Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:30:24.350242Z
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2507.08277.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:30:24.350242Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
46 of 46 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 2357cabb-2f89-4b63-a4fe-09f9c1bb453e · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Ammonia for power
Reference 1
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Observation cf68c922-5344-4ad4-b237-9a75380a0d5e · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Review on Ammonia as a Potential Fuel: From Synthesis to Economics
Reference 2
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Observation 58662577-c53f-4bb6-80ee-4e3486483e02 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Ammonia as a hydrogen energy carrier
Reference 3
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Observation c246e767-334b-4272-9db0-3e2ed7334d12 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation A review of ammonia as a compression ignition engine fuel
Reference 4
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Observation 6dfa9851-fc56-4ca9-b194-df127b54135d · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Unlocking ammonia engines: pre-chamber ignition with partial ammonia cracking
Reference 5
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Observation 1b544feb-b59f-4ef1-bf11-dbcadcdc708c · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation A review on clean ammonia as a potential fuel for power generators
Reference 6
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Observation 6c36c9ef-680a-4815-be58-66920cc6f5ed · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Ammonia as Effective Hydrogen Storage: A Review on Production, Storage and Utilization
Reference 7
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Observation 1a315342-4722-44a8-a996-6e14f5feded3 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Emission and Combustion Characteristics of Ammonia/Methane Mixtures for Carbon Reduction and Alternative Fuel Development
Reference 8
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Observation cc752ab9-6a5e-4f81-91ca-715b9e3b023e · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Effects of injection pa- rameters on the combustion characteristics of ammonia-diesel dual-fuel direct-injection (ADDI) mode and combustion enhancement at high ammonia energy ratio
Reference 9
Source-reported events for the cited work
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Observation 43542251-ad4a-4001-a284-dfdfbe63e61b · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Renew and Sustain Energy Rev
Reference 10
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Observation a6cb9384-d54f-418a-a08c-be107ab2954f · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Propagation and emissions of premixed methane-ammonia/air flames
Reference 11
Source-reported events for the cited work
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Observation 59d0d219-f262-47e0-a760-4b8f348478ac · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Toward accommodating realistic fuel chemistry in large- scale computations
Reference 12
Source-reported events for the cited work
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Observation 09d645ea-f078-4373-94d9-07e0d23bf320 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Revealing the mechanisms of ammonia dual- fuel combustion for decarbonization in marine transportation
Reference 13
Source-reported events for the cited work
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Observation dcb6a5be-85ea-4d51-946d-1584684f85a6 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Numerical simulation of ammonia/methane/air combustion using reduced chem- ical kinetics models
Reference 14
Source-reported events for the cited work
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Observation d7b1550a-195b-4006-8af5-9539649a3c6d · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Predictions of NO and CO emissions in ammonia/methane/air combus- tion by LES using a non-adiabatic flamelet generated manifold
Reference 15
Source-reported events for the cited work
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Observation 5a6b4c7c-9d29-4472-a60e-4347e16fe26c · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Machine Learning for Chemical Reactions
Reference 16
Source-reported events for the cited work
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Observation 5cb25edf-d43f-4f34-a72b-c18136a65f63 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation A multi-scale sampling method for accurate and robust deep neural network to predict combustion chemical kinetics
Reference 17
Source-reported events for the cited work
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Observation af358739-4a2f-443c-9c76-1c5862021d1e · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Machine learning for com- bustion chemistry
Reference 18
Source-reported events for the cited work
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Observation 7851bb24-5767-469b-9328-0ee3542ac56c · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Artificial intelligence as a catalyst for combustion science and engineering
Reference 19
Source-reported events for the cited work
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Observation 2116da81-da7a-4859-9e3c-92976530e776 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Numerical simulation of tur- bulent combustion: Scientific challenges
Reference 20
Source-reported events for the cited work
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Observation eb4f8b37-85d0-484a-a15a-41a496578e15 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Machine learning tabu- lation of thermochemistry in turbulent combustion: An approach based on hybrid flamelet/random data and multiple multilayer perceptrons
Reference 21
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Observation 55f2ee95-db17-437e-8778-01d37b80da76 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Criteria to switch from tabulation to neural networks in computational combustion
Reference 22
Source-reported events for the cited work
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Observation 825b669e-7526-4d78-a69e-d9a113477b32 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation On-the-fly artificial neural network for chemical kinetics in direct numerical simulations of premixed combus- tion
Reference 24
Source-reported events for the cited work
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Observation 4e32fbb3-6232-4c95-bd04-1571514c3c5d · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Chemistry reduction using machine learning trained from non-premixed micro-mixing modeling: Application to DNS of a syngas turbulent oxy-flame with side-wall ef- fects
