Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature | Paper Citation Record

Observation 6a83c9f0-2843-4605-bbe6-e5a7aa72acaf · outbound

This paper cites Realistic roles for hydrogen in the future energy transition.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Realistic roles for hydrogen in the future energy transition

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85e52ee2-50ad-42d7-bab9-ce58dd784bfe · outbound

This paper cites Electrification of industry: Potential, challenges and outlook.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Electrification of industry: Potential, challenges and outlook

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5d4bc0a-c218-4baa-94bf-141e437d83e7 · outbound

This paper cites Hydrogen -storage materials for mobile applications.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Hydrogen -storage materials for mobile applications

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b38e5bd-cd9f-4e36-a379-53ca385d47a9 · outbound

This paper cites Challenges to developing materials for the transport and storage of hydrogen.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Challenges to developing materials for the transport and storage of hydrogen

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb71de88-41e6-4dd9-85ac-b14de59365c4 · outbound

This paper cites Application of hydrides in hydrogen storage and compression: achievements, outlook and perspectives.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Application of hydrides in hydrogen storage and compression: achievements, outlook and perspectives

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b53817f5-4fef-488f-aeac-5eb330b35346 · outbound

This paper cites Materials for hydrogen -based energy storage – past, recent progress and future outlook.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Materials for hydrogen -based energy storage – past, recent progress and future outlook

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1298fac-dc05-4a1e-b3f1-fb5621a88089 · outbound

This paper cites Ti -doped alkali metal aluminium hydrides as potential novel reversible hydrogen storage materials.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Ti -doped alkali metal aluminium hydrides as potential novel reversible hydrogen storage materials

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27a750ba-cbfc-49a5-8a40-658c51533905 · outbound

This paper cites Nanocrystalline magnesium for hydrogen storage.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Nanocrystalline magnesium for hydrogen storage

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7c8893f-1842-46ad-8654-e5b66eb436d3 · outbound

This paper cites Mechanically milled Mg composites for hydrogen storage: the relationship between morphology and kinetics.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Mechanically milled Mg composites for hydrogen storage: the relationship between morphology and kinetics

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7458a76a-5331-4b9c-820f-804d968fdaa5 · outbound

This paper cites Activation of titanium-vanadium alloy for hydrogen storage by introduction of nanograins and edge dislocations using high- pressure torsion.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Activation of titanium-vanadium alloy for hydrogen storage by introduction of nanograins and edge dislocations using high- pressure torsion

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92ea3d19-8fa9-407d-a385-441d0911d760 · outbound

This paper cites Mechanical synthesis and hydrogen storage characterization of MgVCr and MgVTiCrFe high -entropy alloy.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Mechanical synthesis and hydrogen storage characterization of MgVCr and MgVTiCrFe high -entropy alloy

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14a44830-3279-4da1-8479-6034ddc8c27d · outbound

This paper cites Impact of severe plastic deformation on kinetics and thermodynamics of hydrogen storage in magnesium and its alloys.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Impact of severe plastic deformation on kinetics and thermodynamics of hydrogen storage in magnesium and its alloys

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5906e01e-d720-416b-aba5-37e12550968f · outbound

This paper cites Significance of interphase boundaries on activation of high -entropy alloys for room-temperature hydrogen storage.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Significance of interphase boundaries on activation of high -entropy alloys for room-temperature hydrogen storage

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d36c21e-218f-4313-880e-994eba71ba47 · outbound

This paper cites Developing ideal metalorganic hydrides for hydrogen storage: from theoretical prediction to rational fabrication.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Developing ideal metalorganic hydrides for hydrogen storage: from theoretical prediction to rational fabrication

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6493ad45-28c2-42cb-bb6e-8d7c3772efb8 · outbound

This paper cites Machine learning to explore high -entropy alloys with desired enthalpy for room-temperature hydrogen storage: Prediction of density functional theory and experimental data.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Machine learning to explore high -entropy alloys with desired enthalpy for room-temperature hydrogen storage: Prediction of density functional theory and experimental data

