Germany

The chemical industry faces major challenges worldwide. Since 1950 production has increased 50-fold and is projected to continue growing particularly in Asia. It is one of the most energy- and resource-intensive industries contributing significantly to greenhouse gas emissions and the depletion of finite resources. This development exceeds planetary boundaries and calls for a sustainable transformation of the industry. The key transformation areas are as follows: (1) Non-Fossil Energy Supply: The industry must transition away from fossil fuels. Renewable electricity can replace natural gas while green hydrogen can be used for high-temperature processes. (2) Circularity: Chemical production remains largely linear with most products ending up as waste. Sustainable product design and improved recycling processes are crucial. (3) Non-Fossil Feedstock: To achieve greenhouse gas neutrality oil gas and coal must be replaced by recycling plastics renewable biomaterials or CO2-based processes. (4) Sustainable Chemical Production: Energy and resource savings can be achieved through advancements like catalysis biotechnology microreactors and new separation techniques. (5) Sustainable Chemical Products: Chemicals should be designed to be “Safe and Sustainable by Design” (SSbD) meaning they should not have hazardous properties unless essential to their function. (6) Sufficiency: Beyond efficiency and circularity reducing overall material flows is essential to stay within planetary boundaries. This shift requires political economic and societal efforts. Achieving greenhouse gas neutrality in Europe by 2050 demands swift and decisive action from industry governments and society. The speed of transformation is currently too slow to reach this goal. Science can drive innovation but international agreements are necessary to establish a binding framework for action.

To enable climate-neutral aviation improving the energy efficiency of aircraft is essential. The research project Synergies of Highly Integrated Transport Aircraft investigates cross-disciplinary synergies in aircraft and propulsion technologies to achieve energy savings. This study examines a fuel cell electric powered configuration with distributed electric propulsion. For this a reverse-engineered ATR 72-500 serves as a reference model for calibrating the methods and ensuring accurate performance modeling. A baseline configuration featuring a state-of-the-art turboprop engine with the same entry-into-service is also introduced for a meaningful performance comparison. The analysis uses an enhanced version of the Stanford University Aerospace Vehicle Environment (SUAVE) a Python-based aircraft design environment that allows for novel energy network architectures. This paper details the preliminary aircraft design process including calibration presents the resulting aircraft configurations and examines the integration of a fuel cell-electric energy network. The results provide a foundation for higher fidelity studies and performance comparisons offering insights into the trade-offs associated with hydrogen-based propulsion systems. All fundamental equations and methodologies are explicitly presented ensuring transparency clarity and reproducibility. This comprehensive disclosure allows the broader scientific community to utilize and refine these findings facilitating further progress in hydrogen-powered aviation technologies.

The safe removal transportation and long-term storage of fuel debris in the decommissioning of Fukushima Daiichi is the biggest challenge facing Japan. In the nuclear power field passive autocatalytic recombiners (PARs) have become established as a technology to prevent hydrogen explosions inside the containment vessel. To utilize PAR as a measure to reduce the concentration of hydrogen generated in the fuel debris storage canister which is currently an issue it is required to perform in a sealed environment with high doses of radiation low temperature and high humidity and there are many challenges different from conventional PAR. A honeycombshaped catalyst based on automotive catalyst technology has been newly designed as a PAR and research has been conducted to solve unique problems such as high dose radiation low temperature high humidity coexistence of hydrogen and low oxygen and catalyst poisons. This paper summarizes the challenges of hydrogen generation in a sealed container the results of research and a guide to how to use the PAR for fuel debris storage canisters.

