe

PRospective EnvironMental Impact asSEment (premise): A streamlined approach to producing databases for prospective life cycle assessment using integrated assessment models

Prospective Life Cycle Assessment (pLCA) is useful to evaluate the environmental performance of current and emerging technologies in the future. Yet, as energy systems and industries are rapidly shifting towards cleaner means of production, pLCA requires an inventory database that encapsulates the expected changes in technologies and the environment at a given point in time, following specific socio-techno-economic pathways. To this end, this study introduces premise, a tool to streamline the generation of prospective inventory databases for pLCA by integrating scenarios generated by Integrated Assessment Models (IAM). More precisely, premise applies a number of transformations on energy-intensive activities found in the inventory database ecoinvent according to projections provided by the IAM. Unsurprisingly, the study shows that, within a given socio-economic narrative, the climate change mitigation target chosen affects the performance of nearly all activities in the database. This is illustrated by focusing on the effects observed on a few activities, such as systems for direct air capture of CO2, lithium-ion batteries, electricity and clinker production as well as freight transport by road, in relation to the applied sector-based transformation and the chosen climate change mitigation target. This work also discusses the limitations and challenges faced when coupling IAM and LCA databases and what improvements are to be brought in to further facilitate the development of pLCA

PRospective EnvironMental Impact asSEment (premise): A streamlined approach to producing databases for prospective life cycle assessment using integrated assessment models

Prospective Life Cycle Assessment (pLCA) is useful to evaluate the environmental performance of current and emerging technologies in the future. Yet, as energy systems and industries are rapidly shifting towards cleaner means of production, pLCA requires an inventory database that encapsulates the expected changes in technologies and the environment at a given point in time, following specific socio-techno-economic pathways. To this end, this study introduces premise, a tool to streamline the generation of prospective inventory databases for pLCA by integrating scenarios generated by Integrated Assessment Models (IAM). More precisely, premise applies a number of transformations on energy-intensive activities found in the inventory database ecoinvent according to projections provided by the IAM. Unsurprisingly, the study shows that, within a given socio-economic narrative, the climate change mitigation target chosen affects the performance of nearly all activities in the database. This is illustrated by focusing on the effects observed on a few activities, such as systems for direct air capture of CO2, lithium-ion batteries, electricity and clinker production as well as freight transport by road, in relation to the applied sector-based transformation and the chosen climate change mitigation target. This work also discusses the limitations and challenges faced when coupling IAM and LCA databases and what improvements are to be brought in to further facilitate the development of pLCA

PRospective EnvironMental Impact asSEment (premise): A streamlined approach to producing databases for prospective life cycle assessment using integrated assessment models

Prospective Life Cycle Assessment (pLCA) is useful to evaluate the environmental performance of current and emerging technologies in the future. Yet, as energy systems and industries are rapidly shifting towards cleaner means of production, pLCA requires an inventory database that encapsulates the expected changes in technologies and the environment at a given point in time, following specific socio-techno-economic pathways. To this end, this study introduces premise, a tool to streamline the generation of prospective inventory databases for pLCA by integrating scenarios generated by Integrated Assessment Models (IAM). More precisely, premise applies a number of transformations on energy-intensive activities found in the inventory database ecoinvent according to projections provided by the IAM. Unsurprisingly, the study shows that, within a given socio-economic narrative, the climate change mitigation target chosen affects the performance of nearly all activities in the database. This is illustrated by focusing on the effects observed on a few activities, such as systems for direct air capture of CO2, lithium-ion batteries, electricity and clinker production as well as freight transport by road, in relation to the applied sector-based transformation and the chosen climate change mitigation target. This work also discusses the limitations and challenges faced when coupling IAM and LCA databases and what improvements are to be brought in to further facilitate the development of pLCA

PRospective EnvironMental Impact asSEment (premise): A streamlined approach to producing databases for prospective life cycle assessment using integrated assessment models

Prospective Life Cycle Assessment (pLCA) is useful to evaluate the environmental performance of current and emerging technologies in the future. Yet, as energy systems and industries are rapidly shifting towards cleaner means of production, pLCA requires an inventory database that encapsulates the expected changes in technologies and the environment at a given point in time, following specific socio-techno-economic pathways. To this end, this study introduces premise, a tool to streamline the generation of prospective inventory databases for pLCA by integrating scenarios generated by Integrated Assessment Models (IAM). More precisely, premise applies a number of transformations on energy-intensive activities found in the inventory database ecoinvent according to projections provided by the IAM. Unsurprisingly, the study shows that, within a given socio-economic narrative, the climate change mitigation target chosen affects the performance of nearly all activities in the database. This is illustrated by focusing on the effects observed on a few activities, such as systems for direct air capture of CO2, lithium-ion batteries, electricity and clinker production as well as freight transport by road, in relation to the applied sector-based transformation and the chosen climate change mitigation target. This work also discusses the limitations and challenges faced when coupling IAM and LCA databases and what improvements are to be brought in to further facilitate the development of pLCA.ISSN:1364-032