PATENT CLAIM ANALYSIS

Application Number: 15865099
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-07
Patent Classification: ["376", "159000"]

Abstract:
A neutron detector system for discriminating fissile material from non-fissile material wherein a digital data acquisition unit collects data at high rate, and in real-time processes large volumes of data directly to count neutrons from the unknown source and detecting excess grouped neutrons to identify fission in the unknown source. The system includes a Poisson neutron generator for in-beam interrogation of a possible fissile neutron source and a DC power supply that exhibits electrical ripple on the order of less than one part per million. Certain voltage multiplier circuits, such as Cockroft-Walton voltage multipliers, are used to enhance the effective of series resistor-inductor circuits components to reduce the ripple associated with traditional AC rectified, high voltage DC power supplies.

Claim (Index 1):
A method of characterizing a material as fissile or non-fissile, comprising:\n irradiating the material using an interrogation beam of neutrons generated from a pulsed electric source of neutrons; and detecting, through a detector, neutrons emitted from the material while the interrogation beam is irradiating the material, wherein the detector is configured to distinguish between electric source neutrons in the interrogation beam and induced fission neutrons from the material.

Metadata:
- Claim Count in Document: 7.0
- Percentile: 86.0
- Lexical Diversity: 1.48235
- Patent Class: 376.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15865062', '14213502', '15419916', '14515321', '14298406']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.7416962259596354
- 35 USC 102 Novelty (BERT): 0.5993368893360588
- Combined Prediction Score: 0.7274602922972777
- Mean Citation Score: 515.846442
- Max Citation Score: 553.0666
- Similarity Product: 470.74331572871216

Labels:
- Claim Label 101: 1
- Claim Label 102: 0
- Claim Label 103: 0
- Claim Label 112: 0
- Combined Label: 0
- Label 101 Adjusted: 1

Dataset: test