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| 1 | Deep learning analysis of defect and phase evolution during electron beam-induced transformations in WS_(2)显示文摘Recent advances in scanning transmission electron microscopy(STEM)allow the real-time visualization of solid-state transformations in materials,including those induced by an electron beam and temperature,with atomic resolution.However,despite the ever-expanding capabilities for high-resolution data acquisition,the inferred information about kinetics and thermodynamics of the process,and single defect dynamics and interactions is minimal.This is due to the inherent limitations of manual ex situ analysis of the collected volumes of data.To circumvent this problem,we developed a deep-learning framework for dynamic STEM imaging that is trained to find the lattice defects and apply it for mapping solid state reactions and transformations in layered WS_(2).The trained deep-learning model allows extracting thousands of lattice defects from raw STEM data in a matter of seconds,which are then classified into different categories using unsupervised clustering methods.We further expanded our framework to extract parameters of diffusion for sulfur vacancies and analyzed transition probabilities associated with switching between different configurations of defect complexes consisting of Mo dopant and sulfur vacancy,providing insight into pointdefect dynamics and reactions.This approach is universal and its application to beam-induced reactions allows mapping chemical transformation pathways in solids at the atomic level. | Artem Maksov Ondrej Dyck Kai Wang Kai Xiao David B.Geohegan Bobby G.Sumpter Rama K.Vasudevan Stephen Jesse Sergei V.Kalinin Maxim Ziatdinov | 2019 | npj Computational Materials2019，，1： | 11 |
| 2 | Mapping mesoscopic phase evolution during E-beam induced transformations via deep learning of atomically resolved images显示文摘Understanding transformations under electron beam irradiation requires mapping the structural phases and their evolution in real time.To date,this has mostly been a manual endeavor comprising difficult frame-by-frame analysis that is simultaneously tedious and prone to error.Here,we turn toward the use of deep convolutional neural networks(DCNN)to automatically determine the Bravais lattice symmetry present in atomically resolved images.A DCNN is trained to identify the Bravais lattice class given a 2D fast Fourier transform of the input image.Monte-Carlo dropout is used for determining the prediction probability,and results are shown for both simulated and real atomically resolved images from scanning tunneling microscopy and scanning transmission electron microscopy.A reduced representation of the final layer output allows to visualize the separation of classes in the DCNN and agrees with physical intuition.We then apply the trained network to electron beam-induced transformations in WS2,which allows tracking and determination of growth rate of voids.We highlight two key aspects of these results:(1)it shows that DCNNs can be trained to recognize diffraction patterns,which is markedly different from the typical“real image”cases and(2)it provides a method with inbuilt uncertainty quantification,allowing the real-time analysis of phases present in atomically resolved images. | Rama K.Vasudevan Nouamane Laanait Erik M.Ferragut Kai Wang David B.Geohegan Kai Xiao Maxim Ziatdinov Stephen Jesse Ondrej Dyck Sergei V.Kalinin | 2018 | npj Computational Materials2018，，1： | 5 |