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d90c62f-4251-40aa-9750-557b3a60658c · outbound

This paper cites Reversible room temperature hydrogen storage in high -entropy alloy TiZrCrMnFeNi.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Reversible room temperature hydrogen storage in high -entropy alloy TiZrCrMnFeNi

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5dc85974-c016-420a-8a75-22c18c8f41bc · outbound

This paper cites Metal hydrides.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Metal hydrides

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b00fe02d-e9b3-4413-b557-f854ec502b97 · outbound

This paper cites High -entropy ceramics: review of principles, production and applications.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature High -entropy ceramics: review of principles, production and applications

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3695a8f-a6ed-49bf-9b78-a35c8177ade1 · outbound

This paper cites High -entropy alloy TiV 2ZrCrMnFeNi for hydrogen storage at room temperature with full reversibility and good activation.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature High -entropy alloy TiV 2ZrCrMnFeNi for hydrogen storage at room temperature with full reversibility and good activation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe1652ce-d9bf-45ab-a5ea-80b9e580a799 · outbound

This paper cites High -entropy alloys as anode materials of nickel-metal hydride batteries.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature High -entropy alloys as anode materials of nickel-metal hydride batteries

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e58a05b-3475-43eb-8fd6-1be823e0752d · outbound

This paper cites AB-type dual-phase high-entropy alloys as negative electrode of Ni-MH batteries: Impact of interphases on electrochemical performance.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature AB-type dual-phase high-entropy alloys as negative electrode of Ni-MH batteries: Impact of interphases on electrochemical performance

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6cfbf73f-ddbe-4176-b648-8a5b2ece80b4 · outbound

This paper cites Developing a single -phase and nanograined refractory high -entropy alloy ZrHfNbTaW with ultrahigh hardness by phase transformation via high -pressure torsion.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Developing a single -phase and nanograined refractory high -entropy alloy ZrHfNbTaW with ultrahigh hardness by phase transformation via high -pressure torsion

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b3fecaf-170c-4c84-927c-c38d9b582ba4 · outbound

This paper cites Boosting biocompatibility and mechanical property evolution in a high-entropy alloy via nanostructure engineering and phase transformations.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Boosting biocompatibility and mechanical property evolution in a high-entropy alloy via nanostructure engineering and phase transformations

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d6ba375-3d53-4e2d-97c5-8b456e9e99df · outbound

This paper cites Recent progress in high-entropy alloys.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Recent progress in high-entropy alloys

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df08724a-d91d-4e90-a586-35118a638d28 · outbound

This paper cites High -entropy hydrides for fast and reversible hydrogen storage at room temperature: binding -energy engineering via first -principles calculations and experiments.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature High -entropy hydrides for fast and reversible hydrogen storage at room temperature: binding -energy engineering via first -principles calculations and experiments

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d16214b2-5990-4c62-8d5d-7aa0958b34f0 · outbound

This paper cites Microstructural characterization and hydrogen storage properties at room temperature of Ti 21Zr21Fe41Ni17 medium entropy alloy.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Microstructural characterization and hydrogen storage properties at room temperature of Ti 21Zr21Fe41Ni17 medium entropy alloy

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67143c60-941a-4940-b192-68db5729bb10 · outbound

This paper cites Crystal structure and hydrogen storage properties of ZrNbFeCo medium -entropy alloy.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Crystal structure and hydrogen storage properties of ZrNbFeCo medium -entropy alloy

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2016edef-c2ec-4919-9d12-3c59c1c00010 · outbound

This paper cites an unresolved cited work.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Unresolved cited work

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 680ce6dc-6abf-4f6e-96a3-6ba8d87613fb · outbound

This paper cites Effect of particle size, pressure and temperature on the activation process of hydrogen absorption in TiVZrHfNb high entropy alloy.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Effect of particle size, pressure and temperature on the activation process of hydrogen absorption in TiVZrHfNb high entropy alloy

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aeafbbb7-8054-4d7c-ab05-5e2a62bbb3f8 · outbound

This paper cites Hydrogen storage properties of the refractory Ti-V-Zr-Nb-Ta multi-principal element alloy.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Hydrogen storage properties of the refractory Ti-V-Zr-Nb-Ta multi-principal element alloy

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbc855fd-d5c0-497f-8845-1ef774f8dd3d · outbound

This paper cites Hydrogen sorption in TiZrNbHfTa high entropy alloy.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Hydrogen sorption in TiZrNbHfTa high entropy alloy

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23a7ba66-64d9-4419-9179-52be86a7d2b3 · outbound

This paper cites Machine learning analysis of alloying element effects on hydrogen storage properties of AB 2 metal hydrides.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Machine learning analysis of alloying element effects on hydrogen storage properties of AB 2 metal hydrides

Reference 32

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ab0ef1b-ded8-42c4-9e84-c6abfcc63f8f · outbound

This paper cites Hydrogen site occupancy in AB 2 Laves phase.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Hydrogen site occupancy in AB 2 Laves phase

Reference 33

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1aa5f949-ec3f-48c4-a4b0-e984c9309f7a · outbound

This paper cites Research progress in solid -state hydrogen storage alloys: A review.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Research progress in solid -state hydrogen storage alloys: A review

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2673291-74a5-498a-9942-3a7e51294172 · outbound

This paper cites A review on metal hydride materials for hydrogen storage.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature A review on metal hydride materials for hydrogen storage

Reference 35

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 350bfa0c-0c3c-40e4-bebb-19c81e9b7215 · outbound

This paper cites Reproducibility in density functional theory calculations of solids.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Reproducibility in density functional theory calculations of solids

Reference 36

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e25d90b-a3ce-4d95-bfdf-661e292ab843 · outbound

This paper cites Theoretical study of hydrogen storage in metal hydrides.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Theoretical study of hydrogen storage in metal hydrides

Reference 37

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fe84235-b3fc-415c-a74b-9bb522f517ca · outbound

This paper cites Design and synthesis of a magnesium alloy for room temperature hydrogen storage.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Design and synthesis of a magnesium alloy for room temperature hydrogen storage

Reference 38

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ebb8d06-5333-426b-a6dc-c0b823da5722 · outbound

This paper cites Machine learning for medical imaging.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Machine learning for medical imaging

Reference 39

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29dc9623-412a-4fbf-a972-1739d46ac19a · outbound

This paper cites an unresolved cited work.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Unresolved cited work

Reference 40

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04c4dacc-8d69-4a90-9e03-b260508fc016 · outbound

This paper cites Artificial intelligence and machine learning in finance: A bibliometric review.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Artificial intelligence and machine learning in finance: A bibliometric review

Reference 41

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89f26fd5-8e08-4d18-8775-d0044fbd37cf · outbound

This paper cites Neural networks vs Gaussian process regression for representing potential energy surfaces: A comparative study of fit quality and vibrational spectrum accuracy.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Neural networks vs Gaussian process regression for representing potential energy surfaces: A comparative study of fit quality and vibrational spectrum accuracy

Reference 42

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 291bf784-e244-4fa6-9f94-30e40ac70191 · outbound

This paper cites Machine learning in materials science.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Machine learning in materials science

Reference 43

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72bc39cc-debd-490e-b07b-4cc7df1507cd · outbound

This paper cites 14 examples of how LLMs can transform materials science and chemistry: A reflection on a large language model hackathon.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature 14 examples of how LLMs can transform materials science and chemistry: A reflection on a large language model hackathon

Reference 44

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2558b78b-9d07-4922-a321-8b2d7d11761d · outbound

This paper cites Machine learning assisted design of BCC high entropy alloys for room temperature hydrogen storage.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Machine learning assisted design of BCC high entropy alloys for room temperature hydrogen storage

Reference 45

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d21f6b0b-d48b-4c08-8029-bbb9aa0cb7f0 · outbound

