Machine-learning-driven discovery of metal-organic framework adsorbents for hexavalent chromium removal from aqueous environments

HYPOTHESIS

Metal-organic frameworks (MOFs) have been widely studied for Cr(VI) adsorption in water. Theoretically, numerous MOFs can be synthesised by assembling diverse metals and ligands. However, the traditional manual experimentation for screening high-performance MOFs is resource-intensive and inefficient.

EXPERIMENTS

A screening strategy for MOFs based on machine learning was proposed for the adsorption and removal of Cr(VI) from water. By collecting the characteristics of MOFs and the experimental parameters of Cr(VI) adsorption from the literature, a dataset was constructed to predict the adsorption performance. Among the six regression models, the model trained by the extreme gradient boosted tree algorithm had the best performance and was used to simulate the adsorption and screen potential high-performance adsorbents.

FINDINGS

Structure-property analysis indicated that prepared MOF adsorbents with properties of 0.37 < largest cavity diameter < 0.71 nm, 0.18 < pore volume < 0.57 cm3/g, 412 < specific surface area < 1588 m2/g, 0.43 < void fraction < 0.62 will achieve enhanced adsorption of Cr(VI) in water. High-performance adsorbents were successfully screened using a combination of machine-learning prediction and analysis. Experiments were conducted to verify the exceptional adsorption capacity of UiO-66 and MOF-801. This method effectively identified adsorbents and accelerated the development of new MOF adsorbents for contaminant removal, providing a novel approach for the discovery of superior adsorbents.

Monte Carlo simulation of background components in low level Germanium spectrometry

This proceeding presents the decomposition of the background spectra of the four screening detectors GeMPI 1 - 4 at the Gran Sasso Underground Laboratory (LNGS) using Monte Carlo simulations in the Geant4-based framework MaGe. A detailed understanding of the composition of the background spectra was achieved, allowing for the proposal of two new shield designs for future GeMPI-like detectors and enabling a reduction of the integrated background count rate to 15 counts/d/kg in the interval [40, 2700] keV.

Development of ultralow-background cryogenic calorimeters for the measurement of surface α contamination

Next-generation experiments searching for rare events must satisfy increasingly stringent requirements on the bulk and surface radioactive contamination of their active and structural materials. The measurement of surface contamination is particularly challenging, as no existing technology is capable of separately measuring parts of the ²³²Th and ²³⁸U decay chains that are commonly found to be out of secular equilibrium. We will present the results obtained with a detector prototype consisting of 8 silicon wafers of 150 mm diameter instrumented as bolometers and operated in a low-background dilution refrigerator at the Gran Sasso Underground Laboratory of INFN, Italy. The prototype was characterized by a baseline energy resolution of few keV and a background <100 nBq/cm² in the full range of  α energies, obtained with simple procedures for cleaning of all employed materials and no specific measures to prevent recontamination. Such performance, together with the modularity of the detector design, demonstrate the possibility to realize an alpha detector capable of separately measuring all alpha emitters of the ²³²Th and ²³⁸U chains, possibly reaching a sensitivity of few nBq/cm².

Optimal design for a μBq/kg gamma spectrometer based on Monte Carlo simulation

In response to the urgent requirement of material screening in rare event experiments, a new ARray of GermaniUm γ-ray Spectrometer (ARGUS) is planned to be established in China Jinping Underground Laboratory (CJPL). The spectrometer was optimized with Monte Carlo simulation using Geant4. Five HPGe detectors were combined in ARGUS for higher efficiency. Two shielding systems, one with liquid nitrogen, the other with lead plus copper were evaluated. With the combination of multiple detectors, low activity materials and the optimized design of shielding systems, the decision threshold at the level of 10μBq/kg for ²³⁸U/²³²Th decay chain could be achieved.