A Multiobjective Optimization Including Results of Life Cycle Assessment in Developing Biorenewables-Based Processes

Optimization Design of Planar Circle Coil for Limited-Size Wireless Power Transfer System

Power Transfer Efficiency (PTE) and Transferred Power (TP) are two crucial indicators of the wireless power transfer (WPT) system. However, in most compensatory topologies, the ideal coils design parameters of PTE and TP are inconsistent, implying that optimizing for one indicator would make another indicator less effective. As a result, in this article, the Thompson sampling efficient multi-objective optimization (TSEMO) algorithm is used to simultaneously optimize PTE and TP in the S-S compensation topology. Through the co-calculation of MATLAB and COMSOL, the coils can be optimized in the environment of magnetic material (ferrite) and conductive material (aluminum). Coils larger than the underwater vehicle’s size are deleted during the data interaction between MATLAB and COMSOL to guarantee that the optimal PTE and TP can be attained within the constrained area. Due to the open standard external software packages between MATLAB and COMSOL, the entire optimization process may be automated. The results show that for WPT systems with restricted input voltage, such as the battery, this design strategy can achieve better TP at the expense of lower PTE, which is highly beneficial in improving the system’s overall performance.

A Comprehensive Modeling Analysis of Formate-Mediated Microbial Electrosynthesis*

Mediated microbial electrosynthesis (MES) represents a promising strategy for the capture and conversion of CO₂ into carbon-based products. We describe the development and application of a comprehensive multiphysics model to analyze a formate-mediated MES reactor. The model shows that this system can achieve a biomass productivity of ∼1.7 g L^-1  h^-1 but is limited by a competitive trade-off between O₂ gas/liquid mass transfer and CO₂ transport to the cathode. Synthetic metabolic strategies are evaluated for formatotrophic growth, which can enable an energy efficiency of ∼21 %, a 30 % improvement over the Calvin cycle. However, carbon utilization efficiency is only ∼10 % in the best cases due to a futile CO₂ cycle, so gas recycling will be necessary for greater efficiency. Finally, separating electrochemical and microbial processes into separate reactors enables a higher biomass productivity of ∼2.4 g L^-1  h^-1 . The mediated MES model and analysis presented here can guide process design for conversion of CO₂ into renewable chemical feedstocks.

Allocation of Environmental Impacts in Circular and Cascade Use of Resources—Incentive-Driven Allocation as a Prerequisite for Cascade Persistence

In cascade use, a resource is used consecutively in different application areas demanding less and less quality. As this practically allows using the same resource several times, cascading contributes to resource efficiency and a circular economy and, therefore, has gained interest recently. To assess the advantages of cascading and to distribute the environmental impacts arising from resource extraction/processing, potentially needed treatment and upcycling within the cascade chain and end-of-life proesses represent a difficult task within life cycle assessment and highlight the needs for a widely applicable and acceptable framework of how to allocate the impacts. To get insight into how the allocation is handled in cascades, a systematic literature review was carried out. Starting from this status quo, common allocation approaches were extracted, harmonized, and evaluated for which a generic set of criteria was deduced from the literature. Most importantly, participants must be willing to set up a cascade, which requires that for each participant, there are individual benefits, e.g., getting less environmental burdens allocated than if not joining. A game-theoretic approach based on the concept of the core and the Shapley value was presented, and the approaches were benchmarked against this in a case-study setting. Several of the approaches laid outside the core, i.e., they did not give an incentive to the participants to join the cascade in the case study. Their application for cascade use is, therefore, debatable. The core was identified as an approach for identifying suitable allocation procedures for a problem at hand, and the Shapley value identified as a slightly more complex but fair allocation procedure.

Exploration of New Biomass-Derived Solvents: Application to Carboxylation Reactions

A range of hitherto unexplored biomass-derived chemicals have been evaluated as new sustainable solvents for a large variety of CO2 -based carboxylation reactions. Known biomass-derived solvents (biosolvents) are also included in the study and the results are compared with commonly used solvents for the reactions. Biosolvents can be efficiently applied in a variety of carboxylation reactions, such as Cu-catalyzed carboxylation of organoboranes and organoboronates, metal-catalyzed hydrocarboxylation, borocarboxylation, and other related reactions. For many of these reactions, the use of biosolvents provides comparable or better yields than the commonly used solvents. The best biosolvents identified are the so far unexplored candidates isosorbide dimethyl ether, acetaldehyde diethyl acetal, rose oxide, and eucalyptol, alongside the known biosolvent 2-methyltetrahydrofuran. This strategy was used for the synthesis of the commercial drugs Fenoprofen and Flurbiprofen.

Life Cycle Assessment for the Design of Chemical Processes, Products, and Supply Chains

Design in the chemical industry increasingly aims not only at economic but also at environmental targets. Environmental targets are usually best quantified using the standardized, holistic method of life cycle assessment (LCA). The resulting life cycle perspective poses a major challenge to chemical engineering design because the design scope is expanded to include process, product, and supply chain. Here, we first provide a brief tutorial highlighting key elements of LCA. Methods to fill data gaps in LCA are discussed, as capturing the full life cycle is data intensive. On this basis, we review recent methods for integrating LCA into the design of chemical processes, products, and supply chains. Whereas adding LCA as a posteriori tool for decision support can be regarded as established, the integration of LCA into the design process is an active field of research. We present recent advances and derive future challenges for LCA-based design.

Machine learning and molecular descriptors enable rational solvent selection in asymmetric catalysis

Rational solvent selection remains a significant challenge in process development. Here we describe a hybrid mechanistic-machine learning approach, geared towards automated process development workflow. A library of 459 solvents was used, for which 12 conventional molecular descriptors, two reaction-specific descriptors, and additional descriptors based on screening charge density, were calculated. Gaussian process surrogate models were trained on experimental data from a Rh(CO)2(acac)/Josiphos catalysed asymmetric hydrogenation of a chiral α-β unsaturated γ-lactam. With two simultaneous objectives - high conversion and high diastereomeric excess - the multi-objective algorithm, trained on the initial dataset of 25 solvents, has identified solvents leading to better reaction outcomes. In addition to being a powerful design of experiments (DoE) methodology, the resulting Gaussian process surrogate model for conversion is, in statistical terms, predictive, with a cross-validation correlation coefficient of 0.84. After identifying promising solvents, the composition of solvent mixtures and optimal reaction temperature were found using a black-box Bayesian optimisation. We then demonstrated the application of a new genetic programming approach to select an appropriate machine learning model for a specific physical system, which should allow the transition of the overall process development workflow into the future robotic laboratories.

Identification of strategic molecules for future circular supply chains using large reaction networks

Networks of chemical reactions represent relationships between molecules within chemical supply chains and promise to enhance planning of multi-step synthesis routes from bio-renewable feedstocks.