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Blind deconvolution of time-of-flight mass spectra from atom probe tomography.

Ultramicroscopy

Johnson LJ, Thuvander M, Stiller K, Odén M, Hultman L.
PMID: 23607992
Ultramicroscopy. 2013 Sep;132:60-4. doi: 10.1016/j.ultramic.2013.03.015. Epub 2013 Mar 29.

A major source of uncertainty in compositional measurements in atom probe tomography stems from the uncertainties of assigning peaks or parts of peaks in the mass spectrum to their correct identities. In particular, peak overlap is a limiting factor,...

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Johnson LJ, Thuvander M, Stiller K, et al. Blind deconvolution of time-of-flight mass spectra from atom probe tomography. Ultramicroscopy. 2013;132:60-4doi: 10.1016/j.ultramic.2013.03.015.
Johnson, L. J., Thuvander, M., Stiller, K., Odén, M., & Hultman, L. (2013). Blind deconvolution of time-of-flight mass spectra from atom probe tomography. Ultramicroscopy, 13260-4. https://doi.org/10.1016/j.ultramic.2013.03.015
Johnson, L J S, et al. "Blind deconvolution of time-of-flight mass spectra from atom probe tomography." Ultramicroscopy vol. 132 (2013): 60-4. doi: https://doi.org/10.1016/j.ultramic.2013.03.015
Johnson LJ, Thuvander M, Stiller K, Odén M, Hultman L. Blind deconvolution of time-of-flight mass spectra from atom probe tomography. Ultramicroscopy. 2013 Sep;132:60-4. doi: 10.1016/j.ultramic.2013.03.015. Epub 2013 Mar 29. PMID: 23607992.
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Reconstructing atom probe data: a review.

Ultramicroscopy

Vurpillot F, Gault B, Geiser BP, Larson DJ.
PMID: 23607993
Ultramicroscopy. 2013 Sep;132:19-30. doi: 10.1016/j.ultramic.2013.03.010. Epub 2013 Mar 26.

Atom probe tomography stands out from other materials characterisation techniques mostly due to its capacity to map individual atoms in three-dimensions with high spatial resolution. The methods used to transform raw detector data into a three-dimensional reconstruction have, comparatively...

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Vurpillot F, Gault B, Geiser BP, et al. Reconstructing atom probe data: a review. Ultramicroscopy. 2013;132:19-30doi: 10.1016/j.ultramic.2013.03.010.
Vurpillot, F., Gault, B., Geiser, B. P., & Larson, D. J. (2013). Reconstructing atom probe data: a review. Ultramicroscopy, 13219-30. https://doi.org/10.1016/j.ultramic.2013.03.010
Vurpillot, Francois, et al. "Reconstructing atom probe data: a review." Ultramicroscopy vol. 132 (2013): 19-30. doi: https://doi.org/10.1016/j.ultramic.2013.03.010
Vurpillot F, Gault B, Geiser BP, Larson DJ. Reconstructing atom probe data: a review. Ultramicroscopy. 2013 Sep;132:19-30. doi: 10.1016/j.ultramic.2013.03.010. Epub 2013 Mar 26. PMID: 23607993.
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Atomic-scale distribution of impurities in CuInSe2-based thin-film solar cells.

Ultramicroscopy

Cojocaru-Mirédin O, Choi P, Wuerz R, Raabe D.
PMID: 21288643
Ultramicroscopy. 2011 May;111(6):552-6. doi: 10.1016/j.ultramic.2010.12.034. Epub 2011 Jan 11.

Atom Probe Tomography was employed to investigate the distribution of impurities, in particular sodium and oxygen, in a CuInSe(2)-based thin-film solar cell. It could be shown that sodium, oxygen, and silicon diffuse from the soda lime glass substrate into...

