Paper Citation Record · LEDGER

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics

As of 16 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2412.04142.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.04142 v1

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measured 30 of 30 reference resolution

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Reference resolution

30 of 30 outbound references displayed

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Outbound references

Observation 75dd1f4b-4d42-4fce-82b7-749ac879b990 · outbound

This paper cites Green gelled propellant highly throtteable rocket motor and gas generator technology: status and application.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Green gelled propellant highly throtteable rocket motor and gas generator technology: status and application

Reference 5

Resolution: verified exact; raw_fallback, observed 2026-08-11T21:47:18.722354Z

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Observation a5a88f9b-9996-4357-969a-3f2f3d95d5da · outbound

This paper cites Simultaneous measurement of rheological properties in a microfluidic rheometer.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Simultaneous measurement of rheological properties in a microfluidic rheometer

Reference 7

Resolution: verified exact; doi, observed 2026-08-11T21:47:18.391788Z

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Observation e72aadbc-c5f7-4392-ba3f-582d8084a743 · outbound

This paper cites DeepDDM: A Compact Deep-Learning Assisted Platform for Micro-Rheological Assessment of Micro-V olume Fluids.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics DeepDDM: A Compact Deep-Learning Assisted Platform for Micro-Rheological Assessment of Micro-V olume Fluids

Reference 11

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Observation ffdfeb9e-2c59-4c48-961e-4035f0ab4f6e · outbound

This paper cites Numerical modelling of incompressible flows for Newtonian and non-Newtonian fluids.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Numerical modelling of incompressible flows for Newtonian and non-Newtonian fluids

Reference 12

Resolution: verified exact; doi, observed 2026-08-11T21:47:18.341779Z

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Observation 3ae39ade-8a04-4a4b-80dc-4a314437e76e · outbound

This paper cites Design and use of an online drilling fluid pipe viscometer.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Design and use of an online drilling fluid pipe viscometer

Reference 16

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Observation 1b61c649-5c49-4d30-a068-5d06fdf72e50 · outbound

This paper cites Machine learning for microfluidic design and control.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Machine learning for microfluidic design and control

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T21:47:17.987456Z

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Observation 59578336-2465-4e45-a2ea-a61018d5714b · outbound

This paper cites F2E - Ultra High Pressure Distributed Pump Common Rail System.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics F2E - Ultra High Pressure Distributed Pump Common Rail System

Reference 18

Resolution: verified exact; doi, observed 2026-08-11T21:47:18.267441Z

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Observation 5a804378-6a18-430d-af2a-2168341fe2cf · outbound

This paper cites Viscoelastic and shear-thinning effects of aqueous exopolymer solution on disk and sphere settling.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Viscoelastic and shear-thinning effects of aqueous exopolymer solution on disk and sphere settling

Reference 20

Resolution: verified exact; doi, observed 2026-08-11T21:47:18.234053Z

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Observation cb5edaa8-40ef-46aa-ada1-10db1b5979dc · outbound

This paper cites Machine learning based microfluidic sensing device for viscosity measurements.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Machine learning based microfluidic sensing device for viscosity measurements

Reference 21

Resolution: verified exact; doi, observed 2026-08-11T21:47:18.218011Z

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Observation 38416726-0175-4cd9-884e-8684e71c0149 · outbound

This paper cites Bidirectional recurrent neural networks.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Bidirectional recurrent neural networks

Reference 23

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Observation cfbacbb4-6cfc-4da0-a117-5886ad307fe8 · outbound

This paper cites Oxford University Press https://doi.org/10.1017/S0022112006213855.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Oxford University Press https://doi.org/10.1017/S0022112006213855

Reference 25

Resolution: verified exact; doi, observed 2026-08-11T21:47:18.157397Z

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Observation 9f181f19-1241-4a50-8421-cd3afd966bce · outbound

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Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Unresolved cited work

Reference 27

Resolution: verified exact; doi, observed 2026-08-11T21:47:18.123649Z

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Observation ac88b95e-e6a3-47e5-9e3e-9637998a944e · outbound

This paper cites Tacotron: Towards End-to-End Speech Synthesis.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Tacotron: Towards End-to-End Speech Synthesis

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T21:47:18.049025Z

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Observation 0d619cfe-c008-4a12-a064-9d7031fc9810 · outbound

This paper cites An On-Chip Viscoelasticity Sensor for Biological Fluids.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics An On-Chip Viscoelasticity Sensor for Biological Fluids

Reference 30

Resolution: verified exact; doi, observed 2026-08-11T21:47:18.094445Z

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Observation 097578ed-8623-4e59-b15f-9a645165a313 · outbound

This paper cites Long Short-Term Memory.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Long Short-Term Memory

Reference 1997

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Observation 2993bd65-9af2-4063-b449-2958b29e700f · outbound

