Design space for low sensitivity to size variations in [110] PMOS nanowire devices: The implications of anisotropy in the quantization mass

A 20-band sp3d5s* spin-orbit-coupled, semi-empirical, atomistic tight-binding model is used with a semi-classical, ballistic, field-effect-transistor (FET) model, to examine the ON-current variations to size variations of [110] oriented PMOS nanowire devices. Infinitely long, uniform, rectangular nanowires of side dimensions from 3nm to 12nm are examined and significantly different behavior in width vs. height variations are identified and explained. Design regions are identified, which show minor ON-current variations to significant width variations that might occur due to lack of line width control. Regions which show large ON-current variations to small height variations are also identified. The considerations of the full band model here show that ON-current doubling can be observed in the ON-state at the onset of volume inversion to surface inversion transport caused by structural side size variations. Strain engineering can smooth out or tune such sensitivities to size variations. The cause of variations described is the structural quantization behavior of the nanowires, which provide an additional variation mechanism to any other ON-current variations such as surface roughness, phonon scattering etc.Comment: 24 pages, 5 figure

Cloud computing in nanoHUB powering education and research

If you had access to interactive modeling and simulation tools that run in any browser, could you introduce interactive learning into your classes? If you had easy access tools, which need no installation, could you use them to help guide your experiments? If you did not have to worry about compute cycles, would you benchmark your own tools against other state-of-the-art approaches? If you had your own tools and could easily share them with the community, would you do it? This short course will provide an overview of these processes and their impact as they are supported on nanoHUB.org today. If you have never been on nanoHUB.org, learn how it might help you; if you have used it, learn about new and upcoming features and share your story with the nanoHUB team and other participants. Annually, nanoHUB provides a library of 3000+ learning resources to 330,000+ users worldwide. Its 340+ simulation tools, free from the limitations of running software locally, are used in the cloud by over 13,000 annually. Its impact is demonstrated by 1100+ citations to nanoHUB in the scientific literature with over 14,000 secondary citations, yielding an h-index of 57, and by a median time from publication of a research simulation program to classroom use of Cumulatively, ~22,000 students in over 1000 formal classes in over 185 institutions have used nanoHUB simulations. nanoHUB.org is a virtual nanotechnology user facility funded by the National Science Foundation and supports the National Nanotechnology Initiative with a highly successful cyber-infrastructure. nanoHUB.org has been supported by the NSF for 12 years and funding was awarded for another 5 plus 5 years in 2012

Mythbusting scientific knowledge transfer with nanoHUB.org

Gordon Moore’s 1965 prediction of continued semiconductor device down-scaling and circuit up-scaling has become a self-fulfilling prophesy in the past 40 years. Open source code development and sharing of the process modeling software SUPREM and the circuit modeling software SPICE were two critical technologies that enabled the down-scaling of semiconductor devices and up-scaling of circuit complexity. SPICE was originally a teaching tool that transitioned into a research tool, was disseminated by an inspired engineering professor via tapes, and improved by users who provided constructive feedback to a multidisciplinary group of electrical engineers, physicist, and numerical analysts. Ultimately SPICE and SUPREM transitioned into all electronic design software packages that power today’s 280 billion dollar semiconductor industry. Can we duplicate such multidisciplinary software development starting from teaching and research in a small research group leading to true economic impact? What are technologies that might advance such a process? How can we deliver such software to a broad audience? How can we teach the next generation engineers and scientists on the latest research software? What are critical user requirements? What are critical developer requirements? What are the incentives for faculty members to share their competitive advantages? Can real research be conducted in such a web portal? How do we know early on if such an infrastructure is successful? Can one really transfer knowledge from computational science to other areas or research and into education? This presentation will bust some of the myths and perceptions of what is possible and impossible. By serving a community of over 320,000 users in the past 12 months with an ever-growing collection of 3,400 resources, including over 340 simulation tools, nanoHUB.org has established itself as “the world’s largest nanotechnology user facility”[1]. nanoHUB.org is driving significant knowledge transfer among researchers and speeding transfer from research to education, quantified with usage statistics, usage patterns, collaboration patterns, and citation data from the scientific literature. Over 1,100 nanoHUB citations in the literature resulting in a secondary citation h-index of 57 prove that high quality research by users outside of the pool of original tool developers can be enabled by nanoHUB processes. In addition to high-quality content, critical attributes of nanoHUB success are its open access, ease of use, utterly dependable operation, low-cost and rapid content adaptation and deployment, and open usage and assessment data. The open-source HUBzero software platform, built for nanoHUB and now powering many other hubs, is architected to deliver a user experience corresponding to these criteria. Gerhard Klimeck is the Director of the Network for Computational Nanotechnology and Professor of Electrical and Computer Engineering at Purdue University. He was earlier with NASA/JPL and Texas Instruments leading the Nanoelectronic Modeling Tool development -. His work is documented in over 380 peer-reviewed journal and proceedings articles and over 210 invited and 400 contributed conference presentations. He is a fellow of the IEEE, American Physical Society, and the Institute of Physics. REFERENCE [1] Quote by Mikhail Roco, Senior Advisor for Nanotechnology, National Science Foundation

Influence of cross-section geometry and wire orientation on the phonon shifts in ultra-scaled Si nanowires

Engineering of the cross-section shape and size of ultra-scaled Si nanowires (SiNWs) provides an attractive way for tuning their structural properties. The acoustic and optical phonon shifts of the free-standing circular, hexagonal, square and triangular SiNWs are calculated using a Modified Valence Force Field (MVFF) model. The acoustic phonon blue shift (acoustic hardening) and the optical phonon red shift (optical softening) show a strong dependence on the cross-section shape and size of the SiNWs. The triangular SiNWs have the least structural symmetry as revealed by the splitting of the degenerate flexural phonon modes and The show the minimum acoustic hardening and the maximum optical hardening. The acoustic hardening, in all SiNWs, is attributed to the decreasing difference in the vibrational energy distribution between the inner and the surface atoms with decreasing cross-section size. The optical softening is attributed to the reduced phonon group velocity and the localization of the vibrational energy density on the inner atoms. While the acoustic phonon shift shows a strong wire orientation dependence, the optical phonon softening is independent of wire orientation.Comment: 10 figures, 4 Tables, submitted to JAP for revie

Program for User-Friendly Management of Input and Output Data Sets

A computer program manages large, hierarchical sets of input and output (I/O) parameters (typically, sequences of alphanumeric data) involved in computational simulations in a variety of technological disciplines. This program represents sets of parameters as structures coded in object-oriented but otherwise standard American National Standards Institute C language. Each structure contains a group of I/O parameters that make sense as a unit in the simulation program with which this program is used. The addition of options and/or elements to sets of parameters amounts to the addition of new elements to data structures. By association of child data generated in response to a particular user input, a hierarchical ordering of input parameters can be achieved. Associated with child data structures are the creation and description mechanisms within the parent data structures. Child data structures can spawn further child data structures. In this program, the creation and representation of a sequence of data structures is effected by one line of code that looks for children of a sequence of structures until there are no more children to be found. A linked list of structures is created dynamically and is completely represented in the data structures themselves. Such hierarchical data presentation can guide users through otherwise complex setup procedures and it can be integrated within a variety of graphical representations

Effects of Interface Disorder on Valley Splitting in SiGe/Si/SiGe Quantum Wells

A sharp potential barrier at the Si/SiGe interface introduces valley splitting (VS), which lifts the 2-fold valley degeneracy in strained SiGe/Si/SiGe quantum wells (QWs). This work examines in detail the effects of Si/SiGe interface disorder on the VS in an atomistic tight binding approach based on statistical sampling. VS is analyzed as a function of electric field, QW thickness, and simulation domain size. Strong electric fields push the electron wavefunctions into the SiGe buffer and introduce significant VS fluctuations from device to device. A Gedankenexperiment with ordered alloys sheds light on the importance of different bonding configurations on VS. We conclude that a single SiGe band offset and effective mass cannot comprehend the complex Si/SiGe interface interactions that dominate VS.Comment: 5 figure