Indirect Electrochemical Cooling: Model-Based Performance Analysis and Working Fluid Selection.

The rising energy demand for cooling and heating requires efficient and sustainable technologies. Vapor-compression systems represent the state of the art but suffer from downscaling limits and maintenance needs. These disadvantages may be overcome by recently proposed electrochemical processes. However, their potential has not been explored systematically. This work quantifies the thermodynamic potential of an indirect electrochemical cooling process that replaces the vapor compressor of a standard refrigeration cycle with an electrochemical cell. An equilibrium-based process model evaluates the process performance of a working fluid, depending on its composition and temperatures in the process. After screening an extensive database for possible working fluids, an electrochemical cooling process is analyzed and optimized for the coefficient of performance (COP) to operate between two heat reservoirs at 20 °C (heat source) and 35 °C (heat sink). The majority of the investigated working fluids yield smaller or similar efficiencies than vapor-compression refrigeration, with COPs between 3.0 and 4.0. However, 35 promising working fluids that achieve higher efficiencies are identified with a COP up to 9.63, corresponding to 49% of Carnot. These working fluids are worthy of further investigation as their use in the electrochemical cooling process possibly outperforms standard vapor-compression refrigeration.

Blue and green ammonia production: A techno-economic and life cycle assessment perspective.

Blue and green ammonia production have been proposed as low-carbon alternatives to emissions-intensive conventional ammonia production. Although much attention has been given to comparing these alternatives, it is still not clear which process has better environmental and economic performance. We present a techno-economic analysis and full life cycle assessment to compare the economics and environmental impacts of blue and green ammonia production. We address the importance of time horizon in climate change impact comparisons by employing the Technology Warming Potential, showing that methane leakage can exacerbate the climate change impacts of blue ammonia in short time horizons. We represent a constrained renewable electricity availability scenario by comparing the climate change impact mitigation efficiency per kWh of renewable electricity. Our work emphasizes the importance of maintaining low natural gas leakage for sustainability of blue ammonia, and the potential for technological advances to further reduce the environmental impacts of photovoltaics-based green ammonia.

Electrified hydrocarbon-to-oxygenates coupled to hydrogen evolution for efficient greenhouse gas mitigation.

Chemicals manufacture is among the top greenhouse gas contributors. More than half of the associated emissions are attributable to the sum of ammonia plus oxygenates such as methanol, ethylene glycol and terephthalic acid. Here we explore the impact of electrolyzer systems that couple electrically-powered anodic hydrocarbon-to-oxygenate conversion with cathodic H2 evolution reaction from water. We find that, once anodic hydrocarbon-to-oxygenate conversion is developed with high selectivities, greenhouse gas emissions associated with fossil-based NH3 and oxygenates manufacture can be reduced by up to 88%. We report that low-carbon electricity is not mandatory to enable a net reduction in greenhouse gas emissions: global chemical industry emissions can be reduced by up to 39% even with electricity having the carbon footprint per MWh available in the United States or China today. We conclude with considerations and recommendations for researchers who wish to embark on this research direction.

Correction: A smile is all you need: predicting limiting activity coefficients from SMILES with natural language processing.

[This corrects the article DOI: 10.1039/D2DD00058J.].

A smile is all you need: predicting limiting activity coefficients from SMILES with natural language processing.

The knowledge of mixtures' phase equilibria is crucial in nature and technical chemistry. Phase equilibria calculations of mixtures require activity coefficients. However, experimental data on activity coefficients are often limited due to the high cost of experiments. For an accurate and efficient prediction of activity coefficients, machine learning approaches have been recently developed. However, current machine learning approaches still extrapolate poorly for activity coefficients of unknown molecules. In this work, we introduce a SMILES-to-properties-transformer (SPT), a natural language processing network, to predict binary limiting activity coefficients from SMILES codes. To overcome the limitations of available experimental data, we initially train our network on a large dataset of synthetic data sampled from COSMO-RS (10 million data points) and then fine-tune the model on experimental data (20 870 data points). This training strategy enables the SPT to accurately predict limiting activity coefficients even for unknown molecules, cutting the mean prediction error in half compared to state-of-the-art models for activity coefficient predictions such as COSMO-RS and UNIFACDortmund, and improving on recent machine learning approaches.