This paper cites Reexamination of Hagen-Poiseuille flow: shape dependence of the hydraulic resistance in microchannels.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Reexamination of Hagen-Poiseuille flow: shape dependence of the hydraulic resistance in microchannels

Reference 2004

Resolution: verified exact; doi, observed 2026-08-11T21:47:18.250794Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dc3631e7-9492-4909-9643-3318884e99b5 · outbound

This paper cites Intrinsic Viscosity of Polymers and Biopolymers Measured by Microchip.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Intrinsic Viscosity of Polymers and Biopolymers Measured by Microchip

Reference 2005

Resolution: verified exact; doi, observed 2026-08-11T21:47:18.298044Z

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Observation c8310cf8-10b8-4f09-a5a7-b4c97490cc36 · outbound

This paper cites Analysis of Non-Newtonian Liquids Using a Microfluidic Capillary Viscometer.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Analysis of Non-Newtonian Liquids Using a Microfluidic Capillary Viscometer

Reference 2006

Resolution: verified exact; doi, observed 2026-08-11T21:47:18.174390Z

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Observation 22ac6226-3166-4271-afdf-8d12a0064c01 · outbound

This paper cites InTech https://doi.org/10.5772/545.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics InTech https://doi.org/10.5772/545

Reference 2010

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Observation cf6afdd3-3548-484b-a2f3-7d19180ca164 · outbound

This paper cites Design of pressure-driven microfluidic networks using electric circuit analogy.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Design of pressure-driven microfluidic networks using electric circuit analogy

Reference 2012

Resolution: verified exact; doi, observed 2026-08-11T21:47:18.201411Z

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Observation 1e264d54-b4af-4ad5-bb4a-6cbc6cfd7369 · outbound

This paper cites Springer US https://doi.org/10.1007/978-3-642-27758-0_1129-4.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Springer US https://doi.org/10.1007/978-3-642-27758-0_1129-4

Reference 2013

Resolution: verified exact; doi, observed 2026-08-11T21:47:18.470034Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c969cca8-9a68-478f-8d93-0dcbad0ab964 · outbound

This paper cites Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-11T21:47:17.925859Z

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Observation ed3e4726-c527-425e-8885-96083aa27398 · outbound

This paper cites Overview on the Gelled Propellants Activities of DLR Lampoldshausen.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Overview on the Gelled Propellants Activities of DLR Lampoldshausen

Reference 2016

Resolution: verified exact; doi, observed 2026-08-11T21:47:18.325241Z

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Observation 9b61fc21-7dda-4768-aaa6-764bad565dc8 · outbound

This paper cites The lattice Boltzmann method.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics The lattice Boltzmann method

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-11T21:47:17.972488Z

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Observation b8a76ef0-c5a3-4d09-9855-57900f717996 · outbound

This paper cites A novel design of flow structure model for online viscosity measurement.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics A novel design of flow structure model for online viscosity measurement

Reference 2019

Resolution: verified exact; doi, observed 2026-08-11T21:47:18.436846Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 216f15f5-bbf6-4bb5-bab4-bf924f37e351 · outbound

This paper cites ASTM International https://doi.org/10.1520/D2196-20.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics ASTM International https://doi.org/10.1520/D2196-20

Reference 2020

Resolution: verified exact; doi, observed 2026-08-11T21:47:18.453340Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 58c4b1b0-e030-430d-aa2f-cef97c91962d · outbound

This paper cites Enhancing Computational Fluid Dynamics with Machine Learning.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Enhancing Computational Fluid Dynamics with Machine Learning

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-11T21:47:18.043513Z

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Observation 5d3274da-2678-4a87-882c-37dbed7d2e88 · outbound

This paper cites A Review of Microfluidic Devices for Rheological Characterisation.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics A Review of Microfluidic Devices for Rheological Characterisation

Reference 2022

Resolution: verified exact; doi, observed 2026-08-11T21:47:18.374899Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 84519d74-d41f-4c70-aead-fc8355d74641 · outbound

This paper cites The 2D microfluidics cookbook – modeling convection and diffusion in plane flow devices.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics The 2D microfluidics cookbook – modeling convection and diffusion in plane flow devices

Reference 2023

Resolution: verified exact; doi, observed 2026-08-11T21:47:18.420746Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e25b9853-d391-4fa3-a056-d8029f140d98 · outbound

This paper cites Accelerated Computational Fluid Dynamics Simulations of Microfluidic Devices by Exploiting Higher Levels of Abstraction.

Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics Accelerated Computational Fluid Dynamics Simulations of Microfluidic Devices by Exploiting Higher Levels of Abstraction

Reference 2024

Resolution: verified exact; doi, observed 2026-08-11T21:47:18.141022Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

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