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- Ban, Jiaxing, et al.
(author)
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Advances in the use of recycled non-ferrous slag as a resource for non-ferrous metal mine site remediation
- 2022
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In: Environmental Research. - : Elsevier. - 0013-9351 .- 1096-0953. ; 213
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Research review (peer-reviewed)abstract
- The growing global demand for non-ferrous metals has led to serious environmental issues involving uncovered mine site slag dumps that threaten the surrounding soils, surface waters, groundwater, and the atmosphere. Remediation of these slags using substitute cement materials for ordinary Portland cement (OPC) and precursors for alkali-activated materials (AAMs) can convert hazardous solid wastes into valuable construction materials, as well as to attain the desired solidification and stabilization (S/S) of heavy metal(loid)s (HM). This review discusses the current research on the effect of non-ferrous slags on the reaction mechanisms of the OPC and AAM. The S/S of HM from the non-ferrous slags in AAM and OPC is also reviewed. HM can be stabilized in these materials based on the complex salt effect and isomorphic effects. The major challenges faced in AAMs and OPC for HM stabilization include the long-term durability of the matrix (e.g., sulfate attack, stability of volume). The existing knowledge gaps and future trends for the sustainable application of non-ferrous slags are also discussed.
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2. |
- Chang, Keke, et al.
(author)
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Considerations on Circuit Design and Data Acquisition of a Portable Surface Plasmon Resonance Biosensing System
- 2015
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In: Sensors. - : MDPI AG. - 1424-8220. ; 15:8, s. 20511-20523
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Journal article (peer-reviewed)abstract
- The aim of this study was to develop a circuit for an inexpensive portable biosensing system based on surface plasmon resonance spectroscopy. This portable biosensing system designed for field use is characterized by a special structure which consists of a microfluidic cell incorporating a right angle prism functionalized with a biomolecular identification membrane, a laser line generator and a data acquisition circuit board. The data structure, data memory capacity and a line charge-coupled device (CCD) array with a driving circuit for collecting the photoelectric signals are intensively focused on and the high performance analog-to-digital (A/D) converter is comprehensively evaluated. The interface circuit and the photoelectric signal amplifier circuit are first studied to obtain the weak signals from the line CCD array in this experiment. Quantitative measurements for validating the sensitivity of the biosensing system were implemented using ethanol solutions of various concentrations indicated by volume fractions of 5%, 8%, 15%, 20%, 25%, and 30%, respectively, without a biomembrane immobilized on the surface of the SPR sensor. The experiments demonstrated that it is possible to detect a change in the refractive index of an ethanol solution with a sensitivity of 4.99838 × 10(5) ΔRU/RI in terms of the changes in delta response unit with refractive index using this SPR biosensing system, whereby the theoretical limit of detection of 3.3537 × 10(-5) refractive index unit (RIU) and a high linearity at the correlation coefficient of 0.98065. The results obtained from a series of tests confirmed the practicality of this cost-effective portable SPR biosensing system.
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3. |
- Fan, Zheyong, et al.
(author)
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GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations
- 2022
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In: Journal of Chemical Physics. - : AIP Publishing. - 1089-7690 .- 0021-9606. ; 157:11
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Journal article (peer-reviewed)abstract
- We present our latest advancements of machine-learned potentials (MLPs) based on the neuroevolution potential (NEP) framework introduced in Fan et al. [Phys. Rev. B 104, 104309 (2021)] and their implementation in the open-source package gpumd. We increase the accuracy of NEP models both by improving the radial functions in the atomic-environment descriptor using a linear combination of Chebyshev basis functions and by extending the angular descriptor with some four-body and five-body contributions as in the atomic cluster expansion approach. We also detail our efficient implementation of the NEP approach in graphics processing units as well as our workflow for the construction of NEP models and demonstrate their application in large-scale atomistic simulations. By comparing to state-of-the-art MLPs, we show that the NEP approach not only achieves above-average accuracy but also is far more computationally efficient. These results demonstrate that the gpumd package is a promising tool for solving challenging problems requiring highly accurate, large-scale atomistic simulations. To enable the construction of MLPs using a minimal training set, we propose an active-learning scheme based on the latent space of a pre-trained NEP model. Finally, we introduce three separate Python packages, viz., gpyumd, calorine, and pynep, that enable the integration of gpumd into Python workflows.
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