Sugar-to-What? An Environmental Merit Order Curve for Biobased Chemicals and Plastics.

The chemical industry aims to reduce its greenhouse gas emissions (GHGs) by adopting biomass as a renewable carbon feedstock. However, biomass is a limited resource. Thus, biomass should preferentially be used in processes that most reduce GHG emissions. However, a lack of harmonization in current life cycle assessment (LCA) literature makes the identification of efficient processes difficult. In this study, 46 fermentation processes from literature are harmonized and analyzed on the basis of their GHG reduction compared with fossil benchmarks. The GHG reduction per amount of sugar used is defined as Sugar-to-X efficiency and used as a performance metric in the following. The analyzed processes span a wide range of Sugar-to-X efficiencies from -3.3 to 6.7 kg of CO2 equiv per kg of sugar input. Diverting sugar from bioethanol production for fuels to the fermentation and bioconversion processes with the highest Sugar-to-X efficiency could reduce the chemical industry's GHG emissions by an additional 130 MT of CO2 equiv without requiring any more biobased feedstocks.

What Shall We Do with Steel Mill Off-Gas: Polygeneration Systems Minimizing Greenhouse Gas Emissions.

Both the global steel and chemical industries contribute largely to industrial greenhouse gas (GHG) emissions. For both industries, GHG emissions are strongly related to the consumption of fossil resources. While the chemical industry often releases GHGs as direct process emissions, steel mills globally produce 1.78 Gt of off-gases each year, which are currently combusted for subsequent heat and electricity generation. However, these steel mill off-gases consist of high value compounds, which also can be utilized as feedstock for chemical production and thereby reduce fossil resource consumption and thus GHG emissions. In the present work, we determine climate-optimal utilization pathways for steel mill off-gases. We combine a nonlinear, disjunctive model of the steel mill off-gas separation system with a large-scale linear model of the chemical industry to perform environmental optimization. The results show that the climate-optimal utilization of steel mill off-gases depends on electricity's carbon footprint: For the current electricity grid mix, methane, hydrogen, and synthesis gas are recovered as feedstocks for conventional chemical production and enable a methanol-based chemical industry. For low electricity footprints in the future, the separation of steel mill off-gases supports CO2-based production processes in the chemical industry, supplying up to 30% of the required CO2. By coupling the global steel and chemical industry, industrial GHG emissions can be reduced by up to 79 Mt CO2-equivalents per year. These reductions provide up to 4.5% additional GHG savings compared to a stand-alone optimization of the two industries, showing a limited potential for this industrial symbiosis.

Environmental trade-offs of direct air capture technologies in climate change mitigation toward 2100.

Direct air capture (DAC) is critical for achieving stringent climate targets, yet the environmental implications of its large-scale deployment have not been evaluated in this context. Performing a prospective life cycle assessment for two promising technologies in a series of climate change mitigation scenarios, we find that electricity sector decarbonization and DAC technology improvements are both indispensable to avoid environmental problem-shifting. Decarbonizing the electricity sector improves the sequestration efficiency, but also increases the terrestrial ecotoxicity and metal depletion levels per tonne of CO2 sequestered via DAC. These increases can be reduced by improvements in DAC material and energy use efficiencies. DAC exhibits regional environmental impact variations, highlighting the importance of smart siting related to energy system planning and integration. DAC deployment aids the achievement of long-term climate targets, its environmental and climate performance however depend on sectoral mitigation actions, and thus should not suggest a relaxation of sectoral decarbonization targets.

The metabolic potential of plastics as biotechnological carbon sources - Review and targets for the future.

