Time-Resolved Spectra Alignment for Faster Low-Noise Event Averaging
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Solution Overview
Problem
Current charged particle spectroscopy techniques, such as APXPS, SXRD, PM-IRAS, and PES, face limitations in acquiring high signal-to-noise ratios due to weak photoelectron probe signals, restricting the ability to study fast reactions and kinetics of catalyst surfaces under varying conditions.
Innovation Solution
A computer-implemented method generates event-averaged and time-resolved spectra by matching selected parts of time-resolved spectra to improve signal quality, using pattern recognition to determine event points and control physical conditions, thereby enhancing the signal-to-noise ratio and allowing for real-time data acquisition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If charged particle analyser is used to detect photo-electrons, then signal detection capability is improved, but acquisition time increases significantly
Solution Approach 1:
The patent segments the continuous spectrum acquisition into discrete event-based time windows. By dividing the time-resolved spectra into multiple events and analyzing specific portions (pre-event, post-event, during-event) separately, the method enables efficient processing and averaging of weak signals without requiring long continuous acquisition times.
Solution Approach 2:
The patent performs preliminary selection and identification of relevant spectral features before conducting full analysis. By pre-identifying characteristic peaks and selecting specific time windows of interest, the method prepares the data in advance for efficient averaging, reducing the total acquisition time needed to achieve sufficient signal-to-noise ratio.
2Loss of information
If time-resolved spectra are acquired for kinetic studies, then reaction kinetics information is obtained, but signal-to-noise ratio deteriorates
Solution Approach 1:
The patent merges multiple time-resolved spectra from repeated events by aligning them based on identified characteristic features and averaging corresponding time windows. This combining of multiple measurements enhances the signal-to-noise ratio while preserving the kinetic information contained in the time-resolved data.
Solution Approach 2:
The patent creates reference copies of characteristic spectral features from selected events and uses these as templates to identify and align corresponding features in other events. This copying approach enables accurate alignment even when absolute timing varies, ensuring that kinetic information is preserved while enabling effective signal averaging.
3Measurement precision
If event-averaging is performed on all time-resolved spectra, then signal quality is improved, but processing complexity increases
Solution Approach 1:
The patent extracts and focuses only on the specific time windows and spectral regions that contain relevant kinetic information, rather than processing the entire time-resolved spectra. By taking out and averaging only the relevant portions (pre-event, post-event, during-event windows), the method improves signal quality while minimizing processing complexity.
Solution Approach 2:
The patent applies different processing strategies to different portions of the time-resolved spectra based on their local characteristics. By identifying and treating specific time windows (before, during, and after events) with appropriate averaging and alignment methods, the method optimizes signal quality where needed while avoiding unnecessary processing elsewhere.
Data Source
AI summary
A computer-implemented method is described for generating event-averaged and time-resolved spectra, from a plurality of time-resolved spectra of charged particles emitted from a surface (3) of a sample (2), at which surface (3) an event is repeated cyclically, the method comprising the steps of receiving (101), from the charged particle analyser (1), the plurality of time-resolved spectra covering a plurality of events, obtaining (102) at least one selected part (9, 10) of the series of time-resolved spectra, matching (103) the at least one selected part (9, 10) with other parts of the series of time-resolved spectra to find similar parts, and thereby determining points in time for other events in the plurality of events, and generating (104) the event-averaged and time-resolved spectra of the event based on the series of time-resolved charged particle energy spectra and the determined points in time.