This paper cites Machine learning enabled customization of performance -oriented hydrogen storage materials for fuel cell systems.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Machine learning enabled customization of performance -oriented hydrogen storage materials for fuel cell systems

Reference 46

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32a69479-d86b-42b1-a5ea-d47f7c158222 · outbound

This paper cites Estimating hydrogen absorption energy on different metal hydrides using gaussian process regression approach.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Estimating hydrogen absorption energy on different metal hydrides using gaussian process regression approach

Reference 47

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6115b6ed-8173-4c86-a0aa-b9572c1afcd1 · outbound

This paper cites Machine learning assisted predictions for hydrogen storage in metal-organic frameworks.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Machine learning assisted predictions for hydrogen storage in metal-organic frameworks

Reference 48

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76d8b961-d476-443f-a0d0-105e5503776c · outbound

This paper cites Machine learning based prediction of metal hydrides for hydrogen storage, part I: prediction of hydrogen weight percent.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Machine learning based prediction of metal hydrides for hydrogen storage, part I: prediction of hydrogen weight percent

Reference 49

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c26bb38c-27b1-41ae-9c44-af0c9f3d6e78 · outbound

This paper cites Impact of outlier detection on neural networks based property value prediction.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Impact of outlier detection on neural networks based property value prediction

Reference 50

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6fb2057-6c92-4f68-aaa8-47b84b17fc77 · outbound

This paper cites Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median

Reference 51

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85da60eb-ecf5-4cc1-a51f-6b64a5f1d69b · outbound

This paper cites Robust Statistics.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Robust Statistics

Reference 52

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 019abae8-81d0-4091-b22a-046c8c9cd730 · outbound

This paper cites Alternatives to the median absolute deviation.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Alternatives to the median absolute deviation

Reference 53

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2baf723e-de1f-4093-a6ba-ab63b4aee43d · outbound

This paper cites Graphical representation of chemical periodicity of main elements through boxplot.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Graphical representation of chemical periodicity of main elements through boxplot

Reference 54

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdb9d604-6f77-4820-a084-4abc421bfca8 · outbound

This paper cites Beating the hold-out: Bounds for k-fold and progressive cross- validation.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Beating the hold-out: Bounds for k-fold and progressive cross- validation

Reference 55

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c7c10bf-02a3-4450-9184-a86b4bdffe2f · outbound

This paper cites Greedy function approximation: A gradient boosting machine.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Greedy function approximation: A gradient boosting machine

Reference 56

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db817276-ae83-4785-ade9-a9c71ba83e97 · outbound

This paper cites Special quasirandom structures.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Special quasirandom structures

Reference 57

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ac68647-0a27-4ac4-a6b3-c4f7dc239c72 · outbound

This paper cites ICET – A python library for constructing and sampling alloy cluster expansions.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature ICET – A python library for constructing and sampling alloy cluster expansions

Reference 58

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6aa1df47-d465-4817-96fd-e5da113412ea · outbound

This paper cites Machine learning potentials for hydrogen absorption in TiCr2 Laves phases.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Machine learning potentials for hydrogen absorption in TiCr2 Laves phases

Reference 59

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61e5dd1d-e44e-46c1-afe8-5886f1e8f5dc · outbound

This paper cites Concerning atomic sites and capacities for hydrogen absorption in the AB2 Friauf-Laves phases.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Concerning atomic sites and capacities for hydrogen absorption in the AB2 Friauf-Laves phases

Reference 60

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d099115-5666-4e8f-ade0-80c6701fc020 · outbound

This paper cites First -principles calculations of C14 -type Laves phase Ti-Mn hydrides.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature First -principles calculations of C14 -type Laves phase Ti-Mn hydrides

Reference 61

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0231aa41-732b-49f5-b712-498a836e0515 · outbound

This paper cites Substitutional effect of Ti -based AB2 hydrogen storage alloys: A density functional theory study.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Substitutional effect of Ti -based AB2 hydrogen storage alloys: A density functional theory study

