Invention Grant
- Patent Title: Determining atomic coordinates from X-ray diffraction data
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Application No.: US16830532Application Date: 2020-03-26
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Publication No.: US11860114B2Publication Date: 2024-01-02
- Inventor: David Hurwitz
- Applicant: David Hurwitz
- Applicant Address: US MD Rockville
- Assignee: David Hurwitz
- Current Assignee: David Hurwitz
- Current Assignee Address: US MD Rockville
- Agency: Panitch Schwarze Belisario & Nadel LLP
- Main IPC: G01N23/20
- IPC: G01N23/20 ; G06N3/02 ; G06N3/084 ; G06N3/04

Abstract:
Atomic position data may be obtained from x-ray diffraction data. The x-ray diffraction data for a sample may be squared and/or otherwise operated on to obtain input data for a neural network. The input data may be input to a trained convolutional neural network. The convolutional neural network may have been trained based on pairs of known atomic structures and corresponding neural network inputs. For the neural network input corresponding to the sample and input to the trained convolutional neural network, the convolutional neural network may obtain an atomic structure corresponding to the sample.
Public/Granted literature
- US20210302332A1 DETERMINING ATOMIC COORDINATES FROM X-RAY DIFFRACTION DATA Public/Granted day:2021-09-30
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