Normality of I-V Measurements Using ML

Electrochemistry ecosystems are promising for accelerating the design and discovery of electrochemical systems for energy storage and conversion, by automating significant parts of workflows that combine synthesis and characterization experiments with computations. They require the integration of flow controllers, solvent containers, pumps, fraction collectors, and potentiostats, all connected to an electrochemical cell. These are specialized instruments with custom software that is not originally designed for network integration. We developed network and software solutions for electrochemical workflows that adapt system and instrument settings in real-time for multiple rounds of experiments. We demonstrate this automated workflow by remotely operating the instruments and collecting their measurements to generate a voltammogram (I-V profile) of an electrolyte solution in an electrochemical cell. These measurements are made available at the remote computing system and used for subsequent analysis. In this paper, we focus on a novel, analytically validated machine learning (ML) method for an electrochemistry ecosystem to ensure that I-V measurements are consistent with the normal experimental conditions, and to detect abnormal conditions, such as disconnected electrodes or low cell content volume.Comment: published at eScience 202

Amazonian Hydrothermal Alteration Comparing Nakhlite Secondary Mineralogy to Water Rock Reaction Experiments

We report on results from experiments with Mars analog materials under diagenetic conditions. The mineralogical results of our experiments suggest that an important type of fluid alteration in the Amazonian may be short duration (e.g. less than 1 year) events from near neutral, dilute brines, that were able to exchange CO2 either directly, or via ice reservoirs, with the atmosphere

Magnetic properties of the geometrically frustrated S=1/2 antiferromagnets, La2LiMoO6 and Ba2YMoO6, with the B-site ordered double perovskite structure: Evidence for a Collective Spin Singlet Ground State

Two B-site ordered double perovskites, La2LiMoO6 and Ba2YMoO6, based on the S = 1/2 ion, Mo5+, have been investigated in the context of geometric magnetic frustration. Powder neutron diffraction, heat capacity, susceptibility, muon spin relaxation(_SR), and 89Y NMR- including MAS NMR- data have been collected. La2LiMoO6 deviates strongly from simple Curie-Weiss paramagnetic behavior below 150K and zero-field cooled/ field cooled (ZFC/FC)irreversibility occurs below 20K with a weak, broad susceptibility maximum near 5K in the ZFC data. A Curie-Weiss fit shows a reduced mu_eff=1.42\mu_B, (spin only = 1.73 muB) and a Weiss temperature, \theta_c, which depends strongly on the temperature range of the fit. Powder neutron diffraction, heat capacity and 7Li NMR show no evidence for long range magnetic order to 2K. On the other hand oscillations develop below 20K in muSR indicating at least short range magnetic correlations. Susceptibility data for Ba2YMoO6 also deviate strongly from the C-W law below 150K with a similarly reduced mu_eff = 1.72\mu_B and \theta_c = - 219(1)K. Heat capacity, neutron powder diffraction and muSR data show no evidence for long range order to 2K but a very broad maximum appears in the heat capacity. The 89Y NMR paramagnetic Knight shift shows a remarkable local spin susceptibility behavior below about 70K with two components from roughly equal sample volumes, one indicating a singlet state and the other a strongly fluctuating paramagnetic state. Further evidence for a singlet state comes from the behavior of the relaxation rate, 1/T1. These results are discussed and compared with those from other isostructural S = 1/2 materials and those based on S = 3/2 and S = 1.Comment: Accepted for publication in Phys. Rev.