Attributed metadata history
Up to 100 retained publisher events per page for c21371a330ce5b5494dd7d63cc676db18c8071a80c2913cc135ba78a447ee7cb. Withdrawals and unavailable references remain attributed to their publishers.
intelligence_src_5dceb224d3618ef333
observed · 2026-10-12 10:19:03 UTC
available
Fingerprint: ee4471e48e9d6ad5cd7b3b51f38e0f360d1a48bf5bc53484698cc7c758d86df0
intelligence_src_5dceb224d3618ef333
observed · 2026-10-12 10:19:03 UTC
Electric vehicles are pushing scientists to tackle one of the biggest hidden energy drains inside electric motors: magnetic energy loss. Now, researchers in Japan have developed a powerful AI-driven physics model that can peer into the chaotic “maze-like” magnetic patterns inside motor materials and reveal how heat and microscopic magnetic structures trigger wasted energy.
Fingerprint: 88f2d395df171858867fdbdce8577724c86e0b6d81f2cc149f3007ef79d7f7ea
intelligence_src_5664c27502ed6f6dcc
observed · 2026-10-12 10:03:03 UTC
Electric vehicles are pushing scientists to tackle one of the biggest hidden energy drains inside electric motors: magnetic energy loss. Now, researchers in Japan have developed a powerful AI-driven physics model that can peer into the chaotic “maze-like” magnetic patterns inside motor materials and reveal how heat and microscopic magnetic structures trigger wasted energy.
Fingerprint: 88f2d395df171858867fdbdce8577724c86e0b6d81f2cc149f3007ef79d7f7ea
intelligence_src_5664c27502ed6f6dcc
observed · 2026-10-12 10:03:03 UTC
available
Fingerprint: 2da632ad3d12e9a7141064e97894938f80a43739ee76a43c0e15a3401f109989