SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators | Paper Citation Record

Observation b8b701bb-88cc-4b8e-a1e8-f0dcefb7d9cf · outbound

This paper cites The design process for google’s training chips: Tpuv2 and tpuv3.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators The design process for google’s training chips: Tpuv2 and tpuv3

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:41:28.066205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f06f0228-7107-421a-99f1-117cdee05f56 · outbound

This paper cites Serving Large Language Models on Huawei CloudMatrix384.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Serving Large Language Models on Huawei CloudMatrix384

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:41:28.008614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 501d1630-83c0-4515-ae3d-a9cb9562e35f · outbound

This paper cites Breaking the molecular dynamics timescale barrier using a wafer-scale system.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Breaking the molecular dynamics timescale barrier using a wafer-scale system

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:41:28.154347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d9ad300d-8c6a-4a3a-b820-f93844e1555e · outbound

This paper cites Distributed training of large language models on aws trainium.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Distributed training of large language models on aws trainium

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T17:30:38.919439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1b1c69e3-4e62-49b1-b5a2-349c1e9d880a · outbound

This paper cites First impressions of the sapphire rapids processor with hbm for scientific workloads.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators First impressions of the sapphire rapids processor with hbm for scientific workloads

Reference 5

Resolution: verified exact; doi, observed 2026-05-10T17:30:38.929208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 79143413-f9db-4fab-916a-84dcd6b3ab01 · outbound

This paper cites Nvidia hopper h100 gpu: Scaling performance.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Nvidia hopper h100 gpu: Scaling performance

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:41:28.135141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5265ccc4-bb21-42c1-aebb-5eda98526061 · outbound

This paper cites The co-evolution of computational physics and high-performance computing.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators The co-evolution of computational physics and high-performance computing

Reference 7

Resolution: verified exact; doi, observed 2026-05-10T17:30:38.898092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation af8c70c1-d23e-4cc2-bb7c-abf22fb931c6 · outbound

This paper cites A generative model for inorganic materials design.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators A generative model for inorganic materials design

Reference 8

Resolution: verified exact; doi, observed 2026-05-10T17:30:38.907372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 2f40e6a1-62f7-459f-ba44-43e955672f66 · outbound

This paper cites Machine learning interatomic potentials at the centennial crossroads of quantum mechanics.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Machine learning interatomic potentials at the centennial crossroads of quantum mechanics

Reference 9

Resolution: verified exact; doi, observed 2026-05-10T17:30:38.900632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ee20bfbd-867c-48bb-a0b4-ddb175c30dc6 · outbound

This paper cites Roadmap for the development of machine learning-based interatomic potentials.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Roadmap for the development of machine learning-based interatomic potentials

Reference 10

Resolution: verified exact; doi, observed 2026-05-10T17:30:38.931201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f4af1f23-9a5d-4234-85bc-0411ced8fc46 · outbound

This paper cites Discovery through the computational microscope.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Discovery through the computational microscope

Reference 11

Resolution: verified exact; doi, observed 2026-05-10T17:30:38.916100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 3b4555bb-7d9b-478f-802a-0d10874ae86f · outbound

This paper cites Advances in Measuring the Environmental and Social Impacts of Environmental Programs.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Advances in Measuring the Environmental and Social Impacts of Environmental Programs

Reference 12

Resolution: malformed identifier; doi_truncated, observed 2026-05-10T17:30:38.913472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 78bc725f-6059-4a29-9713-8efeb97cd365 · outbound

This paper cites Towards computational microscope of chemical order-disorder via ml-accelerated monte carlo simulation.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Towards computational microscope of chemical order-disorder via ml-accelerated monte carlo simulation

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:41:28.856307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d2e85342-4c7a-4e06-a8f6-d6ed301634bb · outbound

This paper cites Scaling the leading accuracy of deep equivariant models to biomolecular simulations of realistic size.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Scaling the leading accuracy of deep equivariant models to biomolecular simulations of realistic size

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:11:44.278994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9d5617fa-a660-49f5-aed4-cea99c51fad0 · outbound

This paper cites Available: https://doi.org/10.1145/3581784.3627041.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Available: https://doi.org/10.1145/3581784.3627041

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-10T17:30:38.927366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7b7fa814-1f3f-41d9-a1eb-aa14ef39c24a · outbound

This paper cites Atomistic simulations of dislocation mobility in refractory high-entropy alloys and the effect of chemical short-range order.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Atomistic simulations of dislocation mobility in refractory high-entropy alloys and the effect of chemical short-range order

Reference 16

Resolution: verified exact; doi, observed 2026-05-10T17:30:38.910322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1c26e1ff-0279-4e69-a8b4-07696102c6b7 · outbound

This paper cites Mechanism on lattice thermal conductivity of carbon-vacancy and porous medium entropy ceramics.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Mechanism on lattice thermal conductivity of carbon-vacancy and porous medium entropy ceramics

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:11:44.282249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0a743543-b099-4df6-888b-5356ac06296a · outbound

This paper cites Billion atom molecular dynamics simulations of carbon at extreme conditions and experimental time and length scales.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Billion atom molecular dynamics simulations of carbon at extreme conditions and experimental time and length scales

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-10T17:30:38.904282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e6a168a5-fc52-4d97-b8d2-113f9ed50e39 · outbound

This paper cites an unresolved cited work.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Unresolved cited work

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:41:28.227405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0b6f5b30-c518-4bd4-a7a5-8089dd1723b8 · outbound

This paper cites Efficient molecular dynamics simulations with many-body potentials on graphics processing units.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Efficient molecular dynamics simulations with many-body potentials on graphics processing units

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:11:44.245893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation a1f44b78-a740-4156-b2ca-5e0342ea6bd2 · outbound

This paper cites Revealing Nanostructures in High-Entropy Alloys via Machine-Learning Accelerated Scalable Monte Carlo Simulation.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Revealing Nanostructures in High-Entropy Alloys via Machine-Learning Accelerated Scalable Monte Carlo Simulation

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:41:28.497438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 348aa2cf-5323-4697-801d-9ea942c5c887 · outbound

This paper cites Smc-x: A distributed, scalable monte carlo simulation method for chemically complex alloys.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Smc-x: A distributed, scalable monte carlo simulation method for chemically complex alloys

Reference 22

Resolution: verified exact; doi, observed 2026-05-10T17:30:38.938325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 602b1efc-2858-4772-9194-8fd9ae42bfae · outbound

This paper cites Sadigh, P.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Sadigh, P

Reference 23

Resolution: metadata mismatch; doi, observed 2026-05-10T17:30:38.921811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 858caa6c-945a-4e1b-a1b8-8c0b66e3ed99 · outbound

This paper cites Mailoa, Mordechai Kornbluth, Nicola Molinari, Tess E.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Mailoa, Mordechai Kornbluth, Nicola Molinari, Tess E

Reference 24

Resolution: metadata mismatch; doi, observed 2026-05-10T17:30:38.935889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d225debd-afb2-4297-9315-11382a88c4b5 · outbound

This paper cites A scalable method for ab initio computation of free energies in nanoscale systems.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators A scalable method for ab initio computation of free energies in nanoscale systems

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:11:44.275906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 732c8928-8a33-4ac4-979b-fd7e15cb6940 · outbound

This paper cites Available: https://doi.org/10.1145/1654059.1654125.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Available: https://doi.org/10.1145/1654059.1654125

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-10T17:30:38.924786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6e2dc474-fade-4220-bc34-019e7db242ea · outbound

This paper cites Extending the limit of molecular dynamics with ab initio accuracy to 10 billion atoms.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Extending the limit of molecular dynamics with ab initio accuracy to 10 billion atoms

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-10T17:30:38.881417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c9ccd20f-35e6-4e5b-a0de-bfb0fcb11ce5 · outbound

This paper cites 29-billion atoms molecular dynamics simulation with ab initio accuracy on 35 million cores of new sunway supercomputer.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators 29-billion atoms molecular dynamics simulation with ab initio accuracy on 35 million cores of new sunway supercomputer

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:41:28.996475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 218023fd-64ce-4b8d-803d-641667176fec · outbound

This paper cites Tensormd: Molecular dynamics simulation with ab initio accuracy of 50 billion atoms.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Tensormd: Molecular dynamics simulation with ab initio accuracy of 50 billion atoms

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-10T17:30:38.878181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c57da760-737d-4ec2-95b2-4a19d6892500 · outbound

This paper cites General-purpose machine-learned potential for 16 elemental metals and their alloys.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators General-purpose machine-learned potential for 16 elemental metals and their alloys

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:11:44.242362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e159e332-12dc-482a-be88-258a557ae412 · outbound

This paper cites Available: https://doi.org/10.1038/s41467-024-54554-x.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Available: https://doi.org/10.1038/s41467-024-54554-x

Reference 31

Resolution: verified exact; doi, observed 2026-05-10T17:30:38.874571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 86748d9a-6c84-4086-95d8-a1509d7f01ae · outbound

This paper cites Gpu accelerated monte carlo simulation of the 2d and 3d ising model.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Gpu accelerated monte carlo simulation of the 2d and 3d ising model

