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At least 19 records

Solvent Screening for Separation Processes Using Machine Learning and High-Throughput Technologies

As the chemical industry shifts toward sustainable practices, there is a growing initiative to replace conventional fossil-derived solvents with environmentally friendly alternatives such as ionic liquids (ILs) and deep eutectic solvents (DESs). Artificial intelligence (AI) plays a key role in the discovery and design of novel solvents and the development of green processes. This review explores the latest advancements in AI-assisted solvent screening with a specific focus on machine learning (ML) models for physicochemical property prediction and separation process design. Additionally, this paper highlights recent progress in the development of automated high-throughput (HT) platforms for solvent screening. Finally, this paper discusses the challenges and prospects of ML-driven HT strategies for green solvent design and optimization. To this end, this review provides key insights to advance solvent screening strategies for future chemical and separation processes.

Artificial intelligence↗

Pilot Scale Testing of the Hydrophobic-Hydrophilic Separation Process to Produce Value-Added Products from Waste Coal

The primary objective of this project was to demonstrate the technical and economic feasibility of using the hydrophobic-hydrophilic separation (HHS) process to produce high-purity, value-added clean coal that could serve as feedstock for specialty carbon products from waste coal. An existing one-skid (i.e., the entire unit fits on a single tractor-trailer) HHS pilot-scale facility was used to process bituminous and anthracite waste coals to produce: 1) a clean coal containing less than 5% ash (super-clean) and 2) another containing less than 1.5% ash (ultra-clean), all of which contain single-digit moistures. Sufficient quantities of these products were to be generated to permit detailed evaluations by potential customers producing or developing new, high-value market applications. In addition, the project included the evaluation of several process improvements to reduce the capital and operating costs for a commercial HHS plant. A final objective was to complete an economic analysis, market-penetration analysis, and technology-gap analysis of the HHS technology and its products.

01 COAL, LIGNITE, AND PEAT↗

The Production of Low Ash Coals Using the Hydrophobic-Hydrophilic Separation Process with Novel Developments

Froth flotation is a common mineral processing method in coal preparation. This process becomes less efficient, however, as particle size is reduced, and ultrafine particles are often discarded prior to froth flotation, contributing to a substantial amount of coal waste in impoundments. Because of the land-use and risk of an impoundment failure, these impoundments pose an environmental liability. To address ultrafine coal rejection, researchers at Virginia Tech developed the hydrophobic-hydrophilic separation (HHS) process. Unlike in froth flotation, HHS uses an organic solvent to separate and dewater hydrophobic particles from hydrophilic minerals. Past work on the HHS process yielded promising results. In particular, the HHS process has produced a low-ash (<2%) and low moisture (<8%) product, which is a viable feed stock for carbon products. In this work, an investigation of the effects of auxiliary processes on the HHS process was conducted. The auxiliary processes included grinding, pre-concentration, and reagent conditioning. This work also contains an investigation on the interaction between two primary unit operations in the HHS process: oil agglomeration and de-emulsification. Lastly, to make the HHS process more viable for commercial scale-up, a novel unit operation was developed and tested that performs comparably to the current HHS process.

01 COAL, LIGNITE, AND PEAT↗

Developing Digital Twin Visualizations: A Methodology and Case Study on Chemical Separation Processing

As advances in digital engineering continue to push the technological boundaries, digital twin (DT) visualizations for diagnostics and safeguards advancement become much more feasible and practical. DTs generate large and complex data streams that require effective user interfaces to provide monitoring and diagnostic capabilities. Unfortunately, while these frameworks exist, there is not much research on the systematic documentation of human–computer interaction (HCI) for DT visualization. This work presents a dual-mode visualization methodology (two dimensional [2D] graphical user interface dashboard and 3D mixed reality) designed to support diagnostic tasks in DT systems and building on a validated framework and applying established HCI principles. The methodology is demonstrated through a case study of aqueous processing at Idaho National Laboratory, using experimental data from the chemical solvent extraction runs. Our interfaces display real-time alerts and monitoring to inform users of safeguards anomalies. The interfaces use immersive 3D mixed-reality visualization for further system and experiment investigation. This work demonstrates how the systematic application of HCI principles can inform DT visualization design for diagnostic and safeguards applications. While formal user evaluation studies remain as future work, this paper documents the systematic design methodology and demonstrates a proof-of-concept implementation.

