Abstract
The transition to affordable and clean energy sources is essential for creating a sustainable future. Green hydrogen, as an emerging
energy carrier, has the potential to meet increasing energy demands while mitigating environmental impact and achieving
SDG 7. The incorporation of green hydrogen into any energy system is a complex process that entails numerous challenges. These
challenges include fluctuating energy outputs from renewables, the technical demands of storing hydrogen across varying pressures
and temperatures, the intricate logistics required for its safe transportation, skills, and other considerations. Given these
complexities and the constantly evolving knowledge around green hydrogen, it becomes important to identify skills and technologies
propelling the development of the green hydrogen value chain. This study presents a systematic approach for identifying and
analysing the skills and technologies pivotal to the green hydrogen value chain. Using natural language processing techniques,
hard skills, soft skills, and emerging technologies are extracted and categorised from published literature. A token classification
model, built upon the pre-trained
BERT architecture and fine-tuned
with domain-specific
data, enables the precise identification
of contextually relevant entities. The results reveal a taxonomy of skills and technologies, highlighting critical workforce capabilities
such as material science expertise, project management, and leadership skills, alongside emerging technologies like PEM
electrolysers and nanostructured materials. These results provide actionable insights for addressing skill sustainability, fostering
workforce development, advancing decent work and economic development, and guiding technological innovation to strengthen
the green hydrogen value chain. The integration of real-time
updates ensures that the analysis remains current.