In response to the urgent need to address global climate change and achieve deep decarbonization of energy systems, clean energy technologies are undergoing transformative advancement. Within this context, a remote, in situ, and rapid technology for high-precision isotopic analysis of lithium is critical for nuclear energy systems due to their critical role in ensuring the safe operation of nuclear fission systems and in situ breeding of fusion fuel, yet conventional Laser-Induced Breakdown Spectroscopy (LIBS) suffers from severe self-absorption and dense plasma broadening that obscure the minute isotopic shifts (∼15 pm). To overcome this longstanding challenge, we propose a time-space-medium collaboratively modulated LIBS (TSMM-LIBS) approach combined with a matrix dilution strategy to actively regulate the plasma environment and thoroughly suppress self-reversal. A novel self-reversal indicator (SRI) was defined to quantify the degree of self-reversal, and a wing-side recovery algorithm coupled with the Beer–Lambert law was utilized to successfully invert highly distorted absorption dips into effective emission peaks. As a major breakthrough, the lithium doublet structure and its isotopic shifts (670.776 nm for 7Li D2, 670.791 nm for 7Li D1 and 6Li D2, and 670.807 nm for 6Li D1) were simultaneously resolved for the first time in LIBS. The synergistic modulation significantly compressed the spectral full width at half-maximum (fwhm) to 25.65 pm and Stark broadening (ωStark) to 3.87 pm, achieving sub-Doppler resolution and approaches the intrinsic emission quality of a hollow cathode lamp (HCL). Furthermore, an Effective Concentration Model with Self-Absorption Correction (ECM-SAC) was established based on the Lomakin–Schaefer formula and quantum mechanical transition probabilities. Cross-validation demonstrated exceptional quantitative accuracy across wide isotopic abundance gradients for both Li2TiO3 solid ceramics and lithium solution samples. The optimal spectral intensity ratio (670.776/670.807 nm) yielded a root-mean-square error of cross-validation (RMSECV) of 0.041 and a remarkably high ratio of performance to deviation (RPD) of 6.561. This work establishes a rapid, in situ, and high-precision analytical framework for lithium isotope discrimination, holding substantial promise for nuclear material cycle management and monitoring of tritium breeding material in fusion reactors.
Lai et al. (Thu,) studied this question.