The plastic crisis requires drastic measures, especially for the plastics' end-of-life. Mixed plastic fractions are currently difficult to recycle, but microbial metabolism might open new pathways. With new technologies for degradation of plastics to oligo- and monomers, these carbon sources can be used in biotechnology for the upcycling of plastic waste to valuable products, such as bioplastics and biosurfactants. We briefly summarize well-known monomer degradation pathways and computed their theoretical yields for industrially interesting products. With this information in hand, we calculated replacement scenarios of existing fossil-based synthesis routes for the same products. Thereby, we highlight fossil-based products for which plastic monomers might be attractive alternative carbon sources. Notably, not the highest yield of product on substrate of the biochemical route, but rather the (in-)efficiency of the petrochemical routes (i.e., carbon, energy use) determines the potential of biochemical plastic upcycling. Our results might serve as a guide for future metabolic engineering efforts towards a sustainable plastic economy.

Achieving net-zero greenhouse gas emission plastics by a circular carbon economy.

Mitigating life-cycle greenhouse gas emissions of plastics is perceived as energy intensive and costly. We developed a bottom-up model that represents the life cycle of 90% of global plastics to examine pathways to net-zero emission plastics. Our results show that net-zero emission plastics can be achieved by combining biomass and carbon dioxide (CO2) utilization with an effective recycling rate of 70% while saving 34 to 53% of energy. Operational costs for net-zero emission plastics are in the same range as those for linear fossil-based production with carbon capture and storage and could even be substantially reduced. Realizing the full cost-saving potential of 288 billion US dollars requires low-cost supply of biomass and CO2, high-cost supply of oil, and incentivizing large-scale recycling and lowering investment barriers for all technologies that use renewable carbon feedstock.

Renewable carbon feedstock for polymers: environmental benefits from synergistic use of biomass and CO2.

Polymer production is a major source of greenhouse gas (GHG) emissions. To reduce GHG emissions, the polymer industry needs to shift towards renewable carbon feedstocks such as biomass and CO2. Both feedstocks have been shown to reduce GHG emissions in polymer production, however often at the expense of increased utilization of the limited resources biomass and renewable electricity. Here, we explore synergetic effects between biomass and CO2 utilization to reduce both GHG emissions and renewable resource use. For this purpose, we use life cycle assessment (LCA) to quantify the environmental benefits of the combined utilization of biomass and CO2 in the polyurethane supply chain. Our results show that the combined utilization reduces GHG emissions by 13% more than the individual utilization of either biomass or CO2. The synergies between bio- and CO2-based production save about 25% of the limited resources biomass and renewable electricity. The synergistic use of biomass and CO2 also reduces burden shifting from climate change to other environmental impacts, e.g., metal depletion or land use. Our results show how the combined utilization of biomass and CO2 in polymer supply chains reduces both GHG emissions and resource use by exploiting synergies between the feedstocks.

From Unavoidable CO2 Source to CO2 Sink? A Cement Industry Based on CO2 Mineralization.

The cement industry emits 7% of the global anthropogenic greenhouse gas (GHG) emissions. Reducing the GHG emissions of the cement industry is challenging since cement production stoichiometrically generates CO2 during calcination of limestone. In this work, we propose a pathway towards a carbon-neutral cement industry using CO2 mineralization. CO2 mineralization converts CO2 into a thermodynamically stable solid and byproducts that can potentially substitute cement. Hence, CO2 mineralization could reduce the carbon footprint of the cement industry via two mechanisms: (1) capturing and storing CO2 from the flue gas of the cement plant, and (2) reducing clinker usage by substituting cement. However, CO2 mineralization also generates GHG emissions due to the energy required for overcoming the slow reaction kinetics. We, therefore, analyze the carbon footprint of the combined CO2 mineralization and cement production based on life cycle assessment. Our results show that combined CO2 mineralization and cement production using today's energy mix could reduce the carbon footprint of the cement industry by 44% or even up to 85% considering the theoretical potential. Low-carbon energy or higher blending of mineralization products in cement could enable production of carbon-neutral blended cement. With direct air capture, the blended cement could even become carbon-negative. Thus, our results suggest that developing processes and products for combined CO2 mineralization and cement production could transform the cement industry from an unavoidable CO2 source to a CO2 sink.