3D visualization↗

Quantifying the environmental benefits of a solvent-based separation process for multilayer plastic films

Food packaging often appears in the form of multilayer (ML) plastic films, which leverage the functional properties of different polymers to achieve specific food protection goals (e.g., oxygen, water, and temperature barriers). These properties are essential to enable long shelf lives, reduce refrigeration usage, mitigate food waste, and increase food accessibility. However, ML film production processes generate large amounts of plastic waste that cannot be mechanically recycled. Recently, we have proposed a process, called solvent-targeted recovery and precipitation (STRAP), that enables the separation and recycling of the constituent polymers of ML films. This technology uses a series of solvent washes that selectively dissolve and precipitate target polymers. Quantifying the environmental benefits of STRAP over virgin resin production is essential for the commercial deployment of this technology. Further, this work uses life cycle assessment (LCA) methods to evaluate these impacts in terms of carbon footprint, energy use, water use, and toxicity. We analyze three STRAP process variants that use antisolvent and temperature-driven precipitation to treat different ML films. Our analysis reveals that the STRAP-A and STRAP-B process variants can provide environmental benefits over virgin film production. Furthermore, it gives valuable insight into the critical components of ML films (specific polymers) and of the STRAP processes (equipment) that are responsible for the highest impacts. Ultimately, we believe that the proposed analysis framework can lead to the design of more environmentally-friendly ML films and recycling processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Separation Process of Plant Fibers for Textile and Composite Application: A Review of Recent Advances

Plant fiber resources have gained significant attention for value-added utilization due to their renewability, sustainability, abundance, and widely acknowledged physical properties. The efficient and pragmatic separation of plant fibers is a critical process for their efficient utilization, yet a substantial gap persists between laboratory research advancements and their commercialization. To increase the possibility of research advancements for industrial application, this review summarizes the recent advances in different extraction methodologies of plant fiber research in textile and composite fields. It systematically outlines, compares, and contrasts physical (cryogenic, supercritical carbon dioxide, ultrasonic, steam explosion and microwave heating treatment), chemical (alkali, oxidation, organic solvents and deep eutectic solvents methods), and biological (natural retting, enzymatic and microorganism approaches) methods, addressing their respective mechanisms, strengths, limitations, research progress, and future prospects. In general, traditional chemical approaches have proven significantly effective but are accompanied by high pollution. Conversely, novel chemical treatments such as deep eutectic solvents and organic solvents offer a promising blend of efficiency and environmental friendliness but require deeper studies currently. Meanwhile, physical and biological treatments, though largely eco-friendly, tend to suffer from lower separation efficiencies. The research needs and future direction are also addressed to bridge the gap between scientific advancements and their widespread industrial application.

60 APPLIED LIFE SCIENCES↗

Polymeric materials for electrochemical cells and ion separation processes

Polymers of intrinsic microporosity are provided herein. Disclosed polymers of intrinsic microporosity include modified polymers of intrinsic microporosity that include negatively charged sites or crosslinking between monomer units. Systems making use of polymers of intrinsic microporosity and modified polymers of intrinsic microporosity are also described, such as electrochemical cells and ion separation systems. Methods for making and using polymers of intrinsic microporosity and modified polymers of intrinsic microporosity are also disclosed.

Helms, Brett A.↗

An in-situ conductometric apparatus for physicochemical characterization of solutions and in-line monitoring of separation processes at elevated temperatures and pressures

Specific conductance and frequency-dependent resistance (impedance) data are widely utilized for understanding the physicochemical characteristics of aqueous and non-aqueous fluids and for evaluating the performance of chemical processes. However, the implementation of such an in-situ probe in high-temperature and high-pressure environments is not trivial. This work provides a description of both the hardware and software associated with implementing a parallel-type in-situ electrochemical sensor. The sensor can be used for in-line monitoring of thermal desalination processes and for impedance measurements in fluids at high temperature and pressure. Further, a comparison between the experimental measurements on the specific conductance in aqueous sodium chloride solutions and the conductance model demonstrate that the methodology yields reasonable agreement with both the model and literature data. A combination of hardware components, a software-based correction for experimental artifacts, and computational fluid dynamics (CFD) calculations used in this work provide a sound basis for implementing such in-situ electrochemical sensors to measure frequency-dependent resistance spectra.

47 OTHER INSTRUMENTATION↗

Recovery of materials from electrode scraps and spent lithium-ion batteries via a green solvent-based separation process

A method for recycling lithium-ion battery materials is provided. The method includes isolating a composite electrode comprising an electrode material adhered to a current collector with a polyvinylidene difluoride (PVDF) binder. The composite electrode is combined with triethyl phosphate (TEP) as a solvent to form a mixture. The electrode material is delaminated from the current collector in the mixture to give a free electrode material and a free current collector. Each of the free electrode material and the free current collector is recovered from the mixture. The free electrode material may be reused to prepare another composite electrode, as well as a lithium-ion battery comprising the same, which are also disclosed.