Reference 62

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5bac4e8-85e5-47ef-aba6-2a5a0947f3a6 · outbound

This paper cites A DFT study of hydrogen storage in Zr (Cr0.5Ni0.5)2 Laves phase.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature A DFT study of hydrogen storage in Zr (Cr0.5Ni0.5)2 Laves phase

Reference 63

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbcdd9a8-9e18-4626-9bdc-dab32fe5d585 · outbound

This paper cites Concerning atomic sites and capacities for hydrogen absorption in the AB2 Friauf-Laves phases.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Concerning atomic sites and capacities for hydrogen absorption in the AB2 Friauf-Laves phases

Reference 64

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c580883-26e0-4f06-93ae-88dc76d30d87 · outbound

This paper cites Ab initio molecular dynamics for liquid metals.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Ab initio molecular dynamics for liquid metals

Reference 65

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3cf44bc7-fcb9-44a9-9fb6-f3cd0acd5947 · outbound

This paper cites Efficient iterative schemes for ab initio total -energy calculations using a plane-wave basis set.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Efficient iterative schemes for ab initio total -energy calculations using a plane-wave basis set

Reference 66

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04646c9c-2ed9-473d-b44e-0d79f37c4170 · outbound

This paper cites Projector augmented-wave method.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Projector augmented-wave method

Reference 67

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b57d04c2-747e-4bc9-8101-e7802176537c · outbound

This paper cites Generalized gradient approximation made simple.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Generalized gradient approximation made simple

Reference 68

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbe12527-d948-45ff-8d44-13308e532ddf · outbound

This paper cites Iterative minimization techniques for ab initio total -energy calculations: molecular dynamics and conjugate gradients.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Iterative minimization techniques for ab initio total -energy calculations: molecular dynamics and conjugate gradients

Reference 69

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84ef65e6-35b8-42e7-b75a-c7c0fa796f6d · outbound

This paper cites Hydride destabilization in the Ti –Nb–Cr system through Nb/Ti ratio adjustment.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Hydride destabilization in the Ti –Nb–Cr system through Nb/Ti ratio adjustment

Reference 70

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 294db5c1-f7e5-4ecc-bb20-aa61ccf65075 · outbound

This paper cites Hydrogen storage of C14-CruFevMnwTixVyZrz alloys.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Hydrogen storage of C14-CruFevMnwTixVyZrz alloys

Reference 71

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0b445bd-9c58-4fda-bfb7-a54af44363ce · outbound

This paper cites Study on the hydrogen storage properties of a TiZrNbTa high entropy alloy.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Study on the hydrogen storage properties of a TiZrNbTa high entropy alloy

Reference 72

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2b20a40-c8c4-455f-980d-d92cd2d69c0d · outbound

This paper cites Room temperature hydrogen storage properties of Ti -Zr-Mn-Fe-Co high -entropy alloys designed by semi - empirical descriptors, thermodynamic calculations and machine learning.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Room temperature hydrogen storage properties of Ti -Zr-Mn-Fe-Co high -entropy alloys designed by semi - empirical descriptors, thermodynamic calculations and machine learning

Reference 73

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c14adf2f-13fe-40c3-9d22-5df3bce7c1f9 · outbound

This paper cites Laves phases: a review of their functional and structural applications and an improved fundamental understanding of stability and properties.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Laves phases: a review of their functional and structural applications and an improved fundamental understanding of stability and properties

Reference 74

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f28dc15-4817-4f41-8b58-0df87539c714 · outbound

This paper cites The Metal-Hydrogen System.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature The Metal-Hydrogen System

Reference 75

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ade8373-6d42-4b44-86b0-5ff3575f5d04 · outbound

This paper cites Influence of interphase boundary coherency in high-entropy alloys on their hydrogen storage performance.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Influence of interphase boundary coherency in high-entropy alloys on their hydrogen storage performance

Reference 76

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8d02bc0-4908-4f97-a5a8-6eca07d5d9cf · outbound

