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The electrochromic detection of latent fingermarks on polished or unpolished, flat or curved metal surfaces is described using electrochromic material, 1,1'‐dibenzyl‐4,4'‐bipyridinium dichloride. The surface area covered by fingermarks acts as an insulating mask, causing 1,1'‐dibenzyl‐4,4'‐bipyridinium dichloride to change color and produce inversed images of the fingermark. By changing the applied potential, the optical properties of 1,1'‐dibenzyl‐4,4'‐bipyridinium dichloride can be continuously and reversibly adjusted to optimize the visual contrast of fingermarks, so as to realize the detection of latent fingermarks on stainless steel surface. It is demonstrated that the fabricated electrochromic devices can detect the fingermarks on these types of surfaces within twenty seconds at −1.0∼−2.0 V. This work can qualify as a tangible improvement in fingermark detection of the natural fingermarks on the never‐cleaned (more than 3 years) and curved surfaces of daily‐used container, e. g. cup, and the handle of cleaning tool, mop. [ABSTRACT FROM AUTHOR]

Doubly-substituted methane isotopologues (13CH3D and 12CH2D2) can provide unique information to resolve the origin, transport, and conversion of environmental methane. We used a high-resolution mass spectrometer (Thermo Fisher Scientific 253 Ultra) to precisely determine Δ13CH3D and Δ12CH2D2 (precision and accuracy of ∼0.35‰ and ∼1.35‰ (1σ), respectively) in this study. The impacts of temperature, humidity, and slit quality are found to be critical for the reproducibility of the results, while the fragmentation rate and bellows effects on the clumped isotope results were negligible. A heating equilibrium experiment performed at 500 °C, 400 °C and 300 °C (n = 19) calibrates the results to an absolute reference. A pretreatment system that can extract methane having concentrations from ∼15% to ∼99.8% is proposed, while the fractionation produced throughout the pretreatment is negligible within precision (Δ13CH3D = +0.16 ± 0.32‰ and Δ12CH2D2 = +0.14 ± 1.12‰ (n = 16)). Analyses of natural gases from shale basins and variable methane-rich gases emitted from artificial lakes validate the capability of the current pretreatment and spectrometer systems to determine methane clumped isotopes in a wide range of natural environmental samples. [ABSTRACT FROM AUTHOR]

Methane (CH 4 ) is a matter of environmental concern; however, global methane isotopologue data remain inadequate. This is due to the challenges posed by high-resolution testing technology and the need for larger sample volumes. Here, worldwide methane clumped isotope databases ( n = 465) were compiled. We compared machine-learning (ML) models and used random forest (RF) to predict new Δ 12 CH 2 D 2 distributions, which cover valuable and hard-to-replicate methane clumped isotope experimental data. Our RF model yields a reliable and continuous database including ruminants, acetoclastic methane, multiple pyrolysis, and controlled experiments. We showed the effectiveness of utilizing a new data set to quantify isotopologue fractionations in biogeochemical methane processes, as well as predicting the steady-state atmospheric methane clumped isotope composition (Δ 13 CH 3 D of +2.26 ± 0.71‰ and Δ 12 CH 2 D 2 of +62.06 ± 4.42‰) with notable biological contributions. Our measured summer and winter water emitted gases ( n = 6) demonstrated temperature-driven seasonal microbial community evolution determined by atmospheric clumped isotope temporal variations (Δ 13 CH 3 D ∼ -0.91 ± 0.25 ‰ and Δ 12 CH 2 D 2 ∼ +3.86 ± 0.84 ‰), which in turn is relevant for future models quantifying the contribution of methane sources and sinks. Predicting clumped isotopologues translates our methane geochemical understanding into quantifiable variables for modeling that can continue to improve predictions and potentially inform global greenhouse gas emissions and mitigation policy.