Modern mechanical recycling infrastructure for plastic is capable of processing only a small subset of waste plastics, reinforcing the need for parallel disposal methods such as landfilling and incineration. Emerging pyrolysis-based chemical technologies can “upcycle” plastic waste into high-value polymer and chemical products and process a broader range of waste plastics. In this work, we study the economic and environmental benefits of deploying an upcycling infrastructure in the continental United States for producing low-density polyethylene (LDPE) and polypropylene (PP) from post-consumer mixed plastic waste. Our analysis aims to determine the market size that the infrastructure can create, the degree of circularity that it can achieve, the prices for waste and derived products it can propagate, and the environmental benefits of diverting plastic waste from landfill and incineration facilities it can produce. We apply a computational framework that integrates techno-economic analy... [more]

Utilizing sustainable energy sources is crucial for expanding the range of solutions available to meet the growing energy demand and reducing reliance on environmentally damaging and depleting conventional fuels. Biosolids, a type of biomass, are generated as secondary effluent during wastewater treatment process in municipal and industrial sites. These solids possess the potential to serve as a sustainable energy source due to their richness of carbon. For an extended period, biosolids have been landfilled, even though it can be considered a wasteful use of a precious resource and a possible mean for contamination to the food supply chain. This has served as an extra impetus to investigate the potential for harnessing the capabilities of these substances. While many research studies have looked at different ways to put biomass waste to use, very little has been written on biosolids, especially those derived from industrial sources. This research assesses the feasibility of transformin... [more]

Some of the most highly trusted and ubiquitous process simulators have solution methods that are incompatible with algorithms designed for equation-oriented optimization. The natively unconstrained Efficient Global Optimization (EGO) algorithm approximates a black-box simulation with kriging surrogate models to convert the simulation results into a reduced-order model more suitable for optimization. This work evaluates several established constraint-handling approaches for EGO to compare their accuracy, computational efficiency, and reliability using an example simulation of an amine post-combustion carbon capture process. While each approach returned a feasible operating point in the number of iterations provided, none of them effectively converged to a solution, exploring the search space without effectively exploiting promising regions. Using the product of expected improvement and probability of feasibility as next point selection criteria resulted in the best solution value and re... [more]

Critical minerals are essential to the future of clean energy, especially energy storage, electric vehicles, and advanced electronics. In this paper, we argue that process systems engineering (PSE) paradigms provide essential frameworks for enhancing the sustainability and efficiency of critical mineral processing pathways. As a concrete example, we review challenges and opportunities across material-to-infrastructure scales for process intensification (PI) with membranes. Within critical mineral processing, there is a need to reduce environmental impact, especially concerning chemical reagent usage. Feed concentrations and product demand variability require flexible, intensified processes. Further, unique feedstocks require unique processes (i.e., no one-size-fits-all recycling or refining system exists). Membrane materials span a vast design space that allows significant optimization. Therefore, there is a need to rapidly identify the best opportunities for membrane implementation, t... [more]

We study the design and optimization of a multicomponent seawater desalination process with zero liquid discharge (ZLD). The designed process is highly integrated with multiple sub processing units that include humidification-dehumidification, Lithium Bromide absorption chiller, multi-effect evaporators, mechanical vapor compression, and crystallization. Aspen Plus software with E-NRTL and SOLIDS thermodynamic packages are used for modeling and simulation of desalination and crystallization units, respectively. In addition to this, we use data-driven optimization to find the best operating condition (i.e., the temperature of the last effect evaporator) that minimizes the overall energy consumption of the designed plant with an output constraint imposed on the mass fraction of salts going to the ZLD system should be greater than 20 wt.% to achieve the ZLD goal. We use a local sample-based data-driven optimizer, Nonlinear Optimization with the Mesh Adaptive Direct Search (NOMAD) algorith... [more]