This paper cites Impact of severe plastic deformation on microstructure and hydrogen storage of titanium-iron-manganese intermetallics.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Impact of severe plastic deformation on microstructure and hydrogen storage of titanium-iron-manganese intermetallics

Reference 77

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2546c821-7173-4fdd-8848-85a11534fae8 · outbound

This paper cites High-pressure torsion for new hydrogen storage materials.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature High-pressure torsion for new hydrogen storage materials

Reference 78

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0b6fc84-d3d2-403f-8f17-e216a39b3cea · outbound

This paper cites Evolutionary Gaussian processes.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Evolutionary Gaussian processes

Reference 79

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7884ab8-02d9-4bc7-9cf6-91ba150dac8b · outbound

This paper cites Ab initio assisted design of quinary dual-phase high -entropy alloys with transformation -induced plasticity.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Ab initio assisted design of quinary dual-phase high -entropy alloys with transformation -induced plasticity

Reference 80

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb2c5977-da04-4d8d-abf2-27531f4550ad · outbound

This paper cites Advanced high -pressure metal hydride fabricated via Ti –Cr–Mn alloys for hybrid tank.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Advanced high -pressure metal hydride fabricated via Ti –Cr–Mn alloys for hybrid tank

Reference 81

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64d41d1a-79e5-43cb-b783-896f4fe3e0f2 · outbound

This paper cites Active high -entropy photocatalyst designed by incorporating alkali metals to achieve d0+d10+s0 cationic configurations and wide electronegativity mismatch.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Active high -entropy photocatalyst designed by incorporating alkali metals to achieve d0+d10+s0 cationic configurations and wide electronegativity mismatch

Reference 82

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43067f84-9c10-48ad-a361-609d3a115d62 · outbound

This paper cites High-entropy perovskites as new photocatalysts for cocatalyst- free water splitting.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature High-entropy perovskites as new photocatalysts for cocatalyst- free water splitting

Reference 83

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f3db14f-bebd-4fc0-8b58-d7b230eee3a7 · outbound

This paper cites Hydrogen sorption properties of ZrFex (1.9 ≤ x ≤ 2.5) alloys.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Hydrogen sorption properties of ZrFex (1.9 ≤ x ≤ 2.5) alloys

Reference 84

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc81d9ce-4a06-46f8-878d-d73e5a7c4f72 · outbound

This paper cites Sites occupation and thermodynamic properties of the TiCr2−xMnx–H2 (0≤x≤1) system: statistical thermodynamics analysis.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Sites occupation and thermodynamic properties of the TiCr2−xMnx–H2 (0≤x≤1) system: statistical thermodynamics analysis

Reference 85

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 095570c4-0599-4740-adbf-95d67b2d1600 · outbound

This paper cites Structure, morphology and hydrogen storage properties of a Ti 0.97Zr0.019V0.439Fe0.097Cr0.045Al0.026Mn1.5 alloy.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Structure, morphology and hydrogen storage properties of a Ti 0.97Zr0.019V0.439Fe0.097Cr0.045Al0.026Mn1.5 alloy

Reference 86

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30dd55c9-c7ec-44eb-a9e3-34123c7df456 · outbound

This paper cites The structure, hydrogen storage, and electrochemical properties of Fe-doped C14-predominating AB2 metal hydride alloys.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature The structure, hydrogen storage, and electrochemical properties of Fe-doped C14-predominating AB2 metal hydride alloys

Reference 87

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f65e9b17-5a0b-4b48-a02a-7f9ec608c034 · outbound

This paper cites AB2 metal hydrides for high -pressure and narrow temperature interval applications.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature AB2 metal hydrides for high -pressure and narrow temperature interval applications

Reference 88

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a480eb73-ce6f-424e-9e79-ceebf158096b · outbound

This paper cites IMC of vanadium -free hypo-stoichiometric AB2 metal hydride alloy for Ni/MH battery application.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature IMC of vanadium -free hypo-stoichiometric AB2 metal hydride alloy for Ni/MH battery application