Reaction Mechanisms and Rate Constants of Auto-Catalytic Urethane Formation and Cleavage Reactions.

The chemistry of urethanes plays a key role in important industrial processes. Although catalysts are often used, the study of the reactions without added catalysts provides the basis for a deeper understanding. For the non-catalytic urethane formation and cleavage reactions, the dominating reaction mechanism has long been debated. To our knowledge, the reaction kinetics have not been predicted quantitatively so far. Therefore, we report a new computational study of urethane formation and cleavage reactions. To analyze various potential reaction mechanisms and to predict the reaction rate constants quantum chemistry and transition state theory were employed. For validation, experimental data from literature and from own experiments were used. Quantitative agreement of experiments and predictions could be demonstrated. The calculations confirm earlier assumptions that urethane formation reactions proceed via mechanisms where alcohol molecules act as auto-catalysts. Our results show that it is essential to consider several transition states corresponding to different reaction orders to enable agreement with experimental observations. Urethane cleavage seems to be catalyzed by an isourethane, leading to an observed 2nd-order dependence of the reaction rate on the urethane concentration. The results of our study support a deeper understanding of the reactions as well as a better description of reaction kinetics and will therefore help in catalyst development and process optimization.

Is the Microgel Collapse a Two-Step Process? Exploiting Cononsolvency to Probe the Collapse Dynamics of Poly-N-isopropylacrylamide (pNIPAM).

Many applications of responsive microgels rely on the fast adaptation of the polymer network. However, the underlying dynamics of the de-/swelling process of the gels have not been fully understood. In the present work, we focus on the collapse kinetics of poly-N-isopropylacrylamide (pNIPAM) microgels due to cononsolvency. Cononsolvency means that either of the pure solvents, e.g., pure water or pure methanol, act as a so-called good solvent, leading to a swollen state of the polymer network. However, in mixtures of water and methanol, the previously swollen network undergoes a drastic volume loss. To further elucidate the cononsolvency transition, pNIPAM microgels with diameters between 20 and 110 µm were synthesized by microfluidics. To follow the dynamics, pure water was suddenly exchanged with an unfavorable mixture of 20 mol% methanol (solvent-jump) within a microfluidic channel. The dynamic response of the microgels was investigated by optical and fluorescence microscopy and Raman microspectroscopy. The experimental data provide unique and detailed insight into the size-dependent kinetics of the volume phase transition due to cononsolvency. The change in the microgel's diameter over time points to a two-step process of the microgel collapse with a biexponential behavior. Furthermore, the dependence between the two time constants from this biexponential behavior and the microgel's diameter in the collapsed state deviates from the square-power law proposed by Tanaka and Fillmore [ J. Chem. Phys. 1979, 70, 1214-1218]. The deviation is discussed considering the adhesion-induced deformation of the gels and the physical processes underlying the collapse.

Generalized Form for Finite-Size Corrections in Mutual Diffusion Coefficients of Multicomponent Mixtures Obtained from Equilibrium Molecular Dynamics Simulation.

The system-size dependence of computed mutual diffusion coefficients of multicomponent mixtures is investigated, and a generalized correction term is derived. The generalized finite-size correction term was validated for the ternary molecular mixture chloroform/acetone/methanol as well as 28 ternary LJ systems. It is shown that only the diagonal elements of the Fick matrix show system-size dependency. The finite-size effects of these elements can be corrected by adding the term derived by Yeh and Hummer (J. Phys. Chem. B 2004, 108, 15873-15879). By performing an eigenvalue analysis of the finite-size effects of the matrix of Fick diffusivities we show that the eigenvector matrix of Fick diffusivities does not depend on the size of the simulation box. Only eigenvalues, which describe the speed of diffusion, depend on the size of the system. An analytic relation for finite-size effects of the matrix of Maxwell-Stefan diffusivities was developed. All Maxwell-Stefan diffusivities depend on the system size, and the required correction depends on the matrix of thermodynamic factors.

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.