United States

Electrifying ammonia production using renewable energy (RE) and water electrolysis is a critical step in the worldwide transition from fossil fuels to alternative energy sources. However the common requirement that the ammonia reactor operate at a steady production level harms the system’s economic feasibility due to the large hydrogen and battery storage required to overcome RE variability. In this study we examine the sensitivity of the plant storage capacity requirement to the flexibility of the ammonia reactor. We examine two aspects of ammonia reactor flexibility: ramping rate flexibility and the range of operation (turndown flexibility). We develop a storage dispatch and ammonia reactor scheduling optimization which computes the minimum storage requirement given a RE generation profile and set of reactor flexibility parameters. We optimize across a sweep of flexibility parameters for two locations in the United States. We find that turndown flexibility is the most important while ramping flexibility has little effect on the overall storage requirement. Further we see that seasonal variability in the RE generation profile is the primary driver of high storage capacity requirement. We find that with a turndown flexibility of 60% of the ammonia plants rated capacity which is understood to be achievable with existing ammonia reactor technology the storage capacity was reduced by 84 % in one of the locations we examined which resulted in a 22% decrease in the levelized cost of ammonia with pipe-based hydrogen storage.

Efforts to create a sustainable hydrogen economy are gaining momentum as governments all over the world are investing in hydrogen production storage distribution and delivery technologies to develop a hydrogen infrastructure. This involves transporting hydrogen in gaseous or liquid form or using carrier gases such as methane ammonia or mixtures of methane and hydrogen. Hydrogen is a colorless odorless gas and can easily leak into the atmosphere leading to economic loss and safety concerns. Therefore deployment of robust low-cost sensors for various scenarios involving hydrogen is of paramount importance. Here we review some recent developments in hydrogen sensors for applications such as leak detection safety process monitoring in production transport and use scenarios. The status of methane and ammonia sensors is covered due to their important role in hydrogen production and transportation using existing natural gas and ammonia infrastructure. This review further provides an overview of existing commercial hydrogen sensors and also addresses the potential for hydrogen as an interferent gas for currently used sensors. This review can help developers and users make informed decisions about how to drive hydrogen sensor technology forward and to incorporate hydrogen sensors into the various hydrogen deployment projects in the coming decade.

Quantitative Risk Assessments (QRA) is an important tool for enabling safe deployment of hydrogen technologies and is increasingly embedded in the permitting process. Following the framework developed in our companion paper we conducted a detailed QRA on the uncontrolled releases from a high-capacity hydrogen fueling station with liquid hydrogen (LH2) storage. We characterized gaseous and liquid hydrogen releases determined the causal pathways that led to them and the frequency of the potential hazardous outcomes. These hazardous scenarios were modeled to estimate their potential harm on station users. The analysis results reveal that the total frequency for a major hydrogen release is 1.48 × 10− 2 times per station-year. However considering the control barriers in the station the expected frequency of ignition events is reduced to 1.35 × 10− 5 ignition per stationyear. The expected fatality risk is within the tolerable limit for hydrogen fueling stations but still remains higher than that of conventional gasoline stations. The most severe scenario identified involves a high-pressure GH2 release leading to a jet fire with jet flames reaching up to 15 m in length. The most probable sources of GH2 releases are from the gaseous hydrogen filters while for LH2 releases cryogenic pumps are the primary contributors. To improve the accuracy of QRAs for LH2 systems we identified critical gaps including the need for improved reliability data that must be addressed.

Until recently electrified aircraft propulsion (EAP) technology development has been driven by the dual objectives of reducing greenhouse gas (GHG) emissions and addressing the depletion of fossil fuels. However the increasing severity of climate change posing a significant threat to all life forms has resulted in the global consensus of achieving net-zero GHG emissions by 2050. This major shift has alerted the aviation electrification industry to consider the following: What is the clear path forward for EAP technology development to support the net-zero GHG goals for large commercial transport aviation? The purpose of this paper is to answer this question. After identifying four types of GHG emissions that should be used as metrics to measure the effectiveness of each technology for GHG reduction the paper presents three significant categories of GHG reduction efforts regarding the engine evaluates the potential of EAP technologies within each category as well as combinations of technologies among the different categories using the identified metrics and thus determines the path forward to support the net-zero GHG objective. Specifically the paper underscores the need for the aviation electrification industry to adapt adjust and integrate its EAP technology development into the emerging new engine classes. These innovations and collaborations are crucial to accelerate net-zero GHG efforts effectively.

A unique hydrogen leak detection strategy is the use of powerless indicator wraps for fittings and other pneumatic elements within a hydrogen facility. One transduction mechanism of such indicators is a color change that is induced by a reaction between a pigment and released hydrogen. This is an effective way to detect hydrogen leaks and to identify their source before they become a safety event however this technology requires visual (manual) inspection to identify a color change or leak. One improvement in this strategy would be to improve the communication of the visual response to an end-user. Element One (E1) has previously developed and introduced DetecTape® a self-fusing silicone non-reversible hydrogen leak detecting tape for application to potential leak sites in hydrogen piping valves and fittings and it has been successfully commercialized with excellent feedback. Element One’s sensors can be fabricated using either pigments or thin films which both change color and conductivity. Neither change requires an external power source. The conductivity change may be communicated as a wireless transmission such as passive radio frequency identification devices (RFID) to an appropriate receiving system where it may be remotely monitored to achieve higher levels of safety and reliability at low cost. Element One will report on its recent progress in the commercial development of remotely monitored hydrogen leak detection using several wireless protocols including passive RFID.

Hydrogen is one of a handful of new low carbon solutions that will be critical for the transition to net zero. The upscaling of production and applications entails that hydrogen is likely to be stored in liquid phase (LH2) at cryogenic conditions to increase its energy density. Widespread LH2 use as an alternative fuel will require significant infrastructure upgrades to accommodate increased bulk transport storage and delivery. However current LH2 bulk storage separation distances are based on subjective expert recommendations rather than experimental observations or physical models. Experimental studies of large-scale LH2 release are challenging and costly. The existing large-scale tests are scarce and numerical studies are a viable option to investigate the existing knowledge gaps. Controlled or accidental releases of LH2 for hydrogen refueling infrastructure would result in high momentum two-phase jets or formation of liquid pools depending on release conditions. Both release scenarios lead to a flammable/explosive cloud posing a safety issue to the public.<br/>The manuscript reports exploratory study to numerically determine the safety zone resulting from cryogenic hydrogen releases related to LH2 storage and refueling using the in-house HyFOAM solver further modified for gaseous hydrogen releases at cryogenic conditions and the subsequent atmospheric dispersion and ignition within the platform of OpenFOAM V8.0. The current version of the solver neglects the flashing process by assuming that the temperature of the stored LH2 is equal to the boiling point at the atmospheric condition. Numerical simulations of dispersion and subsequent ignition of LH2 release scenarios with respect to different release orientations release rates release temperatures and weather conditions were performed. Both hydrogen concentration and temperature fields were predicted and the boundary of zones within the flammability limit was also defined. The study also considered the sensitivities of the consequences to the release orientation wind speed ambient temperature and release content etc. The effect of different barrier walls on the deflagration were also evaluated by changing the height and location.

Presented is an evaluation of the carbon footprint and costs associated with hydrogen production via the aluminum-water reaction (AWR) identifying an optimized scenario that achieves 1.45 kgCO2 equiv per kg of hydrogen produced. U.S.-based data are used to compare results with conventional production methods and to assess hydrogen use in fuel-cell passenger vehicles. In the optimized scenario major contributors include the use of recycled aluminum (0.38 kgCO2 equiv) aluminum processing (0.45 kgCO2 equiv) and alloy activator recovery (0.57 kgCO2 equiv). A cost analysis estimates hydrogen production at $9.2/kg when using scrap aluminum alloy recovery and recycling thermal energy aligning with current green hydrogen prices. Reselling reaction byproducts such as boehmite could generate revenue 5.6 times greater than input costs enhancing economic feasibility. The cradle-to-grave assessment suggests that aluminum fuel as an energy carrier for hydrogen distribution and fuel cell vehicle applications offers a low-emission and economically viable pathway for clean energy deployment.