To mitigate the effects of catastrophic failure while maintaining resource and production efficiencies, energy systems need to be designed for resilience and sustainability. Conventional approaches such as redundancies through backup processes or inventory stockpiles demand high capital investment and resource allocation. In addition, responding to unexpected “black swan” events requires that systems have the agility to transform and adapt rapidly. To develop targeted solutions that protect the system efficiently, the supply chain network needs to be considered as an integrated multi-scale system incorporating every component from individual process units all the way to the whole network. This approach can be readily integrated with analogous multiscale approaches for sustainability, safety, and intensification. In this work, we bring together classical supply chain resilience with process systems engineering to leverage the multi-scale nature of energy systems for developing resilienc... [more]

Plastics are widely used for their affordability and versatility across many consumer and industrial applications. However, the end-of-life (EoL) management stage can often lead to releasing hazardous chemical additives and degradation products into the environment. The increasing demand for plastics is expected to increase the frequency of material releases throughout the plastic EoL management activities, creating a challenge for policymakers, including ensuring proper material segregation and disposal management and increasing recycling efficiency and material reuse. This research designed a Python-based EoL plastic management tool to support decision-makers in analyzing the holistic impacts of potential plastic waste management policies. The constructed tool was developed to reduce the complexity of material flow analysis calculations, estimating material releases, and environmental impacts. The utility of the tool was tested through the hypothetical nationwide adoption of an exten... [more]

Aiming to mitigate the environmental impact derived from fossil fuels, we propose an integrated carbon capture-biomass gasification process is proposed to produce low-carbon hydrogen as an alternative energy carrier. The process begins with the pre-treatment of empty fruit bunches (EFB), involving grinding, drying, torrefaction, and pelletization. The resulting EFB pellet is then fed into a dual gasifier, followed by a catalytic cracking of tar and water gas shift reaction to produce syngas, aiming to increase its H2 to CO ratio. Subsequently, we explore two alternatives (DEPG and MEA) for syngas upgrading by removing CO2. Finally, a PSA system is modeled to obtain H2 at 99.9% purity. The pre-treatment stage densifies the biomass from an initial composition (%C 46.47, %H 6.22, %O 42.25) to (%C 54.10, %H 6.09, %O 28.67). The dual gasifier operates at 800°C, using steam as a gasifying agent. The resulting syngas has a volume concentration (%CO 20.0, %CO2 28.2, %H2 42.2, %CH4 5.9). Next s... [more]

One of the main challenges to support life in space is the development of sustainable, circular processes that reduce the high cost of resupply missions. Space biomanufacturing is an emerging paradigm that aims to reduce the need for resources, enabling on-demand manufacture of products. The cost of installing biomanufacturing systems in space depends on the cost of transporting the system components, which is directly proportional to their mass/weight. From this perspective, the system mass is a critical factor that dictates process design, and this has important implications in how we can approach such design. For instance, mass constraints require circular use of resources and tight process integration (to minimize resupply) and restricts the type of resources and equipment needed. In this work, we evaluate the lactic acid bioproduction design using Escherichia coli, Saccharomyces cerevisiae, and Pichia pastoris. We use the Equivalent System Mass (ESM) metric as a key design measure... [more]

In this paper, we study the design optimization of methanol production with the goal of minimizing methanol production cost. One challenge of methanol production via carbon dioxide (CO2) hydrogenation is the reduction of operating costs. The simulation of methanol production is implemented within the Aspen HYSYS simulator. The feeds are pure hydrogen and captured CO2. The process simulation involves a single reactor and incorporates recycling at a ratio of 0.995. The methanol production cost is determined using an economic analysis. The cost includes capital and operating costs, which are determined through the equations and data from the capital equipment-costing program. The decision variables are the pressure and temperature of the reactor contents. The optimization problem is solved using a derivative-free algorithm, pyBOUND, a Python-based black-box model optimization algorithm that uses random forests (RFs) and multivariate adaptive regression splines (MARS). The predicted minimu... [more]