Reference 89

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee16802e-3873-4025-8e8e-a98e7d9a9ddb · outbound

This paper cites Development of ZrFeV alloys for hybrid hydrogen storage system.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Development of ZrFeV alloys for hybrid hydrogen storage system

Reference 90

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8586c0c3-f384-4e68-84e6-b945823f9a5a · outbound

This paper cites Effect of CO2 on hydrogen absorption in Ti -Zr-Mn- Cr based AB2 type alloys.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Effect of CO2 on hydrogen absorption in Ti -Zr-Mn- Cr based AB2 type alloys

Reference 91

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d77b5a73-bcb8-48cb-a2f9-390c62555442 · outbound

This paper cites Effect of molybdenum content on structural, gaseous storage, and electrochemical properties of C14-predominant AB2 metal hydride alloys.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Effect of molybdenum content on structural, gaseous storage, and electrochemical properties of C14-predominant AB2 metal hydride alloys

Reference 92

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 668a70eb-79f0-4cad-8b96-1ca0d858234d · outbound

This paper cites Effect of rare earth doping on the hydrogen storage performance of Ti1.02Cr1.1Mn0.3Fe0.6 alloy for hybrid hydrogen storage application.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Effect of rare earth doping on the hydrogen storage performance of Ti1.02Cr1.1Mn0.3Fe0.6 alloy for hybrid hydrogen storage application

Reference 93

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a81a023-f00a-4d08-86e3-df3acb76c9d8 · outbound

This paper cites Effects of B, Fe, Gd, Mg, and C on the structure, hydrogen storage, and electrochemical properties of vanadium -free AB 2 metal hydride alloy.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Effects of B, Fe, Gd, Mg, and C on the structure, hydrogen storage, and electrochemical properties of vanadium -free AB 2 metal hydride alloy

Reference 94

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5728c9d-195f-476d-b036-7779694cffc4 · outbound

This paper cites Effects of La-addition to the structure, hydrogen storage, and electrochemical properties of C14 metal hydride alloys.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Effects of La-addition to the structure, hydrogen storage, and electrochemical properties of C14 metal hydride alloys

Reference 95

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 150305fc-5472-4ca6-91c6-606e9a32c41d · outbound

This paper cites Hydrogen storage properties and microstructures of Ti 0.7Zr0.3(Mn1−xVx)2 (x = 0.1, 0.2, 0.3, 0.4, 0.5) alloys.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Hydrogen storage properties and microstructures of Ti 0.7Zr0.3(Mn1−xVx)2 (x = 0.1, 0.2, 0.3, 0.4, 0.5) alloys

Reference 96

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e919eb1-d5f2-4d16-b309-a7e960fd157e · outbound

This paper cites IMC hydrides with high hydrogen dissociation pressure.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature IMC hydrides with high hydrogen dissociation pressure

Reference 97

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d22a85b-2f69-446e-b67f-46f7377821ed · outbound

This paper cites Improvement of hydrogen storage properties of the AB2 Laves phase alloys for automotive application.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Improvement of hydrogen storage properties of the AB2 Laves phase alloys for automotive application

Reference 98

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 907052de-e1e6-4c19-bb7b-247c5f118f16 · outbound

This paper cites Laves phase hydrogen storage alloys for super-high-pressure metal hydride hydrogen compressors.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Laves phase hydrogen storage alloys for super-high-pressure metal hydride hydrogen compressors

Reference 99

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4be1401-3555-4966-9639-cc5f778b5b72 · outbound

This paper cites Nonstoichiometric Ti -Zr-Ni-V-Mn alloys: the effect of composition on hydrogen sorption and electrochemical characteristics.

Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature Nonstoichiometric Ti -Zr-Ni-V-Mn alloys: the effect of composition on hydrogen sorption and electrochemical characteristics

Reference 100

Resolution: unresolved; no resolver link, observed 2026-06-28T05:25:01.201066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers