Identifying the unknown chemical weapons is an important work for maintaining social security, and it can guide the chemical weapons destruction. Prompt gamma-ray neutron activation analysis (PGNAA) technology has the advantages of being non-destructive and rapid. In this research, the device was designed for identifying the chemical weapons based on PGNAA technology, and logic-tree-based discrimination method was employed to conduct qualitative analysis on samples.Firstly, with the high purity germanium (HPGe) detector and Cf-252 neutron source as the core instruments, the structures of device were optimized using the Monte Carlo MCNP code, including neutron source moderator, the thickness of the shielding body, and the relative position of the detector. To maximize the characteristic gamma ray generated by sample activation, it is necessary to increase the thermal neutron flux in the sample. In this research, polyethylene is used as moderator to increase the scattering of neutrons before the sample, so that more neutrons are thermalized. The simulation results showed that the thermal neutron flux in the sample reaches a high level when the polyethylene has a thickness of 6 cm and a width of 12 cm. In order to reduce the interference of the surrounding material activation noise, lead is selected as the shielding structure. And the simulation showed that it can meet the shielding requirement when the lead shielding thickness reaches 5 cm. At the same time, the distance between the detector and the sample also affects the detection of gamma rays. The final simulation determines that the distance between the detector and the sample is 28 cm, and the characteristic signal count is the highest.According to the optimization results, the experimental device was set up. And the simulated samples of chemical weapon were prepared according to the actual elements by using the analytical pure reagent, and the gamma spectrum was obtained by measuring the five samples. In the process of analyzing the characteristic peaks in the spectrum, the elements were analyzed based on the characteristic peaks of the elements. The elements with well statistic were analyzed by using gauss and polynomial fitting (such as H, Cl, S). The high-energy Compton platform at the characteristic peak was deducted to obtain the full peak information. For the element characteristic peak with poor statistic (such as 10.829 MeV of the N element), the energy interval summation method was used to sum the counts between the full peaks and the single escape energy peaks, so we can get the information of the elements in the sample. Finally, the logic-tree-based discrimination method was used for sample identification. The analysis results showed that the information of H, Cl, S, N and other elements in the simulated samples of chemical weapons can be obtained by using the spectrum fitting method. And the type of simulated samples of chemical weapon can be identified by combining logic-tree-based discrimination method.