Volume 26


Number 5 October 2020


table of contents


Dear Abbe


Dear Abbe, I want to paint my SEM column orange, in homage to


Zeiss vintage equipment, sort of an “orange homage,” if you will. How do I convince my higher-ups that this is indeed a good idea? Tired of Gray in California


Dear 50 Shades of Tired, Ah yes, the orange phase of Zeiss. Having spent some time


Materials Science Applications An improved electron microprobe method for the analysis of halogens in natural silicate glasses Flemetakis, Stamatis; Berndt, Jasper; Klemme, Stephan; Genske, Felix; Cadoux, Anita; Louvel, Marion; Rohrbach, Arno


Ultra-Microtome for the Preparation of TEM Specimens from Battery Cathodes Zhou, Guangwen; Zhang, Hanlei; Wang, Chong-Min


Nanoscale Visualization of Phase Transition in Melting of Sn-Bi Particles by In situ Hard X-ray Ptychographic Coherent Diffraction Imaging Takahashi, Yukio; Ishiguro, Nozomu; Higashino, Takaya; Hirose, Makoto


Dynamic precipitation, dynamic recrystallization and texture evolution of Mg-5Zn alloy sheets with trace Ca and Sr addition Yan, Hongge; Wu, Qin; Chen, Jihua; Xia, Weijun; Song, Min; Su, Bin; Ding, Tian


Correction of secondary fluorescence across phase boundaries in electron probe microanalysis of mineral inclusions Llovet, Xavier; Proenza, Joaquin; Pujol-Solà, Núria; Ferré-de-Pablo, Júlia; Campeny, Marc


Soſtware and Instrumentation Contamination of TEM Holders Quantified and Mitigated with Open-Hardware, High-Vacuum Bakeout System Hovden, Robert; Goh, Yin Min; Schwartz, Jonathan; Rennich, Emily; Ma, Tao; Kerns, Bobby


CDriſt: an algorithm to correct linear driſt from a single high-resolution STEM image Bárcena González, Guillermo; Guerrero-Lebrero, María de la Paz; Guerrero, Elisa; Yañez, Andres; Nuñez-Moraleda, Bernardo; Fernandez, Daniel; Real, Pedro; González, David; Galindo, Pedro


Optimal STEM Convergence Angle Selection using a Convolutional Neural Network and the Strehl Ratio Hovden, Robert; Schnitzer, Noah; Sung, Suk Hyun


Application of blind deconvolution based on the new weighted L1-norm regularization with alternating direction method of multipliers in light microscopy images Lee, Youngjin; Kim, Ji-Youn; Kim, Kyuseok


Expanding the dimensions of a small, two-dimensional diffraction detector LeBeau, James; Chen, Xi; Hauwiller, Matthew; Kumar, Abinash; Penn, Aubrey


Fast Pixelated Detectors in Scanning Transmission Electron Microscopy. Part II: Post Acquisition Data Processing, Visualisation, and Structural Characterisation Paterson, Gary; Webster, Robert; Ross, Andrew; Paton, Kirsty; Macgregor, Tomas; McGrouther, Damien; MacLaren, Ian; Nord, Magnus


Processing APT Spectral Backgrounds for Improved Quantification Haley, Daniel; Moody, Michael; London, Andrew


Mathematical mirroring for identification of local symmetry centers in microscopic images


Willemse, Joost; van der Vaart, Michiel; Yang, Wen; Briegel, Ariane


Biological Applications Advanced microtexture study of Anacardium occidentale L. leaf surface from Amazon by fractal theory da Fonseca Filho, Henrique; Ramos, Glenda; Matos, Robert


2020 September • www.microscopy-today.com


with the company in Jena, I can wholeheartedly agree with your assessment that Orange is the new Gray. It just seems more … Oktoberfestive! Otto Schott and I used to suggest many bright tones on the production of light microscopes and equipment. Unfortunately, the stodgy foundation members loved the “dignified” look of that Nachkriegszeit Kitt color. It is always difficult to convince higher-ups of anything unless money is involved. Try convincing them that orange increases productivity, accuracy, and camaraderie and they may just jump on it (the idea, hopefully not the scope).


Sometimes life hands you lemons, sometimes it hands you


something that looks and smells less appealing. Let Abbe give you the tools to make anything appear more palatable. Contact Herr Abbe’s assistant at johnshields59@gmail.com.


Crossword Puzzle Answers See puzzle on page 68.


12 3 11 14


SMA L LA N G L E T M B A IO O U D O N A I R NI T


4 12 15 19 22


GR O O V E 23


LE T ES I 28 29 33 34 39 A C 47 48 52 57


RU R 49


45


C E PTA N C E A N G L E 46


41 42 43 L


TU T O R R 53


50


CO M A D M I D T E R M S LA L


IN S I T U A 58


61 65 66 70 62


EE L G L 71


67 SI L I F doi:10.1017/S1551929520001248 T O 68 R 63


A R M S 59 60


54 55 L A M E


P E Y I 56


64 U T


A Z E R A T I O 72


69 S N E LS N 77 E R I T E N


PA N H E E 40


35


R O G E N M Y 20


16 17 R 24


H I 36


S 31 S 5 6 7 13 8 9 10 Y


R O R S H O W E 30


I A O C A I 25


26 27 32 37 38 L S L


A A ID 44


Y M P A N UM 51


S E LF 21


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