| 3 | Manifold learning of four-dimensional scanning transmission electron microscopy显示文摘Four-dimensional scanning transmission electron microscopy(4D-STEM)of local atomic diffraction patterns is emerging as a powerful technique for probing intricate details of atomic structure and atomic electric fields.However,efficient processing and interpretation of large volumes of data remain challenging,especially for two-dimensional or light materials because the diffraction signal recorded on the pixelated arrays is weak.Here we employ data-driven manifold leaning approaches for straightforward visualization and exploration analysis of 4D-STEM datasets,distilling real-space neighboring effects on atomically resolved deflection patterns from single-layer graphene,with single dopant atoms,as recorded on a pixelated detector.These extracted patterns relate to both individual atom sites and sublattice structures,effectively discriminating single dopant anomalies via multimode views.We believe manifold learning analysis will accelerate physics discoveries coupled between data-rich imaging mechanisms and materials such as ferroelectric,topological spin,and van der Waals heterostructures. | Xin Li Ondrej E.Dyck Mark P.Oxley Andrew R.Lupini Leland McInnes John Healy Stephen Jesse Sergei V.Kalinin | 2019 | npj Computational Materials2019，，1： | 4 |
| 4 | Urinary NMR metabolomic profiles discriminate inflammatory bowel disease from healthy显示文摘 | Natasha S. Stephens Jesse Siffledeen Xiaorong Su Travis B. Murdoch Richard N. Fedorak Carolyn M. Slupsky | 2012 | Journal of Crohn’s and Colitis2012，，： | 4 |
| 5 | Time scales and length scales in magma ?ow pathways and the origin ofmagmatic Ni-Cu-PGE ore deposits显示文摘Ore forming processes involve the redistribution of heat, mass and momentum by a wide range of processes operating at different time and length scales. The fastest process at any given length scale tends to be the dominant control. Applying this principle to the array of physical processes that operate within magma flow pathways leads to some key insights into the origins of magmatic Ni-Cu-PGE sulfide ore deposits. A high proportion of mineralised systems, including those in the super-giant Noril'sk-Talnakh camp, are formed in small conduit intrusions where assimilation of country rock has played a major role. Evidence of this process is reflected in the common association of sulfides with varitextured contaminated host rocks containing xenoliths in varying stages of assimilation. Direct incorporation of S-bearing country rock xenoliths is likely to be the dominant mechanism for generating sulfide liquids in this setting. However, the processes of melting or dissolving these xenoliths is relatively slow compared with magma flow rates and, depending on xenolith lithology and the composition of the carrier magma, slow compared with settling and accumulation rates. Chemical equilibration between sulfide droplets and silicate magma is slower still, as is the process of dissolving sulfide liquid into initially undersaturated silicate magmas. Much of the transport and deposition of sulfide in the carrier magmas may occur while sulfide is still incorporated in the xenoliths, accounting for the common association of magmatic sulfide-matrix ore breccias and contaminated 'taxitic' host rocks. Effective upgrading of so-formed sulfide liquids would require repetitive recycling by processes such as reentrainment, back flow or gravity flow operating over the lifetime of the magma transport system as a whole. In contrast to mafic-hosted systems, komatiite-hosted ores only rarely show an association with externally-derived xenoliths, an observation which is partially due to the predominant formation of ores in lava flows rather than deep-seated intrusions, but also to the much shorter timescales of key component systems in hotter, less viscous magmas. Nonetheless, multiple cycles of deposition and entrainment are necessary to account for the metal contents of komatiite-hosted sulfides. More generally, the time and length scale approach introduced here may be of value in understanding other igneous processes as well as non-magmatic mineral systems. | Stephen J.Barnes Jesse C.Robertson | 2019 | Geoscience Frontiers2019，10，1： | 4 |
| 6 | Impact of enclosure management on soil properties and microbial biomass in a restored semi-arid rangeland, Kenya显示文摘Rangeland degradation is a serious problem throughout sub-Saharan Africa and its restoration is a challenge for the management of arid and semi-arid areas. In Lake Baringo Basin of Kenya, communities and individual farmers are restoring indigenous vegetation inside enclosures in an effort to combat severe land degradation and address their livelihood problems. This study evaluated the impact of enclosure management on soil properties and microbial biomass, being key indicators of soil ecosystem health. Six reseeded communal enclosures using soil embankments as water-harvesting structures and strictly regulated access were selected, varying in age from 13 to 23 years. In six private enclosures, ranging from 3 to 17 years in age, individual farmers emulated the communal enclosure strategy and restored areas for their exclusive use. Significant decreases in bulk density, and increases in the soil organic carbon, total nitrogen and microbial biomass contents and stocks were found in the enclosures as compared with the degraded open rangeland. In the private enclosures, the impact of rehabilitation on the soil quality was variable, and soil quality was in general lower than that obtained under communal management. The significant increase of absolute stocks of carbon, nitrogen and microbial biomass compared to the degraded open rangeland indicates the potential for the restoration of soil quality through range rehabilitation. Over-sowing with indigenous legume fodder species could improve total nitrogen content in the soil and nutritional value of the pastures as well. | Stephen M MUREITHI Ann VERDOODT Charles KK GACHENE Jesse T NJOKA Vivian O WASONGA Stefaan De NEVE Elizabeth MEYERHOFF Eric Van RANST | 2014 | Journal of Arid Land2014，6，5： | 3 |
| 7 | Deep neural networks for understanding noisy data applied to physical property extraction in scanning probe microscopy显示文摘The rapid development of spectral-imaging methods in scanning probe,electron,and optical microscopy in the last decade have given rise for large multidimensional datasets.In many cases,the reduction of hyperspectral data to the lower-dimension materialsspecific parameters is based on functional fitting,where an approximate form of the fitting function is known,but the parameters of the function need to be determined.However,functional fits of noisy data realized via iterative methods,such as least-square gradient descent,often yield spurious results and are very sensitive to initial guesses.Here,we demonstrate an approach for the reduction of the hyperspectral data using a deep neural network approach.A combined deep neural network/least-square approach is shown to improve the effective signal-to-noise ratio of band-excitation piezoresponse force microscopy by more than an order of magnitude,allowing characterization when very small driving signals are used or when a material’s response is weak. | Nikolay Borodinov Sabine Neumayer Sergei V.Kalinin Olga S.Ovchinnikova Rama K.Vasudevan Stephen Jesse | 2019 | npj Computational Materials2019，，1： | 3 |
| 8 | ACCF 2012 Expert Consensus Document on Practical Clinical Considerations in the Interpretation of Troponin Elevations显示文摘 | L. Kristin Newby Robert L. Jesse Joseph D. Babb Robert H. Christenson Thomas M. De Fer George A. Diamond Francis M. Fesmire Stephen A. Geraci Bernard J. Gersh Greg C. Larsen Sanjay Kaul Charles R. McKay George J. Philippides William S. Weintraub | 2012 | Journal of the American College of Cardiology2012，，23： | 2 |
| 9 | Plasmonic mode mixing in nanoparticle dimers with nm-separations via substrate-mediated coupling显示文摘 | Jesse Theiss Mehmet Aykol Prathamesh Pavaskar Stephen B. Cronin | 2014 | Nano Research2014，7，9： | 2 |
| 10 | Biomechanical evaluation of surgical constructs for stabilization of cervical teardrop fractures显示文摘 | Allyson Ianuzzi Isidoro Zambrano Jigar Tataria Azeema Ameerally Marc Agulnick Jesse S. Little Goodwin Mark Stephen Partap S. Khalsa | 2006 | The Spine Journal2006，，5： | 1 |
| 11 | Comparability of perioperative morbidity between abdominal myomectomy and hysterectomy for women with uterine leiomyomas显示文摘 | Stephen W. Sawin Nicole D. Pilevsky Jesse A. Berlin Kurt T. Barnhart | 2000 | American Journal of Obstetrics and Gynecology2000，，6： | 1 |
| 12 | Effect of antidepressants and their relative affinity for the serotonin transporter on the risk of myocardial infarction显示文摘 | William HS Jesse AB Stephen EK | 2003 | Circulation2003，108，： | 1 |
| 13 | Glyphosate as a selective agent for the production of fertile transgenic maize (Zea mays L.) plants显示文摘 | Arlene R. Howe Charles S. Gasser Sherri M. Brown Stephen R. Padgette Jesse Hart Gregory B. Parker Michael E. Fromm Charles L. Armstrong | 2002 | Molecular Breeding2002，，3： | 1 |
| 14 | Angiographic correlates of cardiac death and myocardial infarction complicating major nonthoracic vascular surgery显示文摘 | Stephen G. Ellis Norman R. Hertzer Jess R. Young Sorin Brener | 1996 | The American Journal of Cardiology1996，，12： | 1 |
| 15 | E-beam manipulation of Si atoms on graphene edges with an aberration-corrected scanning transmission electron microscope显示文摘The burgeoning field of atomic-level material control holds great promise for future breakthroughs in quantum and memristive device manufacture and fundamental studies of atomic-scale chemistry.Realization of atom-by-atom control of matter represents a complex and ongoing challenge.Here,we explore the feasibility of controllable motion of dopant Si atoms at the edges of graphene via the sub-atomically focused electron beam in a scanning transmission electron microscope.We demonstrate that the graphene edges can be cleaned of Si atoms and then subsequently replenished from nearby source material.It is also shown how Si edge atoms may be 'pushed'from the edge of a small hole into the bulk of the graphene lattice and from the bulk of the lattice back to the edge. This is accomplished through sputtering of the edge of the graphene lattice to bury or uncover Si dopant atoms.Finally,we demonstrate e-beam mediated hole healing and incorporation of dopant atoms.These experiments form an initial step toward general atomic-scale material control. | Ondrej Dyck Songkil Kim Sergei V.Kalinin Stephen Jesse | 2018 | Nano Research2018，11，12： | 1 |
| 16 | The Posterior Monteggia Lesion显示文摘 | Jesse B. Jupiter Stephen J. Leibovic William Ribbans Richard M. Wilk | 1991 | Journal of Orthopaedic Trauma1991，，4： | 1 |
| 17 | Microbiota Separation and C-reactive Protein Elevation in Treatment-na?ve Pediatric Granulomatous Crohn Disease显示文摘 | Richard Kellermayer Sabina A.V. Mir Dorottya Nagy-Szakal Stephen B. Cox Scot E. Dowd Jess L. Kaplan Yan Sun Sahna Reddy Jiri Bronsky Harland S. Winter | 2012 | Journal of Pediatric Gastroenterology and Nutrition2012，，3： | 1 |
| 18 | Imaging mechanism for hyperspectral scanning probe microscopy via Gaussian process modelling显示文摘We investigate the ability to reconstruct and derive spatial structure from sparsely sampled 3D piezoresponse force microcopy data,captured using the band-excitation(BE)technique,via Gaussian Process(GP)methods.Even for weakly informative priors,GP methods allow unambiguous determination of the characteristic length scales of the imaging process both in spatial and frequency domains.We further show that BE data set tends to be oversampled in the spatial domains,with~30% of original data set sufficient for high-quality reconstruction,potentially enabling faster BE imaging.At the same time,reliable reconstruction along the frequency domain requires the resonance peak to be within the measured band.This behavior suggests the optimal strategy for the BE imaging on unknown samples.Finally,we discuss how GP can be used for automated experimentation in SPM,by combining GP regression with non-rectangular scans. | Maxim Ziatdinov Dohyung Kim Sabine Neumayer Rama K.Vasudevan Liam Collins Stephen Jesse Mahshid Ahmadi Sergei V.Kalinin | 2020 | npj Computational Materials2020，，1： | 1 |
| 19 | Metaanalysisof observational studies inEpidemiology显示文摘 | DonnaE Stroup Jesse A.Berlin Sally C.Morton Ingrarn Olkin G.David Williamson Drummond tkennie David Moher Betsy J.Becker Theresa Ann Sipe Stephen B.Thacker | | 0，，15： | 1 |
| 20 | A phase I trial of an antisense inhibitor of hepatitis C virus (ISIS 14803), administered to chronic hepatitis C patients显示文摘 | John G. McHutchison Keyur Patel Paul Pockros Lisa Nyberg Stephen Pianko Rosie Z. Yu F. Andrew Dorr T. Jesse Kwoh | 2005 | Journal of Hepatology2005，，1： | 1 |
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