2,3 butanediol (BDO) has garnered recent interest due to the high titer concentrations that can be obtained through biochemical routes and its potential for efficient conversion into long-chain hydrocarbons. BDO separation, however, is challenging given its low volatility and high affinity towards water. In this study, two BDO separation pathways were compared, single distillation and combined simulated moving bed (SMB) adsorption with distillation. The separations were incorporated into a 2018 biorefinery design developed by the National Renewable Energy Laboratory (NREL) to produce renewable fuels from corn stover, with BDO as an intermediate and adipic acid as the co-product. The comparison was performed on the basis of sustainability, using lifecycle greenhouse gas (GHG) emissions as the metric. It was found that using a single distillation column gives GHG emissions of 48 gCO2e/MJ for the renewable fuel. This is lower than 93 gCO2e/MJ for petroleum fuel but is higher compared to t... [more]

Sustainable and economically viable plastic recycling methodologies are vital for addressing the increasing environmental consequences of single-use plastics. In this study, we evaluate the plastic waste management value for the state of Georgia, US and investigate the potential of introducing novel depolymerization methods within the network. An equation-based formulation is developed to identify the optimum supply-chain design given the geographic location of existing facilities. Chemical recycling technologies that have received increasing attention are evaluated as candidate technologies to be integrated within the network. The optimum supply-chain design is selected based on environmental and economic objectives. The designed network of pathways uses a mix of different technologies (chemical and mechanical recycling) in a way that are both economically environmentally sound.

The overarching goal of limiting the increase in global temperature to = 2.0° C likely requires both decarbonization and defossilization efforts. Direct air capture (DAC) and CO2 electrolysis stand out as promising technologies for capturing and utilizing atmospheric CO2. In this effort, we explore the details of designing and operating an integrated DAC-electrolysis process by examining some key parameters for economic feasibility. We evaluate the gross profit and net income to find the most appropriate capacity factor, average electricity price, syngas sale price, and CO2 taxes. Additionally, we study an optimistic scenario of CO2 electrolysis and perform a sensitivity analysis of the CO2 capture price to elucidate the impact of design decisions on the economic feasibility. Our findings underscore the necessity of design improvements of the CO2 electrolysis and DAC processes to achieve reasonable capacity factor and average electricity price limits. Notably, CO2 taxes and tax credits... [more]

Recent advances in process design for solvent-based, post-combustion capture (PCC) processes, such as the Piperazine/Advanced Flash Stripper (PZ/AFS) process, have led to a reduction in the energy required for capture. Even though PCC processes are progressively improving in Technology Readiness Levels (TRL), with a few commercial installations, incorporating carbon capture adds cost to any operation. Hence, cost reduction will be instrumental for proliferation. The aim of this work is to improve process economics through optimization and to identify the parameters in our economic model that have the greatest impact on total cost to build and operate these systems. To that end, we investigated changes to the optimal solution and the corresponding cost of capture considering changes in the price of utilities and solvent. We found that changes in solvent price had the most effect on the cost of capture. However, re-optimizing the designs in the event of price changes did not lead to sign... [more]

Circular systems design is an emerging approach for promoting sustainable development. Despite its perceived advantages, the characterization of circular systems remains loosely defined and ambiguous. This work proposes a network optimization framework that evaluates three objective functions related to economic and environmental domains and employs a Pareto analysis to illuminate the trade-offs between objectives. The US polyethylene terephthalate (PET) value chain is selected as a case study and represented via a superstructure containing various recycling pathways. The superstructure optimization problems are modeled as a mixed integer linear program (MILP) and linear programs (LPs), implemented in Pyomo, and solved with CPLEX for a one-year assessment horizon. Solutions to the circular economy models are then compared to the corresponding solutions of linear economy models. Preliminary results show that the optimal circular network is advantageous over the optimal linear network fo... [more]

