Inertial electrostatic confinement and DD fusion at interelectrode media of nanosecond vacuum discharge. PIC simulations and experiment

Abstract

The generation of energetic ions and DD neutrons from microfusion at the interelectrode space of a low-energy nanosecond vacuum discharge has been demonstrated recently [1, 2]. However, the physics of fusion processes and some results regarding the neutron yield from the database accumulated were poorly understood. The present work presents a detailed particle-in-cell (PIC) simulation of the discharge experimental conditions using a fully electrodynamic code. The dynamics of all charge particles was reconstructed in time and anode–cathode (AC) space. The principal role of a virtual cathode (VC) and the corresponding single and double potential wells formed in the interelectrode space are recognized. The calculated depth of the quasistationary potential well (PW) of the VC is about 50–60 keV, and the D+ ions being trapped by this well accelerate up to energy values needed to provide collisional DD nuclear synthesis. The correlation between the calculated potential well structures (and dynamics) and the neutron yield observed is discussed. In particular, ions in the potential well undergo high-frequency (∼80 MHz) harmonic oscillations accompanied by a corresponding regime of oscillatory neutron yield. Both experiment and PIC simulations illustrate favorable scaling of the fusion power density for the chosen IECF scheme based on nanosecond vacuum discharge.

Warm Dense Matter Generation and DD Synthesis at Vacuum Discharge with Deuterium‐Loaded Pd Anode

“…Ions being accelerated from different edges of the PW to the Z axis, represent head-on fluxes at r → 0 with ion energies of 20-50 keV. Evidently, this explains the collisional DD fusion observed in the real experiments (in that case we also have to take into account collisions with neutrals, deuterium clusters and the deuterated anode itself) [10]. The area of Z and R at the half-width of the PW contains an almost isotropic distribution of fast ions with mean energy about 25 keV [10] (volume of the "reactor", fig7; picture for V r /c has similar shape being 20% broader by velocity).…”

“…In fact, solid density electrodes, vacuum environment, fast and local energy deposition provides the framework to create and study WDM also. For example, there are many ways to concentrate energy up to 10 4 J/g in microscopic volumes of a cathode. These concentrations of energy result in microscopic explosions accompanied by emission of electrons, creating a plasma, liquid droplets of metal, and metal vapor.…”

“…The efficiency of hard X-rays and fast ions generation by nanosecond vacuum discharge, as well as the neutron generation, is at least two orders of magnitude higher than for experiments on DD fusion driven by Coulomb explosion of laser irradiated deuterium clusters [3]. To understand better the physics of fusion processes the detailed PIC simulation of the discharge experimental conditions have been developed using a fully electrodynamic code KARAT [10,24]. The dynamics of main charge particle species was reconstructed in time at anode -cathode (A-C) space.…”

“…As a result, head-on collisions of D + ions with energies of a few tens of keV is followed by DD nuclear fusion, transforming the interelectrode space into something like a reactor chamber. PIC modeling allows the identification of the small-scale experiment [8][9][10] with a rather old branch of plasma physics, as inertial electrostatic confinement fusion (IECF) system (see [11][12][13][14] and refs therein). Pioneers of IECF were O. Lavrent'ev in the USSR and F. Farnsworth in the USA, but due to different reasons, including a rather low value for Q = E fusion / E input ∼ 10 −6 or even less, this concept for fusion was almost forgotten.…”

“…(Online colour: www.cpp-journal.org). The complex physics of nanosecond discharge processes and the mechanisms of microfusion were poorly understood at first [8], and motivated the interest in complementary PIC (particlein-cell) KARAT simulations [10,24,29]. In addition to representing the key points of general physical picture, computer modelling allows clarification of the details of the experimental data.…”