Emerging energy technologies offer significant opportunities for climate change mitigation. However the assessment of their potential environmental impact through prospective life cycle assessment (pLCA) is challeng‑ ing owing to parameter uncertainties arising from data gaps temporal variability and evolving technological contexts when modeling their prospective life cycle inventories (pLCI). Existing methodologies lack standardized approaches for systematically integrating parameter uncertainty within pLCI frameworks often initially overlooking it. In order to fill this gap this study proposes a structured and transparent approach for incorporating parameter uncertainty directly into the pLCI modeling process. The goal is to enhance the robustness transparency and reproducibility of pLCI models. A decision–support flowchart based on an adapted six-step framework was developed to help life cycle assessment (LCA) practitioners address parameter uncertainty during the “goal and scope definition” and“life cycle inventory” phases of pLCA. The flowchart guides users through the process of defining of the assessment’s goal scope as well as its temporal and geographical boundaries and the technology’s maturity level (Step 1). Step 2 entails gathering data to depict the technology’s development. Steps 3 and 4 involve identifying parameters that are likely to change in the future such as manufacturing processes materials equipment and component dimensions as well as their respective uncertainties. Step 5 includes the learning effects required for industrial-scale production once the technology has reached maturity. Finally step 6 identifies external developments impacting the technology as well as contributing uncertainties. A case study of a fuel cell-based propulsion system for a hydrogen-powered aircraft in 2040 illustrates the applicability of the framework. This study introduces a structured flowchart to support decision making in cases when parameter uncertainty should be integrated into pLCI modeling. By supporting the selection of appropriate prospective meth‑ ods as well as uncertainty identification and characterization strategies the proposed flowchart enhances the trans‑ parency consistency and representativeness of the pLCA results facilitating their broader application in emerging technology assessment methods.

Green hydrogen is essential for advancing the energy transition as it is regarded as a CO2-neutral flexible and storable energy carrier. Particularly in steel production which is known for its high energy intensity hydrogen has great potential to replace conventional energy sources. In a game-theoretic bi-level optimization model involving a power plant operator and a steel company we investigate in which situations the production and use of green hydrogen is advantageous from an economic and ecological point of view. Through an extensive case study based on a realworld scenario we can observe that hydrogen production can serve as a profitable and flexible secondary income opportunity for the power plant operator and help avoid curtailment and spot market losses. On the other hand the steel manufacturer can reduce CO2 emissions and associated costs while also meeting the growing customer demand for low-carbon products. However our findings also highlight important trade-offs and uncertainties. While lower electricity generation costs or improved electrolyzer efficiency enhance hydrogen’s competitiveness increases in coal and CO2 emission prices do not always result in greater hydrogen adoption. This is due to the persistent reliance on a non-replaceable share of coal in steel production which raises the overall cost of both low-carbon and carbon-intensive steel. The model further shows that consumer demand elasticity plays a critical role in determining hydrogen uptake. These insights underscore the importance of not only reducing hydrogen costs but also designing supportive policies that address market acceptance and the full cost structure of green industrial products.

This study examines the technical feasibility of using seawater as a feedstock for green hydrogen production with a focus on system design and water treatment aspects. Both direct and indirect seawater splitting approaches are considered. Direct seawater electrolysis is excluded from further consideration due to unresolved challenges such as parasitic side reactions and electrode degradation. For make-up water generation thermal desalination and seawater reverse osmosis (SWRO) were evaluated. Thermal desalination though potentially powered by waste heat from electrolysis was deemed impractical due to its dependence on the electrolyzer plant’s heat management system which complicates overall plant control. In contrast SWRO operates as a standalone system and imposes minimal impact on hydrogen production costs through competing power consumption making it the preferred option for large-scale applications. Alkaline Water Electrolysis (AWE) and Proton Exchange Membrane (PEM) electrolysis are identified as the only currently available industrial-scale electrolyzer technologies. A Balance of Plant analysis revealed key water treatment interfaces including make-up water systems required for both technologies and a loop purification system specific to PEM systems. A design study translated the identified requirements into practical plant configurations providing a detailed evaluation of treatment options and implementation strategies. The study concluded with an outlook on future water-focused research laying the groundwork for continued advancements in support of large-scale green hydrogen production.

