Technology transfer utilizing the proof-of-concept facility

Author(s):  
R.D. Fair ◽  
J.F. Freedman
2018 ◽  
Vol 32 (5) ◽  
pp. 312-325 ◽  
Author(s):  
Mariacarmela Passarelli ◽  
Alfio Cariola ◽  
Pino Vecellio

This article focuses on co-development technology transfer models. It offers an empirical analysis of a pioneer model applied in Italy: the proof-of-concept network (PoCN) applied by AREA Science Park in Trieste. Starting with a review of the literature, the authors identify the drivers that facilitate collaboration between the industrial and research systems in the embryonic phase of technology development. Then, discussing the PoCN model, the article analyzes and explores an emerging phenomenon that is as yet poorly understood. The application of a model for co-development, in fact, highlights many advantages for both firms and the research system and improves the efficiency of matching between these distant and heterogeneous sectors. The authors report a single case study which, while appearing to be a limitation of the article, offers elements of originality because it concerns the first applied co-development model in Italy. There are many practical implications, not only for firms and research institutions but also for policymakers who seek to implement public policies to support innovation and technology transfer.


2020 ◽  
Author(s):  
Zachary Arnold ◽  
Rebecca Gelles ◽  
Ilya Rahkovsky

Artificial intelligence is of increasing interest to the private sector, but what exactly constitutes an “AI company?” This data brief offers a flexible, data-driven framework for identifying the companies most relevant in this field at the moment, providing policymakers and researchers with a tool for mapping technology transfer risks and gauging the overall health of America’s AI sector.


Author(s):  
A. G. Jackson ◽  
M. Rowe

Diffraction intensities from intermetallic compounds are, in the kinematic approximation, proportional to the scattering amplitude from the element doing the scattering. More detailed calculations have shown that site symmetry and occupation by various atom species also affects the intensity in a diffracted beam. [1] Hence, by measuring the intensities of beams, or their ratios, the occupancy can be estimated. Measurement of the intensity values also allows structure calculations to be made to determine the spatial distribution of the potentials doing the scattering. Thermal effects are also present as a background contribution. Inelastic effects such as loss or absorption/excitation complicate the intensity behavior, and dynamical theory is required to estimate the intensity value.The dynamic range of currents in diffracted beams can be 104or 105:1. Hence, detection of such information requires a means for collecting the intensity over a signal-to-noise range beyond that obtainable with a single film plate, which has a S/N of about 103:1. Although such a collection system is not available currently, a simple system consisting of instrumentation on an existing STEM can be used as a proof of concept which has a S/N of about 255:1, limited by the 8 bit pixel attributes used in the electronics. Use of 24 bit pixel attributes would easily allowthe desired noise range to be attained in the processing instrumentation. The S/N of the scintillator used by the photoelectron sensor is about 106 to 1, well beyond the S/N goal. The trade-off that must be made is the time for acquiring the signal, since the pattern can be obtained in seconds using film plates, compared to 10 to 20 minutes for a pattern to be acquired using the digital scan. Parallel acquisition would, of course, speed up this process immensely.


2002 ◽  
Author(s):  
Sheri Yvonne Nottestad Boyd ◽  
Linda L. Huffer ◽  
Terry D. Bauch ◽  
James L. Furgerson

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