Belharouak, Ilias↗

Buffer-IPyC separation process in TRISO fuel particles simulated with Bison code

During High Temperature Gas-cooled Reactor (HTGR) operation, tristructural isotropic (TRISO) coated-particle fuel undergoes irradiation-induced changes in morphology and thermomechanical properties. Experimental results from the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program show, among other things, the mechanism of gap formation between the buffer and inner pyrolytic carbon (IPyC) layers, which could be explored further via computational simulations using the Bison code. Two simulation models were developed, the debonding restricted model, where no gap formation between buffer and IPyC layers is permitted, and the debonding enabled model, where the gap between those layers is created. The inputs of the simulated models are based on the irradiation conditions from the AGR-1 experiment. The research included simulations on spherical and aspherical fuel types. Under the specific temperatures and fluences of the AGR-1 irradiation experiment, and the Bison simulations, it was concluded that the most common scenario is a gap formation along the buffer-IPyC interface, while the least possible scenario is the situation where there is no gap formation at the buffer-IPyC junction. The computational results confirmed that the sphericity of the fuel influences the thickness of the gap that occurs at the buffer-IPyC junction, in a way that with increasing aspect ratio the gap thickness increases. The results obtained for spherical and aspherical fuel are nearly identical. Finally, performed simulations match conclusions observed from the AGR-1 experiment, which as such shows that the Bison code is a good computational method for simulating the TRISO fuel. Future simulations will include the validation of performed research and comparison of the results between Bison and PARFUME codes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Methodology for assessing the maximum potential impact of separations opportunities in industrial processes

Separation technologies currently used in U.S. manufacturing industries are estimated to account for more than 20% of plant energy consumption. However, accurately determining the impact of new separation technology solutions can sometimes be difficult, especially when evaluating a slate of new candidate separation technologies, each of which has its own separation performance, energy demand, and capital cost. In these cases, a typical approach is to assess each new separation technology by collecting performance and cost information and then using that information to develop a techno-economic analysis to identify overall benefits. While this approach is thorough, it can be time consuming and can hinder reaching a critical understanding of the potential of a given separation challenge, especially when there is no known solution. To address these issues, we developed an assessment methodology, using industrial screening processes, that can be used to better understand the potential impacts of addressing a given separation challenge. This paper presents an overview of our separation challenge stream assessment methodology. The methodology involves defining an “ideal” separator and deriving the associated minimum separation energy. The “ideal” separator represents the most optimistic outlook of a given opportunity so the maximum impact from existing and not-yet-developed solutions can be assessed. Using established biorefinery models, we applied the methodology to 10 different separation challenge streams from two different biomass conversion platforms to identify the type of information that can be obtained. Three of the ten challenge streams assessed had maximum possible cost savings predictions >20%, and associated reductions in process energy carbon intensity ranging from 0 to 54%. Two streams had cost and energy savings potential that were < 5%. Some of the opportunity drivers from the various assessments include higher product yields, reduction or elimination of downstream equipment, new co-products, and cost savings associated with raw materials and energy consumption. The information from these assessments can help guide the selection or development of new separation technology solutions based on the various potential factors that drive the projected benefits.

09 BIOMASS FUELS↗

A parametric approach to identify synergistic domains of process intensification for reactive separation

Process intensification aims to combine multiple tasks within multi-functional units to drastically improve economic, energy or sustainability metrics of a chemical process. Limited work exists to systematically identify the synergistic domains where intensification outperforms its nonintensified counterpart. In this work, we computationally derive the synergistic domains of a reactive separation system. Specifically, we first postulate general models for both intensified and nonintensified systems. We use these models to generate data to train a ReLU-type artifical neural network (ANN). Further, the trained ReLU-NN model is formulated as a multi-parametric mixed-integer linear program (mp-MILP), and the critical regions of this mp-MILP define the synergistic feasible domains of intensification. We have derived these synergistic domains of vapor–liquid equilibrium (VLE)-based reactive separation for several industrial applications. These synergistic domains enable quick screening of properties that favor intensification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling Isotope Separation in Electrochemical Lithium Deposition

Naturally occurring Li consists of two stable isotopes, 6 Li with an abundance of about 7.5%, and 7 Li making up the remainder with 92.5%. The development of a 6 Li enrichment technique, in terms of technical reliability and environmental safety to reach 6 Li future requirements, represents a key step in the roadmap for nuclear fusion energy supply worldwide. This paper uses finite element analysis-based models to simulate electrochemical Li isotope separation, which is an attractive method in terms of simplicity, safety, and scalability. In the model, we quantitatively analyze how different electrochemical factors including thermodynamics, charge-transfer kinetics, and diffusivities affect the separation process (separation factor), together with cell parameters, such as cell length and current density. The maximum separation factor of 1.128 could be obtained with the cell under the optimal thermodynamic, kinetic, and diffusive conditions, which is among the highest separation factors ever reported. Furthermore, these results will assist in designing the actual isotope separation setup with large separation factor and appropriate timing for sample collection.

07 ISOTOPE AND RADIATION SOURCES↗