Hydrogen handling equipment suffers from interaction with their operating environment which degrades the mechanical properties and compromises component integrity. Hydrogen-assisted cracking is responsible for several industrial failures with potentially severe consequences. A thorough failure analysis can determine the failure mechanism locate its origin and identify possible root causes to avoid similar events in the future. Postmortem fractographic analysis can classify the fracture mode and determine whether the hydrogen-metal interaction contributed to the component’s breakdown. Experts in fracture classification identify characteristic marks and textural features by visual inspection to determine the failure mechanism. Although widely adopted this process is time-consuming and influenced by subjective judgment and individual expertise. This study aims to automate fractographic analysis through advanced computer vision techniques. Different materials were tested in hydrogen atmospheres and inert environments and their fracture surfaces were analyzed by scanning electron microscopy to create an extensive image dataset. A pre-trained Convolutional Neural Network was finetuned to accurately classify brittle and ductile fractures. In addition Grad-CAM interpretability method was adopted to identify the image regions most influential in the model’s prediction and compare the saliency maps with expert annotations. This approach offered a reliable data-driven alternative to conventional fractographic analysis.

Solid oxide fuel cell (SOFC) systems offer high-efficiency conversion of the chemical energy of fuel gases into electrical energy. To meet market and policy targets such systems must be able of operating on an industrial scale and be compatible with environmentally friendly fuels. This study models the scale-up of a 750 W naturalgas-fueled SOFC to a 240 kW system with various gas-path configurations evaluating the impact of blending up to 30 vol% of hydrogen (H2) into the methane feed. Aspen Plus simulations coupled with pressure-loss and carbon-deposition models were used to optimize recirculation ratio and reactant utilization for maximum efficiency. The parallel configuration achieved the highest electrical efficiency of 64.0 % while series-connected and intermediate systems suffered from increased pressure losses. H2 admixture simulations confirm that operation is feasible without loss of efficiency in the small- and large-scale systems due to reduced carbondeposition potential. A techno-economic analysis indicates a 91.7 % cost reduction through scale-up and a 1.6 % cost increase for adjusting the system to H2 admixtures. The economic viability of the large-scale system was evaluated for all tested fuel compositions (0.201–0.204 €/kWh) with payback times under 20 years at market-relevant electricity prices. These results demonstrate the technical and economic feasibility of large-scale H2-adapted SOFC systems for industrial decarbonization.

Single Atom Catalysts (SACs) are an emerging frontier in heterogeneous electrocatalysis. They are made of metal atoms atomically dispersed on a matrix. A lot of attention has been dedicated to the study of Hydrogen Evolution Reaction (HER) mechanism due to its relevance in energy conversion technologies both with computational and experimental methods. The classical HER mechanism can be described by a Volmer–Heyrovsky–Tafel mechanism where the two desorption steps are competitive. The Volmer-Heyrovsky mechanism is conventionally proposed for single-atom catalysts. It has been computationally demonstrated that hydrogen complexes can form on SACs due to their analogy with homogeneous catalysts. Unfortunately it is hard to “visualize” these species experimentally. Electrochemical Impedance Spectroscopy (EIS) could be the most promising approach to study electrocatalytic mechanisms. In this work we present microkinetic and Electrochemical Impedance Spectroscopy models for HER on SACs describing Volmer-Heyrovsky and a mechanism mediated by the formation of hydrogen complexes. Our simulated data applied to a case study based on Pd@TiN show that Tafel plots will not suffice in the visualization of hydrogen complexes formation and will need the support of electrochemical impedance spectra in order to clarify the correct mechanism.

A well-developed hydrogen infrastructure is a key element for the global energy transition. The strategic implementation of this infrastructure is challenging due to the wide range of different criteria which need to be considered and analyzed. This paper presents a novel multi-criteria analysis framework for the optimal localization of power-to-gas (PtG) plants. The framework considers criteria such as renewable energy availability hydrogen demand proximity to existing gas infrastructure and groundwater availability. A techno-economic model is integrated into the framework to evaluate the levelized cost of hydrogen (LCOH) for different electrolyzer technologies. Applying the developed framework to Germany the potential of northern and northwestern Germany as suitable locations becomes apparent. In addition LCOH for PtG plants at selected locations in Germany are evaluated depending on the year of commissioning. The large differences between present LCOH ranging from 16.8 €/kg to 9.1 €/kg illustrate the importance of an integrated techno-economic model.