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:11:44.249759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 67eaeaaa-09fb-40e0-98f4-5b448f5b68bf · outbound

This paper cites High performance monte carlo simulation of ising model on tpu clusters.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators High performance monte carlo simulation of ising model on tpu clusters

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-10T17:30:38.872176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5e20e0ba-593f-4818-a067-3cad59198c47 · outbound

This paper cites High performance implementations of the 2d ising model on gpus.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators High performance implementations of the 2d ising model on gpus

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:11:44.256861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 3349ee18-072b-4cb4-941a-be00c2b8515c · outbound

This paper cites Gpu-accelerated gibbs ensemble monte carlo simulations of lennard-jonesium.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Gpu-accelerated gibbs ensemble monte carlo simulations of lennard-jonesium

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:11:44.268816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ee8994b4-86fd-40d1-986e-038d834bf4e0 · outbound

This paper cites Lammps - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Lammps - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:11:44.273034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation fce6b878-816e-42e4-afaa-c213fb6f051b · outbound

This paper cites Complex strengthening mechanisms in the NbMoTaW multi-principal element alloy.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Complex strengthening mechanisms in the NbMoTaW multi-principal element alloy

Reference 37

Resolution: verified exact; doi, observed 2026-05-10T17:30:38.883875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 487ce046-f0cb-4697-afc6-ed4e08ef9706 · outbound

This paper cites Revealing nanostructures in high-entropy alloys via machine-learning accelerated scalable monte carlo simulation.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Revealing nanostructures in high-entropy alloys via machine-learning accelerated scalable monte carlo simulation

Reference 38

Resolution: verified exact; doi, observed 2026-05-10T17:30:38.869056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e938f172-ebbe-4365-949d-36af5168f827 · outbound

This paper cites FastAttention: Extend FlashAttention2 to NPUs and Low-resource GPUs.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators FastAttention: Extend FlashAttention2 to NPUs and Low-resource GPUs

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:41:28.896017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 794ff764-71b2-4741-a362-6c4a3dbb5fac · outbound

This paper cites Huawei cloud model-as-a-service on the cloudmatrix384 superpod.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Huawei cloud model-as-a-service on the cloudmatrix384 superpod

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:41:28.681376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 77c493b3-e37d-4197-9eb4-86f947f6e741 · outbound

This paper cites Eisenbach, Y.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Eisenbach, Y

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:41:28.538829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 8775648e-eac6-4714-a626-56a80427e644 · outbound

This paper cites Order-N multiple scattering approach to electronic structure calculations.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Order-N multiple scattering approach to electronic structure calculations

Reference 42

Resolution: verified exact; doi, observed 2026-05-10T17:30:38.890918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 8bdc9c58-b806-4aec-8757-ee4331870fe1 · outbound

This paper cites Machine learning for high- entropy alloys: Progress, challenges and opportunities.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Machine learning for high- entropy alloys: Progress, challenges and opportunities

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:11:44.260077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation cbb82941-1309-4b0d-94e0-12cd8b425d0a · outbound

This paper cites Multicomponent intermetallic nanoparticles and superb mechanical behaviors of complex alloys.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Multicomponent intermetallic nanoparticles and superb mechanical behaviors of complex alloys

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:11:44.263445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 37fde8ca-cdf1-4c85-95b7-6e3509d2c306 · outbound

This paper cites High-entropy alloys.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators High-entropy alloys

Reference 45

Resolution: verified exact; doi, observed 2026-05-10T17:30:38.888564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 2a9199ea-b679-44a1-8f53-432f0168450d · outbound

This paper cites Machine- learning design of ductile fenicoalta alloys with high strength.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Machine- learning design of ductile fenicoalta alloys with high strength

Reference 46

Resolution: verified exact; doi, observed 2026-05-10T17:30:38.895697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d1ed492f-8d4e-4a84-8c1b-a8d8a6280ae9 · outbound

This paper cites Bifunctional nanoprecipitates strengthen and ductilize a medium-entropy alloy.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Bifunctional nanoprecipitates strengthen and ductilize a medium-entropy alloy

Reference 47

Resolution: verified exact; doi, observed 2026-05-10T17:30:38.893164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0c80cccc-f2cd-4af8-bdc8-bcbca9de113c · outbound

This paper cites Large scale hybrid monte carlo simulations for structure and property prediction.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Large scale hybrid monte carlo simulations for structure and property prediction

Reference 48

Resolution: verified exact; doi, observed 2026-05-10T17:30:38.886290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 29812a22-9057-4fb1-bcc0-ef433afa3a21 · outbound

This paper cites Chatgpt.

SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators Chatgpt

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:11:44.253241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers