• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to project page

2021 Fiscal Year Final Research Report

Radon reduction in dark matter search experiment by the development of ultra-low activity molecular sieves

Research Project

  • PDF
Project/Area Number 19K03893
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 15020:Experimental studies related to particle-, nuclear-, cosmic ray and astro-physics
Research InstitutionNihon University

Principal Investigator

OGAWA Hiroshi  日本大学, 理工学部, 助手 (20374910)

Project Period (FY) 2019-04-01 – 2022-03-31
Keywords暗黒物質 / ラドン / 極低放射能技術
Outline of Final Research Achievements

This study is the developing of an ultra-low radioactive adsorbent Molecular Sieves (MS) to remove radioactive impurities, that are the background of dark matter search experiments and impurities, that attenuate light emission characteristics from the rare gas used in dark matter detectors. This is a study aimed at improving the sensitivity of dark matter search. In particular, the primary goal is to adsorb radon, which is a radioactive impurity.
First, we conducted the production of ultra-low radioactive MS and evaluated the radioactivity of the produced MS, and found that it is possible to produce ultra-low radioactivity MS by selecting materials. After that, by selecting the materials and examining the manufacturing process, we succeeded in developing a radon adsorption MS with less radioactivity that can be used in actual dark matter search experiments.

Free Research Field

素粒子・原子核実験物理

Academic Significance and Societal Importance of the Research Achievements

近年、ガスを用いた暗黒物質探索実験は、トンスケールの大型検出器 (XMASS, XENON)や、方向に感度を持つ検出器(NEWAGE, DRIFT)など、大型化、多様化が進んでおり、ガスの純化は、暗黒物質探索実験の感度向上のために非常に重要である。本研究のアプローチは、これらのガスの純化に大きく貢献するものである。実際、本研究で開発されたMSによるガス中からの不純物除去研究が進められている。また、モレキュラーシーブの用途として、暗黒物質探索実験に使われるという基礎科学への貢献ということについての新たなフロンティアを開くものとなった。

URL: 

Published: 2023-01-30  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi