Ammonia as a hydrogen carrier is an emerging route to the hydrogen economy for cleaner and environmentally friendly energy systems. Recovering hydrogen from ammonia by decomposition in ammonia-cracking reactors is an established technology. With ammonia gaining significance as a green hydrogen carrier, it must be studied as a part of larger integrated energy systems. Surrogate modeling of the ammonia decomposition reactor aids real-time optimization and digital twins, yet research work on the topic is scarce, if available at all. To address this gap, a robust data-driven model of an ammonia cracker was developed from CFD-generated data of a reactor producing 200 kg/day of hydrogen. A segment-wise surrogate modeling approach was followed to enable the surrogate model to predict the reactor performance at varying parameter values not only at the reactor inlet but also inside the reactor. This method was successfully applied to vary the kinetic reaction rate along the length of the reactor and find the optimum catalyst loading distribution through the application of the genetic algorithm. The optimization results predicted about 20% savings in catalyst load with less than 1% decrease in ammonia conversion. Valuable insights are gained in the surrogate modeling of the ammonia cracker system.

As the hydrogen society emerges, hydrogen refueling stations (HRSs) should be installed to accommodate the demand for fuel-cell electric vehicles. In this study, to determine the acceptable HRS for urban areas, off-site and on-site HRSs were investigated using techno-economic, life-cycle, and quantitative risk assessments to evaluate their economic, environmental, and safety performances. Five promising hydrogen sources (compressed hydrogen, liquid hydrogen, ammonia, natural gas, and water electrolysis) were selected for a defined urban HRS capable of producing 600 kg of hydrogen daily. The results revealed that gaseous HRSs are the most dangerous HRS because of the explosion risk of the compressed hydrogen stored in the tube; however, their lack of hydrogenation or liquefaction processes makes them the most cost-effective and environmentally friendly, with a levelized cost of 7.32 $/kgH2 and a carbon intensity of 13.72 kgCO2-eq/kgH2. When renewable energy systems become commercialized and the use of green electricity and hydrogen becomes popular, liquid HRSs are projected to perform best, with 5.73 $/kgH₂ and 1.47 kgCO₂-eq/kgH₂. This advantage is attributed to their simple process structure and low energy consumption from employing cryogenic pumps instead of gas-phase compressors.

Ethylene production via naphtha steam cracking is one of the most energy-and carbon-intensive processes in the petrochemical industry. As global efforts toward carbon neutrality accelerate, electrification has emerged as a promising pathway for reducing reliance on fossil fuel combustion. This study evaluates the sustainability of electrified naphtha cracking, considering both electrified steam cracking and plasma arc cracking, using six electricity sources and multiple methane utilization pathways. Industrial-scale process models, supported by pilot-scale data for plasma cracking, were developed to obtain detailed material and energy balances. Comprehensive techno-economic analysis (TEA), life cycle assessment (LCA), and carbon avoidance cost (CAC) evaluation were performed. The results show that plasma cracking achieves higher ethylene selectivity but requires a substantially higher energy input than electrified steam cracking. Economically, electrified steam cracking with methane-to-blue-hydrogen conversion powered by wind achieved the lowest levelized cost of ethylene (LCOE) ($1.66/kg ethylene) and a negative CAC (-$89.30/tonne CO2-eq), indicating simultaneous cost savings and emission reduction. Environmentally, the lowest emissions occurred in a case study with plasma cracking with methane-to-blue-hydrogen conversion powered by hydropower, achieving an 80.32% reduction relative to that of conventional naphtha steam cracking. Monte Carlo simulation confirmed the robustness of this finding, with the most cost-effective configuration showing an 86.5% probability of CAC below the current carbon price. Overall, this study identified renewable-powered electrified steam cracking combined with carbon-capture-enabled methane utilization as the most cost-effective near-term pathway for carbon-neutral ethylene production, while highlighting the efficiency improvements needed for future plasma cracking technologies.

Two HTGR-integrated hydrogen-production pathways based on steam methane reforming-helium-heated SMR (h-SMR) and electrified SMR (e-SMR)-are proposed. The former directly supplies HTGR heat to the reformer through helium, whereas the latter converts HTGR heat into electricity. Aspen Plus evaluates these systems against conventional and electrolysis-based benchmarks. Elimination of the fired furnace reduces natural gas consumption by 18.8% for h-SMR and 23.3% for e-SMR relative to gray hydrogen. Levelized cost of hydrogen is estimated at $2.37/kg for h-SMR and $2.99/kg for e-SMR, indicating cost competitiveness relative to the benchmarked pink and green hydrogen pathways under the assumed conditions. Furthermore, life-cycle assessments reveal net global warming potentials of 3.5 and 3.18 kgCO(2)/kgH(2 )for h-SMR and e-SMR, a reduction of >70% relative to gray hydrogen. Sensitivity analysis confirms the economic robustness of the h-SMR pathway across market scenarios. HTGR-integrated SMR processes offer a practical and cost-effective transition pathway for large-scale hydrogen production.

Data-driven surrogate models are increasingly recognized as effective tools for overcoming the limitations of conventional input-intensive dynamic modeling and for reducing computational costs associated with real-time decision-making and design improvements. In complex chemical systems, it is essential to select models that offer robustness and flexibility for accurate prediction and dynamic analysis. In this study, nonlinear autoregressive models with exogenous input (NARX)-based Gaussian process (GP) and neural network (NN) models were developed and evaluated using transient data from high-fidelity simulations. Cryogenic natural gas (NG) and hydrogen (H2) liquefaction processes served as case studies. Comparative analysis showed that GP-NARX models required longer training times and achieved lower accuracy (16.48 %) than NN-NARX models (89.96 %). NN-NARX models provided acceptable accuracy and were effective for operability studies such as plant turndown and capacity expansions in NG liquefaction, with accurate predictions within trained data ranges. In H2lique-faction, closed-loop NN-NARX achieved moderate success for correlated profiles in multi-step-ahead predictions, but performed poorly for highly nonlinear or weakly correlated variables. NN-NARX was effective for one-step-ahead predictions in open-loop mode, making it useful for real-time applications, but faced challenges in closed-loop scenarios. The proposed NARX-based surrogate modeling framework offers a structured, scalable solution for dynamic process analysis. While demonstrated on cryogenic systems, the methodology is process-agnostic and can be applied to other nonlinear unit operations, providing a practical alternative to traditional highfidelity dynamic modeling.

This study presents a dynamic simulation of a hydrogen liquefaction process using a helium Brayton cycle under partial load conditions. Hydrogen feed flow was reduced to 90%, 80%, and 70% of the design value and temperature, pressure, and energy consumption across heat exchangers and rotating equipment were evaluated. Results showed that insufficient reduction in helium flow caused subcooling, lowering the liquid hydrogen temperature from 20.5K to 19.5K. Furthermore, due to the lower efficiency of the expander compared to the compressor, the decrease in recoverable energy exceeded the reduction in compression work, resulting in a 44.1% increased specific energy consumption. These findings emphasize the need for precise control of helium flow and operating conditions during partial load operation. Additionally, improving the performance of rotating equipment such as compressors and expanders is essential for enhancing the energy efficiency of hydrogen liquefaction systems.

Carbon neutrality requires efficient, cost-effective carbon capture and utilization (CCU) pathways. Superstructure optimization enables the systematic evaluation of alternative CCU pathways and identification of the most cost-effective and environmentally sustainable configurations. However, existing superstructure optimization approaches are limited by fixed process parameters, reducing model accuracy and flexibility in evaluating novel CCU supply chains. Therefore, this study aims to develop a surrogate-integrated superstructure optimization framework to design CCU supply chains that maximize economic returns and minimize greenhouse gas (GHG) emissions. The proposed model employed a detailed two-level, block-based structure design that captures process-level nonlinearities through artificial neural network-based surrogate models, with a particular focus on methanol synthesis. Environmental and economic trade-offs were examined across 10-90% GHG reduction targets, showing that the surrogate-based approach allows more flexible and realistic optimization than traditional fixed-parameter models. The findings indicate that surrogate-based optimization sustained or improved profitability while enabling more sustainable carbon and energy pathways. This study offers valuable insights to guide the strategic deployment of CCU technologies in global net-zero transition efforts.

The conversion of carbon dioxide (CO2) into value-added products such as calcium formate (Ca(HCO2)2) through carbon capture and utilization (CCU) technologies has emerged as a promising strategy for mitigating global warming. For industrial feasibility, both economic competitiveness and effective CO2 conversion must be achieved. To address the high energy consumption and cost associated with conventional Ca(HCO2)2 production, particularly in the energy-intensive evaporation step, an integrated CO2 hydrogenation process was developed. The implementation of antisolvent crystallization, an optimized amine separation system, and an enhanced catalytic strategy contributed to improved overall process efficiency. Through precipitation experiments and process modeling, the optimal acetone-to-water ratio was determined to be 1:1, which balances product yield and energy consumption. Techno-economic analysis (TEA) confirmed that this ratio provides the lowest production cost, while life-cycle assessment (LCA) revealed a trade-off between economic performance and environmental impact, with slightly lower CO2 emissions observed at a 0.75 ratio. Use of acetone as an antisolvent led to a 63% reduction in steam consumption compared to conventional water evaporation. Moreover, the complex distillation-based amine recovery process was replaced with a simplified phase separation method, improving operational simplicity. Catalytic system improvements further increased hydrogenation performance. TEA and LCA demonstrated a 24% reduction in production cost (518 USD/tCa(HCO2)2) and a 57% decrease in global warming potential (GWP, 1.72 kgCO2-eq/kgCa(HCO2)2) relative to traditional CO-based processes. These results highlight the environmental sustainability and economic viability of the proposed approach, indicating its potential for practical implementation in CCU applications.

Decarbonizing methanol production requires deploying renewable hydrogen-based pathways, yet their techno-economic and environmental performance varies dramatically across regions. Existing assessments rely on national-average assumptions and single-technology evaluations, failing to capture spatial variability in renewable resources, water availability, and infrastructure costs that determine deployment feasibility. This study develops a geographically resolved Power-to-Methanol (PtM) framework by integrating spatial techno-economic analysis (S-TEA), spatial life cycle assessment (S-LCA), and water scarcity evaluation across 27 configurations, combining three electrolyzer technologies with three renewable energy sources across three representative regions. Regional renewable electricity cost, carbon intensity, and water availability create substantial performance variation, with minimum methanol selling price (MMSP) ranging from $0.84 to $2.18/kg methanol. The solar-powered polymer electrolyte membrane (PEM) electrolyzer systems achieved the lowest MMSP in the United States ($0.84/kg methanol) and Australia ($0.86/kg methanol), while the wind-powered solid oxide electrolyzer cell (SOEC) systems delivered the lowest global warming potential (0.48 kg CO2-eq/kg methanol) in both countries. Water scarcity potential varied substantially (0.09 to 1.85 m3 world-eq/kg methanol), with solar-based systems in Australia exhibiting the highest water stress. Pareto analysis identified four optimal configurations balancing cost-carbon trade-offs. In renewable-rich regions, PEM–solar systems can approach cost parity with fossil methanol, whereas resource-constrained regions require alternative strategies such as SOEC–hybrid systems, carbon pricing, or hydrogen imports. The proposed framework provides decision-makers with quantitative insights for multi-criteria site selection and supports region-specific strategies for PtM deployment.

The design of electrode parameters is a crucial determinant of the rate and quantity of lithium storage, which directly impacts the energy density and overall performance of lithium-ion batteries (LIBs) in practical applications. Therefore, the optimal design of electrode parameters is essential for enhancing the performance of LIB cells, especially under high-demand operating conditions. In this study, we develop a hybrid optimization framework that combines Bayesian Optimization (BO) with a Genetic Algorithm (GA) to systematically identify optimal design conditions for LIB cathodes. Unlike conventional approaches, we validate our investigation under practical and experimentally aligned conditions to ensure the reliability and applicability of the results. In the study, a pseudo two-dimensional (P2D) model is employed to examine the impact of physical design parameters on the electrochemical performance at varying C-rates. The Bayesian approach is integrated with the P2D model into the Gaussian process to construct a surrogate model, with the aim of optimizing the electrode design parameters to maximize the discharge capacity. Overall, this paper provides valuable insights into the design and optimization of electrode parameters for improving the performance of LIBs, particularly for NCM622 cathodes operating at high C-rates. This approach not only bridges the gap between simulation and practical application but also demonstrates a scalable methodology for future battery design optimization. Moreover, we reveal that BO is an effective technique for designing battery components.