Initial design stages are inherently complex and often lack comprehensive information, posing challenges in evaluating sustainability metrics. Machine Learning (ML) emerges as a valuable solution to address these challenges. ML algorithms, particularly effective in predicting environmental impacts of new chemicals with limited data, enable more informed decisions in sustainable design. This study focuses on employing ML for predicting the environmental impacts related to human health, ecosystem quality, climate change, and resource utilization to aid in early-stage environmental impact assessment of chemical processes. The effectiveness of the ML algorithm, eXtreme Gradient Boosting (XGBoost) tested using a dataset of 350 points, divided into training, testing, and validation sets. The study also includes a practical application of the model in a cradle-to-cradle LCA of N-Methylpyrrolidone (NMP), demonstrating its utility in sustainable chemical process design. This approach signifies... [more]

This study delves into the development and examination of various mathematical models for conventional steam-methane reforming (SMR) reactors, establishing a foundational basis for an electrified SMR reactor design. Distinct mathematical models with different scales and dimensions are derived. A basic 1D-fluid, 0D-catalyst (1D-0D) pseudo-homogeneous model is validated with plant data, and progressively advanced to a 2D-0D model considering radial transfer, then further extended to a rigorous 2D-1D model considering transfer phenomena between catalyst particle and fluid. Simulation cases are conducted under uniform design parameters, heat source and operation conditions. Comparative analyses focus on several key performance aspects, including temperature, reaction rate distribution, and outlet characteristics such as temperature, pressure, flow rate, composition and CH4 conversion. The models effectively describe the industrial SMR reactor behavior. Influences of scale and dimension of... [more]

The synthesis of energy systems necessitates simultaneous optimization of both design and operation across all components within the energy system. In real-world applications, this synthesis poses a mixed-integer nonlinear programming (MINLP) problem, considering nonlinear behaviours such as investment cost curves and part-load performance. The complexity increases further when seasonal energy storage is involved, as it requires temporal coupling of the full time series. Although numerous solution approaches exist to solve the synthesis problems simplified by linearization, methods for solving a full-scale problem are currently missing. In this work, we introduce a rigorous method, RiNSES4, to manage the nonlinear aspects of energy system synthesis, particularly focusing on long-term time-coupling constraints. RiNSES4 calculates the upper and lower bounds of the initial synthesis problem in two separate branches. The proposed method yields feasible solutions through upper bounds, while... [more]

The placement of wind turbines is a crucial design element in wind farms, given the energy losses resulting from the wake effect. Despite numerous studies addressing the Wind Farm Layout Optimization (WFLO) problem, considering multiple directions to determine wind turbine spacing and layout remains limited. However, relying solely on one predominant direction may lead to overestimating energy production, and loss of energy generation. This work introduces a novel mathematical programming optimization framework to solve the WFLO problem, emphasizing the wind energy's nonlinear characteristics and wake effect losses. Comparisons with traditional layout approaches demonstrate the importance of optimizing wind farm layouts during the design phase. By providing valuable insights into the renewable energy sector, this research aims to guide future wind farm projects towards layouts that balance economic considerations with maximizing energy production.

In view of achieving the decarbonization target, green hydrogen is commonly regarded as the alternative capable of reducing the share of fossil fuels. Despite its wide application as a chemical on industrial scale, hydrogen utilization as an energy vector still suffers from unfavorable economics, mainly due to its high cost of production, storage and transportation. To overcome the last two of these issues, different hydrogen carriers have been proposed. Hydrogen storage and transportation through these carriers involve: 1. the carrier hydrogenation, exploiting green hydrogen produced at the loading terminal, where renewable sources are easily accessible, 2. the storage and transportation of the hydrogenated species and 3. its subsequent dehydrogenation at the unloading terminal, to favour H2 release. Although there is a number of studies in literature on the economic feasibility of hydrogen transport through different H2 vectors, very few of them delve into the technical evaluation of... [more]

The transition to net-zero greenhouse gas emissions requires a rapid redesign of energy systems. However, the redesign may shift environmental impacts to other categories than climate change. To assess the sustainability of the resulting impacts, the planetary boundaries framework provides absolute limits for environmental sustainability. This study uses the planetary boundaries framework to assess net-zero sector-coupled energy system designs for absolute environmental sustainability. Considering Germany as a case study, we extend the common focus on climate change in sustainable energy system design to seven additional Earth-system processes crucial for maintaining conditions favorable to human well-being. Our assessment reveals that transitioning to net-zero greenhouse gas emissions reduces many environmental impacts but is not equivalent to sustainability, as all net-zero designs transgress at least one planetary boundary. However, the environmental impacts vary substantially betwe... [more]

Biogas is often considered as a source of renewable energy, for heat and power production. However, biogas has greater promise as a source of concentrated CO2 in addition to methane, making it a rich supply of carbon and hydrogen for the generation of fuel and chemicals. In this work, we use the concept of attainable region in the enthalpy-Gibbs free energy space to identify opportunities for effective biogas valorization that maximizes the conversion of CO2. The AR concept allows us to study a chemical process without knowing the exact reaction mechanism that the species in the process use. Deriving Material Balance equations that relate a reactive process's output species to its input species is sufficient to identify process limits and explore opportunities to optimize its performance in terms of material, energy, and work. The conversion of biogas to valuable products is currently done in two steps; the high temperature and endothermic reformer step, followed by the low temperatur... [more]

We study the impact of switching from combustion heating to electric heating in processes comprising high temperature reaction/separation sequences, where the heat supporting the reaction(s) is substantially provided by combusting a reaction byproduct (fuel gas). A canonical process structure is de?ned. It is shown that the conventional combustion- based process presents signi?cant interactions. An asymptotic analysis is utilized to investigate and compare the dynamic responses of the conventional and electric process configurations. It is demonstrated that the dynamic behavior of the two processes exhibits two timescales, with the faster corresponding to the evolution of the temperatures of the units with high heat duty, and the slow time scale capturing the variables involved in the material balance. A simpli?ed ethylene cracking process example is used to demonstrate these findings.

As a promising electricity storage system, Liquid Air Energy Storage (LAES) has the main advantage of being geographically unconstrained. LAES has a considerable potential in energy efficiency improvement by utilizing compression heat and integrating with other systems. In this work, the Stirling Engine (SE) is introduced to improve the energy efficiency of the LAES system. Three LAES-SE systems are modelled in Aspen HYSYS and optimized by the Particle Swarm Optimization (PSO) algorithm. The studied systems include (i) the LAES system with 3 compressors and 3 expanders (3C+3E) using an SE to recover the compression heat, (ii) the 3C+3E LAES system with LNG regasification and SE, and (iii) the 3C+3E LAES system with solar energy and SE. The optimization results show that the Round-Trip Efficiencies (RTEs) of the LAES-SE system and the LNG-LAES-SE systems are 68.2% and 73.7%, which are 3.2% and 8.7% points higher than the basic 3C+3E LAES-ORC system with an RTE of 65.0%. For the Solar-LA... [more]

An important measure to achieve global reduction in CO2 emissions is CO2 capture, transport, and storage. The deployment of CO2 capture requires the development of a shared CO2 transport infrastructure, where CO2 can be transported with different transport modes. Furthermore, the cost of CO2 transport can be subject to significant economies of scale effects with respect to the amount of CO2 transported, also mentioned as clustering effects. Therefore, optimizing the shared infrastructure of multiple CO2 sources can lead to significant reductions in infrastructure costs. This paper presents a novel formulation of the clustered CO2 transport network. The Markov Decision Process formulation defined here allows for more detailed modeling of non-linear, discrete transport costs and increased geographical resolution. The clustering effects are modeled through cooperative multi-agent interactions. A multi-agent, reinforcement learning-based algorithm is proposed to optimize the shared transpo... [more]