Hydrogen is a zero-carbon energy carrier with potential to decarbonize industrial and transportation sectors but its life-cycle greenhouse gas (GHG) emissions depend on its energy supply chain and carbon management measures (e.g. carbon capture and storage). Global support for clean hydrogen production and use has recently intensified. In the United States Congress passed several laws that incentivize the production and use of renewable and low-carbon hydrogen such as the Bipartisan Infrastructure Law (BIL) in 2021 and the Inflation Reduction Act (IRA) in 2022 which provides tax credits of up to $3/kg depending on the carbon intensity of the produced hydrogen. A comprehensive life-cycle accounting of GHG emissions associated with hydrogen production is needed to determine the carbon intensity of hydrogen throughout its value chain. In the United States Argonne’s R&D GREET® (Greenhouse Gases Regulated emissions and Energy use in Technologies) model has been widely used for hydrogen carbon intensity calculations. This paper describes the major hydrogen technology pathways considered in the United States and provides data sources and carbon intensity results for each of the hydrogen production and delivery pathways using consistent system boundaries and most recent technology performance and supply chain data.

Introduction: Several cities in Malaysia have established plans to reduce their CO2 emissions in addition to Malaysia submitting a Nationally Determined Contribution to reduce its carbon intensity (against GDP) by 45% in 2030 compared to 2005. Meeting these emissions reduction goals will require ajoint effort between governments industries and corporations at different scales and across sectors.<br/>Methods: In collaboration with national and sub-national stakeholders we developed and used a global integrated assessment model to explore emissions mitigation pathways in Malaysia and Kuala Lumpur. Guided by current climate action plans we created a suite of scenarios to reflect uncertainties in policy ambition level of adoption and implementation for reaching carbon neutrality. Through iterative engagement with all parties we refined the scenarios and focus of the analysis to best meet the stakeholders’ needs.<br/>Results: We found that Malaysia can reduce its carbon intensity and reach carbon neutrality by 2050 and that action in Kuala Lumpur can play a significant role. Decarbonization of the power sector paired with extensive electrification energy efficiency improvements in buildings transportation and industry and the use of advanced technologies such as hydrogen and carbon capture and storage will be Major drivers to mitigate emissions with carbon dioxide removal strategies being key to eliminate residual emissions.<br/>Discussion: Our results suggest a hopeful future for Malaysia’s ability to meet its climate goals recognizing that there may be technological social and financial challenges along the way. This study highlights the participatory process in which stakeholders contributed to the development of the model and guided the analysis as well as insights into Malaysia’s decarbonization potential and the role of multilevel governance.

Hydrogen is increasingly recognized as a key contributor to a low-carbon energy future and machine learning (ML) is emerging as a valuable tool to optimize hydrogen production processes. This review presents a comprehensive analysis of ML applications across various hydrogen production pathways including gray blue and green hydrogen with additional insights into pink turquoise white and black/brown hydrogen. A total of 51 peer-reviewed studies published between 2012 and 2025 were systematically reviewed. Among these green hydrogen—particularly via water electrolysis and biomass gasification—received the most attention reflecting its central role in decarbonization strategies. ML algorithms such as artificial neural networks (ANNs) random forest (RF) and gradient boosting regression (GBR) have been widely applied to predict hydrogen yield optimize operational conditions reduce emissions and improve process efficiency. Despite promising results real-world deployment remains limited due to data sparsity model integration challenges and economic barriers. Nonetheless this review identifies significant opportunities for ML to accelerate innovation across the hydrogen value chain. By highlighting trends key methodologies and current gaps this study offers strategic guidance for future research and development in intelligent hydrogen systems aimed at achieving sustainable and cost-effective energy solutions.