Testable Design and Testing of High-Speed Superconductor Microelectronics

True software-defined radio cellular base stations require extremely fast data converters, which can not currently be implemented in semiconductor technology. Superconductor niobium-based delta ADCs have shown to be able to perform this task. The problem of testing these devices is a severe task, as very little is known about possible defects in this technology. This paper shows an approach for gaining information on these defects and illustrates how BIST can be a solution of detecting defects in ADCs under extreme conditions

Structural testing of the HYPRES Niobium process

The HYPRES 3.0 μm niobium (Nb) process has proven to be capable of realizing complex low temperature superconductor (LTS) rapid single flux quantum (RSFQ) circuits. In such a mature fabrication process, the importance of the detection of random defects is crucial as they contribute to the majority of the defects occurring while processing the chips. The global low yield in superconductor electronics (SCE) is due to the fact that little is known about the defects and fault mechanisms occurring in Nb technology. This is, however, of crucial importance in realizing the required complex systems with yields required for commercial production. For this purpose, a structural testing approach has been applied to the HYPRES Nb process. As a result, we have developed test structures for the detection of random defects in the process. Test chips were realized in the process and measurements were carried out. Test results on the processed chips leading to defect statistics in the HYPRES Nb process are presented in this paper

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Testing Superconductor Logic Integrated Circuits

Superconductor logic has the potential of extremely low-power consumption and ultra-fast digital signal processing. Unfortunately, the obtained yield of the present processes is low and specific faults occur. This paper deals with fault-modelling, Design-for-Test structures, and ATPG for these integrated circuits