Featured Research Highlights
Liquid Water Vibrates Slower When Confined at the Nanoscale
Scientific Achievement (A) Illustration of “aloof” EELS (beam positioned ~10nm from sample to prevent radiation damage) of BN-encapsulated liquid cell; (B) EEL spectra showing the difference between O-H and O-D modes as well as lowering of the...
Understanding Nanoscale Electromechanical Energy Conversion with Machine Learning
Scientific Achievement The experiments utilized band-excitation piezoresponse spectroscopy, a tool developed at the CNMS, to unravel the role of domain geometry on ferroelectric and ferroelastic switching. A machine learning method enables...
A scanning tunneling microscope (STM) tip is used to write and erase (move) individual vacancies on a crystalline lattice in multiple layers of PdSe2, and then to switch the charge state of the defect.
G. D. Nguyen, L. Liang, Q. Zou, M. Fu, A. D. Oyedele, B. G. Sumpter, Z. Liu, Z. Gai, K. Xiao, and A.-P. Li, "3D imaging and manipulation of subsurface selenium vacancies in PdSe2," Phys. Rev. Lett. 121, 086101 (2018). DOI: 10.1103/PhysRevLett.121.086101
Using the ORNL Monochromated Aberration-Corrected Scanning Transmission Electron Microscope (MAC-STEM), Robert Klie, Juan Carlos Idrobo, and co-workers show that electron energy loss spectroscopy (EELS) can distinguish between hydrogen and deuterium vibrational modes. They also observe that encapsulating a small volume of water between boron nitride (BN) monolayers slows down these hydrogen modes.
J. R. Jokisaari, J. A. Hachtel, X. Hu, A. Mukherjee, C. Wang, A. Konecna, T. C. Lovejoy, N. Dellby, J. Aizpurua, O. L. Krivanek, J. C. Idrobo, and R. F. Klie, "Vibrational spectroscopy of water with high spatial resolution," Advanced Materials (2018). DOI: 10.1002/adma.201802702
Scanning probe measurements of ferroelectric switching greatly benefit from machine learning.
J. C. Agar, Y. Cao, B. Naul, S. Pandya, S. van der Walt, A. I. Luo, J. T. Maher, N. Balke, S. Jesse, S. V. Kalinin, R. K. Vasudevan. and L. W. Martin, "Machine detection of enhanced electromechanical energy conversion in PbZr0.2Ti0.8O3 thin films," Advanced Materials (2018). DOI: 10.1002/adma.201800701
Machine Learning Integrated with Acoustic Sensors Enables an Efficient and Deep Analysis of the Quality and Safety of Milk
Machine learning made it possible to improve the sensitivity of a microbalance-based approach to sub-nanomolar sensitivity.
M. Tatarko, E. S. Muckley, V. Subjakova, M. Goswami, B. G. Sumpter, T. Hianik, and I. N. Ivanov, "Machine learning enabled acoustic detection of sub-nanomolar concentration of trypsin and plasmin in solution," Sensors & Actuators: B. Chem. 272, 282 (2018). DOI: 10.1016/j.snb.2018.05.100
This paper reveals the growth of single layer transition metal carbides on MXene surfaces.
X. Sang, Y. Xie, D. E. Yilmaz, R. Lotfi, M. Alhabeb, A. Ostadhossein, B. Anasori, W. Sun, X. Li, Kai Xiao, P. R.C. Kent, A. van Duin, Y. Gogotsi, and R. R. Unocic, "In situ atomistic insight into the growth mechanisms of single layer 2D transition metal carbides," Nature Commun. 9, 2266 (2018). DOI:10.1038/s41467-018-04610-0
In-situ STEM initiates and reveals the formation of edges in Mo1-xWxSe2.
X. Sang, X. Li, W. Zhao, J. Dong, C. M. Rouleau, D. B. Geohegan, F. Ding, K. Xiao, and R. R. Unocic, "In situ edge engineering in two-dimensional transition metal dichalcogen Nature Commun. 9, Article 2051, (2018). DOI: 10.1038/s41467-018-04435-x
Atomic Force Microscopy Reveals How Structural Water Makes A Battery Material More Efficient at Storing Energy
A new nm-scale method to observe energy storage electrochemistry shows the importance of structural water.
R. Wang, J. B. Mitchell, Q. Gao, W.-Y. Tsai, S. Boyd, M. Pharr, N. Balke, and V. Augustyn, "Operando atomic force microscopy reveals mechanics of structural water driven battery-to-pseuocapacitor transition," ACS Nano 12, 6032, (2018). DOI: 10.1021/acsnano.8b02273
Synthetic biomembranes were doped with voltage-activated alamethicin pepties to yield two-terminal devices with properties resembling biological synapses.
J. S. Najem, G. J. Taylor, R. J. Weiss, Md. S. Hasan, G. Rose, C. D. Schuman, A. Belianinov, C. P Collier, and S. A. Sarles, "Memristive ion channel-doped biomembranes as synaptic mimics," ACS Nano 12, 4702 (2018). DOI: 10.1021/acsnano.8b01282
Atom probe tomography shows that K substitution for Cu directly reduces unwanted defects – thus improves solar cell performance.
C.P. Muzzillo, J.D. Poplawsky, H.M. Tong, and T. Anderson, "Revealing the beneficial role of K in grain interiors, grain boundaries, and at the buffer interface for highly efficient CuInSe2 solar cells," Prog Photovolt.Res. Appl. 1-10 (2018). DOI: 10.1002/pip.3022