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Cojocaru-Mirédin O, Choi P, Wuerz R, et al. Atomic-scale distribution of impurities in CuInSe2-based thin-film solar cells. Ultramicroscopy. 2011;111(6):552-6doi: 10.1016/j.ultramic.2010.12.034.
Cojocaru-Mirédin, O., Choi, P., Wuerz, R., & Raabe, D. (2011). Atomic-scale distribution of impurities in CuInSe2-based thin-film solar cells. Ultramicroscopy, 111(6), 552-6. https://doi.org/10.1016/j.ultramic.2010.12.034
Cojocaru-Mirédin, O, et al. "Atomic-scale distribution of impurities in CuInSe2-based thin-film solar cells." Ultramicroscopy vol. 111,6 (2011): 552-6. doi: https://doi.org/10.1016/j.ultramic.2010.12.034
Cojocaru-Mirédin O, Choi P, Wuerz R, Raabe D. Atomic-scale distribution of impurities in CuInSe2-based thin-film solar cells. Ultramicroscopy. 2011 May;111(6):552-6. doi: 10.1016/j.ultramic.2010.12.034. Epub 2011 Jan 11. PMID: 21288643.
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Atom-probe for FinFET dopant characterization.

Ultramicroscopy

Kambham AK, Mody J, Gilbert M, Koelling S, Vandervorst W.
PMID: 21288644
Ultramicroscopy. 2011 May;111(6):535-9. doi: 10.1016/j.ultramic.2011.01.017. Epub 2011 Jan 18.

With the continuous shrinking of transistors and advent of new transistor architectures to keep in pace with Moore's law and ITRS goals, there is a rising interest in multigate 3D-devices like FinFETs where the channel is surrounded by gates...

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Kambham AK, Mody J, Gilbert M, et al. Atom-probe for FinFET dopant characterization. Ultramicroscopy. 2011;111(6):535-9doi: 10.1016/j.ultramic.2011.01.017.
Kambham, A. K., Mody, J., Gilbert, M., Koelling, S., & Vandervorst, W. (2011). Atom-probe for FinFET dopant characterization. Ultramicroscopy, 111(6), 535-9. https://doi.org/10.1016/j.ultramic.2011.01.017
Kambham, A K, et al. "Atom-probe for FinFET dopant characterization." Ultramicroscopy vol. 111,6 (2011): 535-9. doi: https://doi.org/10.1016/j.ultramic.2011.01.017
Kambham AK, Mody J, Gilbert M, Koelling S, Vandervorst W. Atom-probe for FinFET dopant characterization. Ultramicroscopy. 2011 May;111(6):535-9. doi: 10.1016/j.ultramic.2011.01.017. Epub 2011 Jan 18. PMID: 21288644.
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In situ electron holographic study of Ionic liquid.

Ultramicroscopy

Shirai M, Tanigaki T, Aizawa S, Park HS, Matsuda T, Shindo D.
PMID: 25171751
Ultramicroscopy. 2014 Nov;146:125-9. doi: 10.1016/j.ultramic.2014.08.003. Epub 2014 Aug 10.

Investigation of the effect of electron irradiation on ionic liquid (IL) droplets using electron holography revealed that electron irradiation changed the electrostatic potential around the IL. The potential for low electron flux irradiation (0.5 × 10(17)e/m(2)s) was almost constant...

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Shirai M, Tanigaki T, Aizawa S, et al. In situ electron holographic study of Ionic liquid. Ultramicroscopy. 2014;146:125-9doi: 10.1016/j.ultramic.2014.08.003.
Shirai, M., Tanigaki, T., Aizawa, S., Park, H. S., Matsuda, T., & Shindo, D. (2014). In situ electron holographic study of Ionic liquid. Ultramicroscopy, 146125-9. https://doi.org/10.1016/j.ultramic.2014.08.003
Shirai, Manabu, et al. "In situ electron holographic study of Ionic liquid." Ultramicroscopy vol. 146 (2014): 125-9. doi: https://doi.org/10.1016/j.ultramic.2014.08.003
Shirai M, Tanigaki T, Aizawa S, Park HS, Matsuda T, Shindo D. In situ electron holographic study of Ionic liquid. Ultramicroscopy. 2014 Nov;146:125-9. doi: 10.1016/j.ultramic.2014.08.003. Epub 2014 Aug 10. PMID: 25171751.
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Design of an ultra-miniaturized electron optical microcolumn with sub-5 nm very high resolution.

Ultramicroscopy

Oh TS, Kim HS, Ahn S, Kim DW.
PMID: 24184680
Ultramicroscopy. 2014 Jan;136:171-5. doi: 10.1016/j.ultramic.2013.10.003. Epub 2013 Oct 17.

The achievement of a microminiaturized electrostatic electron optical column with very-high-resolution probe beam is an important challenge in the fields of electron beam lithography, metrology, and inspection for semiconductor and/or display devices. In this study, we propose an ultra-miniaturized,...

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Oh TS, Kim HS, Ahn S, et al. Design of an ultra-miniaturized electron optical microcolumn with sub-5 nm very high resolution. Ultramicroscopy. 2013;136:171-5doi: 10.1016/j.ultramic.2013.10.003.
Oh, T. S., Kim, H. S., Ahn, S., & Kim, D. W. (2014). Design of an ultra-miniaturized electron optical microcolumn with sub-5 nm very high resolution. Ultramicroscopy, 136171-5. https://doi.org/10.1016/j.ultramic.2013.10.003
Oh, Tae-Sik, et al. "Design of an ultra-miniaturized electron optical microcolumn with sub-5 nm very high resolution." Ultramicroscopy vol. 136 (2014): 171-5. doi: https://doi.org/10.1016/j.ultramic.2013.10.003
Oh TS, Kim HS, Ahn S, Kim DW. Design of an ultra-miniaturized electron optical microcolumn with sub-5 nm very high resolution. Ultramicroscopy. 2014 Jan;136:171-5. doi: 10.1016/j.ultramic.2013.10.003. Epub 2013 Oct 17. PMID: 24184680.
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StatSTEM: An efficient approach for accurate and precise model-based quantification of atomic resolution electron microscopy images.

Ultramicroscopy

De Backer A, van den Bos KHW, Van den Broek W, Sijbers J, Van Aert S.
PMID: 27657649
Ultramicroscopy. 2016 Dec;171:104-116. doi: 10.1016/j.ultramic.2016.08.018. Epub 2016 Aug 31.

An efficient model-based estimation algorithm is introduced to quantify the atomic column positions and intensities from atomic resolution (scanning) transmission electron microscopy ((S)TEM) images. This algorithm uses the least squares estimator on image segments containing individual columns fully accounting...

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De Backer A, van den Bos KHW, Van den Broek W, et al. StatSTEM: An efficient approach for accurate and precise model-based quantification of atomic resolution electron microscopy images. Ultramicroscopy. 2016;171:104-116doi: 10.1016/j.ultramic.2016.08.018.
De Backer, A., van den Bos, K. H. W., Van den Broek, W., Sijbers, J., & Van Aert, S. (2016). StatSTEM: An efficient approach for accurate and precise model-based quantification of atomic resolution electron microscopy images. Ultramicroscopy, 171104-116. https://doi.org/10.1016/j.ultramic.2016.08.018
De Backer, A, et al. "StatSTEM: An efficient approach for accurate and precise model-based quantification of atomic resolution electron microscopy images." Ultramicroscopy vol. 171 (2016): 104-116. doi: https://doi.org/10.1016/j.ultramic.2016.08.018
De Backer A, van den Bos KHW, Van den Broek W, Sijbers J, Van Aert S. StatSTEM: An efficient approach for accurate and precise model-based quantification of atomic resolution electron microscopy images. Ultramicroscopy. 2016 Dec;171:104-116. doi: 10.1016/j.ultramic.2016.08.018. Epub 2016 Aug 31. PMID: 27657649.
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Compressed sensing for STEM tomography.

Ultramicroscopy

Donati L, Nilchian M, Trépout S, Messaoudi C, Marco S, Unser M.
PMID: 28411510
Ultramicroscopy. 2017 Aug;179:47-56. doi: 10.1016/j.ultramic.2017.04.003. Epub 2017 Apr 06.

A central challenge in scanning transmission electron microscopy (STEM) is to reduce the electron radiation dosage required for accurate imaging of 3D biological nano-structures. Methods that permit tomographic reconstruction from a reduced number of STEM acquisitions without introducing significant...

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Donati L, Nilchian M, Trépout S, et al. Compressed sensing for STEM tomography. Ultramicroscopy. 2017;179:47-56doi: 10.1016/j.ultramic.2017.04.003.
Donati, L., Nilchian, M., Trépout, S., Messaoudi, C., Marco, S., & Unser, M. (2017). Compressed sensing for STEM tomography. Ultramicroscopy, 17947-56. https://doi.org/10.1016/j.ultramic.2017.04.003
Donati, Laurène, et al. "Compressed sensing for STEM tomography." Ultramicroscopy vol. 179 (2017): 47-56. doi: https://doi.org/10.1016/j.ultramic.2017.04.003
Donati L, Nilchian M, Trépout S, Messaoudi C, Marco S, Unser M. Compressed sensing for STEM tomography. Ultramicroscopy. 2017 Aug;179:47-56. doi: 10.1016/j.ultramic.2017.04.003. Epub 2017 Apr 06. PMID: 28411510.
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Mapping buried nanostructures using subsurface ultrasonic resonance force microscopy.

Ultramicroscopy

van Es MH, Mohtashami A, Thijssen RMT, Piras D, van Neer PLMJ, Sadeghian H.
PMID: 28968522
Ultramicroscopy. 2018 Jan;184:209-216. doi: 10.1016/j.ultramic.2017.09.005. Epub 2017 Sep 23.

Nondestructive subsurface nanoimaging of buried nanostructures is considered to be extremely challenging and is essential for the reliable manufacturing of nanotechnology products such as three-dimensional (3D) transistors, 3D NAND memory, and future quantum electronics. In scanning probe microscopy (SPM),...

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van Es MH, Mohtashami A, Thijssen RMT, et al. Mapping buried nanostructures using subsurface ultrasonic resonance force microscopy. Ultramicroscopy. 2017;184:209-216doi: 10.1016/j.ultramic.2017.09.005.
van Es, M. H., Mohtashami, A., Thijssen, R. M. T., Piras, D., van Neer, P. L. M. J., & Sadeghian, H. (2018). Mapping buried nanostructures using subsurface ultrasonic resonance force microscopy. Ultramicroscopy, 184209-216. https://doi.org/10.1016/j.ultramic.2017.09.005
van Es, Maarten H, et al. "Mapping buried nanostructures using subsurface ultrasonic resonance force microscopy." Ultramicroscopy vol. 184 (2018): 209-216. doi: https://doi.org/10.1016/j.ultramic.2017.09.005
van Es MH, Mohtashami A, Thijssen RMT, Piras D, van Neer PLMJ, Sadeghian H. Mapping buried nanostructures using subsurface ultrasonic resonance force microscopy. Ultramicroscopy. 2018 Jan;184:209-216. doi: 10.1016/j.ultramic.2017.09.005. Epub 2017 Sep 23. PMID: 28968522.
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Sparse modeling of EELS and EDX spectral imaging data by nonnegative matrix factorization.

Ultramicroscopy

Shiga M, Tatsumi K, Muto S, Tsuda K, Yamamoto Y, Mori T, Tanji T.
PMID: 27529804
Ultramicroscopy. 2016 Nov;170:43-59. doi: 10.1016/j.ultramic.2016.08.006. Epub 2016 Aug 06.

Advances in scanning transmission electron microscopy (STEM) techniques have enabled us to automatically obtain electron energy-loss (EELS)/energy-dispersive X-ray (EDX) spectral datasets from a specified region of interest (ROI) at an arbitrary step width, called spectral imaging (SI). Instead of...

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Shiga M, Tatsumi K, Muto S, et al. Sparse modeling of EELS and EDX spectral imaging data by nonnegative matrix factorization. Ultramicroscopy. 2016;170:43-59doi: 10.1016/j.ultramic.2016.08.006.
Shiga, M., Tatsumi, K., Muto, S., Tsuda, K., Yamamoto, Y., Mori, T., & Tanji, T. (2016). Sparse modeling of EELS and EDX spectral imaging data by nonnegative matrix factorization. Ultramicroscopy, 17043-59. https://doi.org/10.1016/j.ultramic.2016.08.006
Shiga, Motoki, et al. "Sparse modeling of EELS and EDX spectral imaging data by nonnegative matrix factorization." Ultramicroscopy vol. 170 (2016): 43-59. doi: https://doi.org/10.1016/j.ultramic.2016.08.006
Shiga M, Tatsumi K, Muto S, Tsuda K, Yamamoto Y, Mori T, Tanji T. Sparse modeling of EELS and EDX spectral imaging data by nonnegative matrix factorization. Ultramicroscopy. 2016 Nov;170:43-59. doi: 10.1016/j.ultramic.2016.08.006. Epub 2016 Aug 06. PMID: 27529804.
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Numerical modeling of specimen geometry for quantitative energy dispersive X-ray spectroscopy.

Ultramicroscopy

Xu W, Dycus JH, LeBeau JM.
PMID: 28886487
Ultramicroscopy. 2018 Jan;184:100-108. doi: 10.1016/j.ultramic.2017.08.015. Epub 2017 Sep 01.

Transmission electron microscopy specimens typically exhibit local distortion at thin foil edges, which can influence the absorption of X-rays for quantitative energy dispersive X-ray spectroscopy (EDS). Here, we report a numerical, three-dimensional approach to model the geometry of general...

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Xu W, Dycus JH, LeBeau JM. Numerical modeling of specimen geometry for quantitative energy dispersive X-ray spectroscopy. Ultramicroscopy. 2017;184:100-108doi: 10.1016/j.ultramic.2017.08.015.
Xu, W., Dycus, J. H., & LeBeau, J. M. (2018). Numerical modeling of specimen geometry for quantitative energy dispersive X-ray spectroscopy. Ultramicroscopy, 184100-108. https://doi.org/10.1016/j.ultramic.2017.08.015
Xu, W, et al. "Numerical modeling of specimen geometry for quantitative energy dispersive X-ray spectroscopy." Ultramicroscopy vol. 184 (2018): 100-108. doi: https://doi.org/10.1016/j.ultramic.2017.08.015
Xu W, Dycus JH, LeBeau JM. Numerical modeling of specimen geometry for quantitative energy dispersive X-ray spectroscopy. Ultramicroscopy. 2018 Jan;184:100-108. doi: 10.1016/j.ultramic.2017.08.015. Epub 2017 Sep 01. PMID: 28886487.
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Applications and limitations of electron correlation microscopy to study relaxation dynamics in supercooled liquids.

Ultramicroscopy

Zhang P, He L, Besser MF, Liu Z, Schroers J, Kramer MJ, Voyles PM.
PMID: 27638332
Ultramicroscopy. 2017 Jul;178:125-130. doi: 10.1016/j.ultramic.2016.09.001. Epub 2016 Sep 08.

Electron correlation microscopy (ECM) is a way to measure structural relaxation times, τ, of liquids with nanometer-scale spatial resolution using coherent electron scattering equivalent of photon correlation spectroscopy. We have applied ECM with a 3.5nm diameter probe to Pt

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Zhang P, He L, Besser MF, et al. Applications and limitations of electron correlation microscopy to study relaxation dynamics in supercooled liquids. Ultramicroscopy. 2016;178:125-130doi: 10.1016/j.ultramic.2016.09.001.
Zhang, P., He, L., Besser, M. F., Liu, Z., Schroers, J., Kramer, M. J., & Voyles, P. M. (2017). Applications and limitations of electron correlation microscopy to study relaxation dynamics in supercooled liquids. Ultramicroscopy, 178125-130. https://doi.org/10.1016/j.ultramic.2016.09.001
Zhang, Pei, et al. "Applications and limitations of electron correlation microscopy to study relaxation dynamics in supercooled liquids." Ultramicroscopy vol. 178 (2017): 125-130. doi: https://doi.org/10.1016/j.ultramic.2016.09.001
Zhang P, He L, Besser MF, Liu Z, Schroers J, Kramer MJ, Voyles PM. Applications and limitations of electron correlation microscopy to study relaxation dynamics in supercooled liquids. Ultramicroscopy. 2017 Jul;178:125-130. doi: 10.1016/j.ultramic.2016.09.001. Epub 2016 Sep 08. PMID: 27638332.
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Showing 1 to 12 of 3331 entries