To reduce energy and economic consumption in hydrogen (H2) liquefaction cycles, this study develops an integrated system using liquefied natural gas (LNG) regasification for pre-cooling. The system incorporates a sixstep Joule-Brayton (J-B) cycle, a solid oxide fuel cell (SOFC), and a carbon dioxide (CO2) power generation cycle, with partial power supplied by wind turbines located in South Korea. The system achieves specific power consumption (SPC) of 6.595 kWh/kgLH2, energy efficiency of 65.61 %, and a production rate of 50 tons per day (TPD) of liquid hydrogen (LH2). The energy efficiencies of the SOFC, CO2 power cycle, and organic Rankine cycle (ORC) are 60.71 %, 47.63 %, and 9.974 %, respectively. Exergy analysis reveals that the highest exergy destruction occurs in SOFC (36.81 %) and heat exchangers (37.98 %). The exergy irreversibility and exergy efficiency (EXE) of the developed system are 38.91 MW and 66.27 %, respectively. Economic analysis, using the annualized cost method (ACS), shows a return period of 5.47 years, an annual net benefit of 26.45 MMUS$/year, and a primary cost of 4.957 US$/kgLH2. Sensitivity analysis indicates that reducing LNG prices from 15 to 5 US $/MMBTU lowers the return period by 4.299 years and the primary cost by 4.518 US$/kgLH2. Additionally, reducing H2 production costs from 4.2 to 2 US$/kgH2 decreases the return period by 3.374 years and the primary cost by 3.957 US$/kgLH2, while increasing the annual net benefit by 42.88 MMUS$/year.

Despite its crucial role in renewable energy networks, hydrogen transportation incurs elevated costs and high carbon intensity (CI). To enable affordable low-carbon hydrogen, this study examined integrating a closed CO2 and heat cycle via a dual solid carriers looping strategy to mitigate direct and indirect carbon emissions. A techno-environmental-economic analysis of the hydrogen transportation infrastructure was conducted on a large-scale overseas supply chain. This analysis involved base cases (i.e., LH2, LNH3, MeOH, formic acid, and dimethyl ether) and various combinations of hydrogen and CO2/heat dual carriers (i.e., CaO, ZnO, Li2O, and MgO). The results showed a considerable decrease in cost and carbon emissions through the integration of the CO2/heat closed cycle system. Particularly, the MeOH-ZnO route showed substantial improvement, achieving a CI reduction to 15.54 kgCO2-eq/kgH2 (i.e., 46 % lower than that of the MeOH route), with a cost of 6.0 USD/ kgH2. In the projected 2050 scenario, employing the CO2/heat looping system further reduced CI to as low as 0.7 kgCO2-eq/kgH2 and a cost of up to 4.6 USD/kgH2, despite the use of costly renewable heat and direct air carbon capture. Integrating the CO2/heat looping system thus facilitates affordable, greener hydrogen transport, crucial for a sustainable energy economy.

Techno-economic analysis and life cycle assessment of thermophilic dark fermentation (TDF) and mesophilic dark fermentation (MDF) integrated with anaerobic digestion (AD) from coffee-manufacturing wastewater (CW) as feedstock were studied. The pilot plants were based in Iran and designed to convert 800 m3/day of CW into hydrogen. The hydrogen volume flow rate (m3/h) under thermophilic conditions was 1.1 times higher than that under mesophilic conditions; however, the hydrogen mass flow rate (kg/h) was approximately equal in both conditions (1.04). The hydrogen production costs for the MDF-AD and TDF-AD plants were 3.86 and 3.84 USD/kg, respectively. A payback period of 1.3 and 1.33 years for the MDF-AD and TDF-AD plants were obtained, respectively. The Global warming potential from the entire system was 0.79 kg CO2-eq/kg hydrogen for the DF-AD plants. The DF commercialization is supported by environmental advantages, despite its higher hydrogen cost than natural gas-based methods.

Carbon capture and utilization is an emerging technology used to mitigate CO2 emissions. Incorporating captured CO2 as a raw material in the chemical industry provides a sustainable CO2 reduction approach rather than mere disposal. Existing literature showcases successful experiments demonstrating CO2's feasibility as a raw material. However, not all carbon capture and utilization products have the capacity to efficiently utilize substantial amounts of CO2 or be economically viable. Therefore, this study concentrates on investigating carbon capture and utilization processes, warranting further exploration and comparison with conventional process based on techno-economic feasibility, sustainability, and market potential by proposing novel methodology. Sustainable feasibility index was developed to rank promising carbon capture and utilization processes based on techno-economic, environmental, and market size considerations. Eleven high-potential products were investigated. Acetic acid, formic acid, and calcium formate were identified as the top-ranking products for the base cases. Results from carbon to hydrogen mass ratio indicated decreasing the global warming index of CO2 have a larger effect compared to decreasing the global warming index of H2 on overall carbon footprint of the products. Future projections with respect to raw material sources show the changes in CO2 sources when compared to changes in the hydrogen and electricity sources, have the most significant effects on the levelized cost of the product and global warming index. Additionally, this work seeks to ease the decision-making for stakeholders regarding the selection of feasible and sustainable carbon capture and utilization processes with a detailed comparative investigation.