Reference 25
Source-reported events for the cited work
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Observation e7334d15-d9e7-47ae-9938-be5b7b7880be · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Artificial neural network chem- istry solving for high-pressure hydrogen–air combustion
Reference 26
Source-reported events for the cited work
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Observation a6c656ef-3fe5-431d-8592-d5ab4a3a5414 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Unresolved cited work
Reference 27
Source-reported events for the cited work
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Observation d4f6b4c8-677d-4dc8-a07f-1fb65cfb101d · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Tabulation of combus- tion chemistry via Artificial Neural Networks (ANNs): Methodology and application to LES-PDF simulation of Sydney flame L
Reference 28
Source-reported events for the cited work
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Observation cdc6754b-f0c7-4af4-9b69-3d045384c6d9 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Simulation of turbulent premixed flames with machine learning - tabulated thermochemistry
Reference 29
Source-reported events for the cited work
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Observation f66ffbdf-b099-4661-ae88-e8e78e356c56 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation A feasibility study on the use of low-dimensional simulations for database generation in adaptive chem- istry approaches
Reference 30
Source-reported events for the cited work
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Observation a431676d-a039-46b5-8c9a-f75ec4328135 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Simplifying chemical kinetics: Intrinsic low- dimensional manifolds in composition space
Reference 31
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Observation eeaff7a7-0412-4db0-803e-a3fb7c716d7e · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Graphics process- ing unit/artificial neural network-accelerated large-eddy simulation of swirling premixed flames
Reference 32
Source-reported events for the cited work
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Observation 0e3c8343-24a5-4b00-a19f-533c21d87299 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Comprehensive deep learning for combustion chemistry integration: Multi-fuel gener- alization anda posteriorivalidation in reacting flow
Reference 33
Source-reported events for the cited work
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Observation 843a7cc7-d9ad-403e-ab57-f9cd516ce283 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Experimental and numerical study of the laminar burning velocity of CH4–NH3–air premixed flames
Reference 34
Source-reported events for the cited work
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Observation 2124faf3-e976-454c-a080-722477850348 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Cantera: An Object-oriented Software Toolkit for Chemical Kinetics, Thermody- namics, and Transport Processes
Reference 35
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Observation cd1f37a9-8c28-4fa4-a699-d67ea2e70c77 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation DeepFlame: A deep learning empowered open-source platform for reacting flow simulations
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Source-reported events for the cited work
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Observation e4036124-9e1d-43bb-9521-fd1245a55cd8 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation An integrated framework for accelerating reactive flow simulation using GPU and ma- chine learning models
Reference 37
Source-reported events for the cited work
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Observation 3a683c67-79f8-4caf-a7a0-5a39de4bec88 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation DeepFlame 2.0: A new version for fully GPU-native machine learning accelerated reacting flow simulations under low-Mach conditions
Reference 38
Source-reported events for the cited work
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Observation 28fe7a19-34c1-4d17-bf2c-a2a2afb48111 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Machine learning tabulation of ther- mochemistry of fuel blends
Reference 39
Source-reported events for the cited work
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Observation 841acad7-408e-4001-b488-c1fcaad6fb51 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Delving into Deep Imbalanced Regression
Reference 40
Source-reported events for the cited work
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Observation 4b5f4887-3468-4b14-b26b-a08e594f9473 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Data-driven simulation of ammonia combustion using neural ordinary differential equations (NODE)
Reference 41
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Observation 932ccc14-69d7-4159-aeb2-ca4e58845576 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Clustering-Enhanced Deep Learning Method for Computation of Full Detailed Ther- mochemical States via Solver-Based Adaptive Sampling
Reference 42
Source-reported events for the cited work
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Observation 27992316-00ef-4c59-acac-eef529e845e2 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Combust Theory and Model
Reference 43
Source-reported events for the cited work
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Observation 0acc14f6-1854-47cf-860f-b301336b6a42 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation An improved approach towards more robust deep learning models for chemical kinetics
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Source-reported events for the cited work
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Observation d281cbb3-190e-42f0-bdce-30041139d3c6 · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Unresolved cited work
Reference 45
Source-reported events for the cited work
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Observation 4a8adb6c-329e-4509-9246-75536d81167f · outbound
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation Efficient machine learningmethodforsupercriticalcombustion: Predictingreal-fluidprop- erties and chemical ODEs
Reference 46
Source-reported events for the cited work
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Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation DNSLab: A gateway to turbulent flow sim- ulation in Matlab
Reference 47
Source-reported events for the cited work
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No inbound Pith citation observations are available.