Third-dimension information retrieval from a single convergent-beam transmission electron diffraction pattern using an artificial neural network

Pennington, Robert S.; Broek, Wouter Van den; Koch, Christoph T.

doi:10.1103/physrevb.89.205409

Cited by 20 publications

(22 citation statements)

References 42 publications

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“…We consider first the same "prototype" specimen used in previous work [12]. This specimen has third-dimensional variations in its local crystal tilt in the α x direction, given in Table 1 as a function of percent-depth in the specimen.…”

Section: Results and Analysismentioning

confidence: 99%

“…To solve this manyparameter optimization problem, our algorithm uses artificial neural network (ANN) optimization tools that are similar to those used to retrieve individual atomic positions in nanoparticles [13,14]; however, we apply these tools to a different optimization problem in a different context. Our previous work [12] demonstrated that our algorithm can work; in contrast, this paper discusses how well our algorithm works and how to provide optimal input data. First, how does reciprocal space sampling affect our algorithm's effectiveness at retrieving specimen parameters?…”

Section: Introductionmentioning

confidence: 83%

“…For single-scattering-based measurements, where the depth information may be captured by using variations of specific experimental conditions that are considered to generate single-scattering data, the reconstruction algorithms are generally linear: electron tomography, either algebraic or geometric [6,7], is commonly limited to specimen density or shape information; focal-series annular dark field images [8] have been used to retrieve surface-layer strain, but only for the top 15 nm of the specimen; in high-angle annular dark-field scanning TEM or scanning confocal electron microscopy, depth-direction information can be recorded using focal variation [9][10][11]. Recently, we have developed an algorithm that enables efficient evaluation of this multiple-scattering inverse problem for nanoscale stackedBloch-wave simulations from a single convergent-beam electron diffraction (CBED) pattern, even if using only a few CBED disks and including noise [12]. This algorithm can be applied, in principle, to retrieving the "third-dimension" (depth-direction) variation of any specimen parameter affecting the Bloch-wave scattering matrix.…”

Section: Introductionmentioning

confidence: 98%

“…We use the stacked-Bloch-wave (SBW) forward-simulation algorithm [16][17][18], implemented as described previously with an artificial-neural-network optimizer [19,12,20] as the basis for our retrieval algorithm. Our target parameter is the local crystal tilt in one direction for a 10 layer specimen.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Retrieving depth-direction information from TEM diffraction data under reciprocal-space sampling variation

Pennington¹,

Koch²

2015

Ultramicroscopy

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Section: Results and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 83%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Retrieving depth-direction information from TEM diffraction data under reciprocal-space sampling variation

Pennington¹,

Koch²

2015

Ultramicroscopy

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“…However, since it has a different significance for many fields, most approaches of the scientific literature are not carried out from the LIS perspective. This is proven by studies that have explored the information dimensions in areas such as Economy (Melody, 1987), Physics (Morriss, 1987;Wei et al, 2014;Pennington, Van den Broek & Koch, 2014), Neuroscience (Li et al, 2007), and Oncology (Petricoin et al, 2006), to mention just some cases.…”

Section: Introductionmentioning

confidence: 99%

Rethinking the information dimension of marketing

González-Valiente¹,

Pacheco‐Mendoza

2017

Biblios

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This article discusses the information dimension of marketing from a technical, theoretical and behavioral perspective. It also comments the relationship between marketing and the library and information science (LIS). It is an exploratory and descriptive study and its qualitative approaches are carried out through classic documentary analysis. From the technical perspective, it addresses the presence of information in all marketing management processes, from market research to the final preparation of the marketing plan. From the theoretical perspective, it addresses the frameworks for marketing information processing, the influence of the information value theory and the application of techniques from dissimilar areas of study to analyze the information. From the behavioral perspective, it shows empirical evidence of human information behavior of marketing managers and other actors, based on cognitive and social viewpoints. Regarding disciplinary relations, marketing and LIS share theories related to information behavior, information management, and systems analysis and design. The marketing approaches is more noticeable on LIS studies than LIS approaches on marketing studies, considering the analysed literature. Information, as a link between both disciplines, makes way to delve into new research, academic and practical scenarios. Repensando la dimensión informacional de la mercadotecnia ResumenEn este artículo se aborda la dimensión informacional de la mercadotecnia desde una perspectiva técnica, teórica y comportamental. También se profundiza en las relaciones entre la mercadotecnia y la Bibliotecología y la Ciencia de la Información (BCI). Es un estudio exploratorio-descriptivo, cuyos abordajes cualitativos se realizan mediante el análisis documental clásico. Desde la perspectiva técnica se aborda la presencia de la información en todos los procesos de gestión mercadotécnica, desde la investigación de mercados hasta la confección final del plan de mercadotecnia. Desde la perspectiva teórica se hace alusión a los marcos para el procesamiento de la información de mercado, la influencia de la teoría del valor de la información y la aplicación de técnicas provenientes de disímiles áreas de estudio para analizar la información. Desde la perspectiva comportamental se exponen evidencias empíricas de comportamiento humano informacional de los gestores de mercadotecnia y otros actores, a partir de las aristas cognitiva y social. Relativo a las relaciones disciplinares, se percibe que la mercadotecnia y la BCI comparten teorías asociadas al comportamiento informacional, la gestión de información y el análisis y diseño de sistemas. El enfoque de la mercadotecnia es más notable en los estudios de BCI que en enfoques de BCI sobre estudios de mercadeo, considerando la literatura analizada. La información, como nexo entre ambas disciplinas, abre un camino para profundizar en nuevos escenarios investigativos, académicos y prácticos.

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Retrieving atomic structure from dynamical rocking curve measurements in both real and reciprocal space

Broek¹,

Wang²,

Pennington³

2016

European Microscopy Congress 2016: Proceedings

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Transmission electron microscopy (TEM) data, in particular high‐resolution TEM and conventional electron diffraction has the reputation of being not easily interpretable in a quantitative manner in terms of the object being probed by the fast electrons. The reason for this lies in the fact that multiple scattering makes the detected signal a non‐linear function of the scattering potential. In cases where the structure is approximately known, refinement of structure factors from convergent beam electron diffraction (CBED) data [1] or atom positions from HRTEM images [2] is possible. But the ab‐initio inversion of multiple scattering to recover the structure of an unknown object has not yet been shown to work in a routine manner for experimental data. Structure determination approaches thus typically revert to techniques which collect tilt‐averaged data, such as precession electron diffraction (PED) and scanning transmission electron microscopy (STEM) with a convergent probe. Integrating the signal over a range of different relative orientations between object and electron beam wave vector averages over different multiple scattering conditions – however, a large amount of structural information encoded in the multiple scattering signal gets lost, including valuable information about the object's 3D structure [3]. Fig. 1 demonstrates that in the case of experimental large‐angle rocking‐beam electron diffraction (LARBED) data [4], i.e. diffraction data for a large range of beam tilts (about 20 times larger than possible in conventional CBED of silicon), the projected potential can be recovered by straight forward gradient optimization from a starting guess in which all structure factors were initialized to the same value, i.e. initially, all Ug = (0.01 + 0.01i) Å −2 [5]. Although rocking curves of only 121 diffraction spots were measured, 456 structure factors could be determined from this data, since, all possible difference vectors between reflections extracted from the diffraction pattern were also included in the dynamical diffraction calculation. Although CBED and HRTEM are very different modes of operation of the microscope, the multiple scattering contribution to the signal in tilt series of HRTEM images allows us to retrieve the 3D scattering potential [6], where the position and height of peaks allows direct interpretation as atom species and positions (see Fig. 2). This inversion of multiple scattering is based on an interpretation of the multislice algorithm as an artificial neural network that is taught by feeding it TEM data recorded under different experimental conditions. This can be HRTEM tilt series, ptychography data sets, or scanning confocal electron microscopy (SCEM) data [7].[8]

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Third-dimension information retrieval from a single convergent-beam transmission electron diffraction pattern using an artificial neural network

Cited by 20 publications

References 42 publications

Retrieving depth-direction information from TEM diffraction data under reciprocal-space sampling variation

Retrieving depth-direction information from TEM diffraction data under reciprocal-space sampling variation

Rethinking the information dimension of marketing

Retrieving atomic structure from dynamical rocking curve measurements in both real and reciprocal space

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