Process electrification is a viable solution for reducing reliance on non-renewable fuels, with green ammonia considered as a promising hydrogen carrier with a gravimetric storage capacity of 17.6 wt%. The incorporation of these two direct COX-free energy systems inevitably facilitates enhanced environmental performance; however, extensive improvements are required to achieve cost-effectiveness. Therefore, this study proposed and optimized the concept of electrified ammonia decomposition (AD) and evaluated it in terms of the technological, environmental, and economic feasibilities. To mitigate indirect CO2 emissions, a novel electrification process was proposed wherein a multi-concentric porous heater (MCPHs-AD) configuration was developed and compared to the natural gas heated (NGH-AD) process and the conventional electrically heated wall-adjacent heated reaction (WAH-AD.) A multi-step analysis approach was implemented, involving various scenarios of electricity sources (gray, blue, and green energy), to thoroughly assess the economic and environmental feasibility of the heat supply routes for the hydrogen refueling station. The non-feasibility of electrification was highlighted when using gray electricity owing to increased cost and CO2 emissions of 12.8 USD/kg-H2 and 10.5 kg-CO2/kg-H2, respectively. The application of CCS-integrated electricity reduced the carbon intensity by 14.3 % and 11.6 % for WAHAD and MCPHs-AD, respectively, compared to NGH-AD with up to 14.7 % increase in cost. For the 2050 scenario, green electricity implementation reduced the carbon emissions and cost to 10.7 USD/kg-H2 and 3.5 kg-CO2/kgH2 when using MCPHs-AD with up to 8.2 % decrease in carbon intensity compared to WAH-AD. This achievement is attributable to the high energy efficiency because of the high surface area of the MCPHs-AD.

Steam methane reforming (SMR) is the most widely employed method for industrial hydrogen production owing to its cost-effectiveness. Existing studies have primarily focused on operational conditions, with relatively less attention given to the structural configuration of the reformer. In this study, a computational framework integrating computational fluid dynamics (CFD) modeling with Bayesian optimization (BO) is proposed to simultaneously optimize the design and operational variables of an SMR reactor. A CFD model was developed by coupling and iteratively solving the furnace and tube domains to accurately simulate the heat transfer characteristics. A sensitivity analysis was conducted to identify the key design variables, followed by BO, to efficiently investigate the design space. Consequently, methane (CH4) conversion improved 3.0

Hydrogen production via steam reforming (SR) is technically and economically feasible. To achieve higher feedstock conversion and H2 yield, this study reviews the key parameters affecting SR, including feedstock type, temperature, steam-to-carbon molar ratio, pressure, space velocity, catalyst type, and reactor type. Accordingly, optimal parameter values must be selected considering thermodynamic, kinetic, and economic conditions. In addition, the challenges and prospects of the SR process are explored. Significant limitations of the SR process include overdependence on fossil fuels, CO2 emissions, high energy requirements, catalyst deactivation, heat management, and infrastructure development. However, adopting renewable and sustainable feedstocks such as biogas, renewable energy sources like wind, solar, hydropower, tidal, and geothermal, smaller-scale SR, and carbon capture utilization, and storage technology can ensure that SR remains a viable H2 production method alongside the increasing adoption of greener alternatives.

Among natural gas-based hydrogen production methods, autothermal reforming (ATR) has a high efficiency for carbon capture and storage integration due to the high CO2 levels at the reactor outlet. This study proposes an integrated system (ATR/HLU-LOX) that utilizes liquefied oxygen (LOX) in the precooling stage of the hydrogen liquefaction unit (HLU) to reduce liquefaction energy costs and CO2 intensity. This conducted an enviro-technoeconomic analysis for large-scale hydrogen production (100 tonnes/day) suitable for natural gas valorization and hydrogen storage. Additionally, this study evaluated the performance of a CCS-based ATR system (ATR-CCS/ HLU-LOX) and compared it to LOX-free liquefaction unit (ATR/HLU and ATR-CCS/HLU). For further comparison, grey and blue steam methane reforming (SMR) for hydrogen generation was also investigated (i.e., SMR/ HLU and SMR-CCS/HLU systems). The main findings of this study depicted that ATR-CCS/HLU-LOX reduced specific energy consumption by 6.6% and lowered the levelized cost of hydrogen and global warming impact by 1.3 and 11.0%, respectively, compared to SMR-CCS/HLU. This achievement can encourage adopting ATR for various applications (e.g., flare gas treatment, blue hydrogen generation, and subsurface NG valorization) instead of high CO2 emitting SMR.