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  2. Slide 1

    www.tcm.phy.cam.ac.uk/~gjc29/talks/NIMSTalk2022.pdf
    4 Sep 2022: Yield stress at 900˚C > 200 MPaTensile strength at 900˚C > 300 MPa. ... γ’ solvus > 1000˚CThermal resistance > 0.04 KΩ-1m-3. Yield stress at 900˚C > 200 MPaTensile strength at 900˚C > 300 MPa.
  3. Slide 1

    www.tcm.phy.cam.ac.uk/~gjc29/talks/RadiologyTalk2022.pdf
    7 Mar 2022: γ’ solvus > 1000˚CThermal resistance > 0.04 KΩ-1m-3. Yield stress at 900˚C > 200 MPaTensile strength at 900˚C > 300 MPa. ... Yield stress at 900˚C > 200 MPaTensile strength at 900˚C > 300 MPa.
  4. Slide 1

    www.tcm.phy.cam.ac.uk/~gjc29/talks/TCMCurrentResearchTalk2022.pdf
    14 Mar 2022: γ’ solvus > 1000˚C. Thermal resistance > 0.04 KΩ-1m-3. Yield stress at 900˚C > 200 MPa.
  5. Slide 1

    www.tcm.phy.cam.ac.uk/~gjc29/talks/GrapheneCentreTalk2022.pdf
    13 May 2022: γ’ solvus > 1000˚CThermal resistance > 0.04 KΩ-1m-3. Yield stress at 900˚C > 200 MPaTensile strength at 900˚C > 300 MPa. ... Yield stress at 900˚C > 200 MPaTensile strength at 900˚C > 300 MPa.
  6. Slide 1

    www.tcm.phy.cam.ac.uk/~gjc29/talks/CambridgePresentationTalk2022.pdf
    13 Oct 2022: γ’ solvus > 1000˚CThermal resistance > 0.04 KΩ-1m-3. Yield stress at 900˚C > 200 MPaTensile strength at 900˚C > 300 MPa.
  7. Slide 1

    www.tcm.phy.cam.ac.uk/~gjc29/talks/LoughboroughTalk2022.pdf
    27 Jan 2022: γ’ solvus > 1000˚CThermal resistance > 0.04 KΩ-1m-3. Yield stress at 900˚C > 200 MPaTensile strength at 900˚C > 300 MPa.
  8. Slide 1

    www.tcm.phy.cam.ac.uk/~gjc29/talks/HPCAutumnAcademyTalk2022.pdf
    15 Sep 2022: γ’ solvus > 1000˚CThermal resistance > 0.04 KΩ-1m-3. Yield stress at 900˚C > 200 MPaTensile strength at 900˚C > 300 MPa.
  9. 21 Nov 2022: There arecurrently more than 200 compounds in Series 4, with in vitropotencies against P. ... 58% runner-up. Slade Matthews (TheUniversity of Sydney). Random forest model using 200 mordred descriptors based on optimized 3D structures.
  10. 21 Nov 2022: Inboth cases, Alchemite used an ensemble of 200 sub-learnerstrained on random subsets of the available training data, withthe resulting prediction being the average of the ensemble’spredictions and the
  11. sustainable handout.dvi

    www.tcm.phy.cam.ac.uk/~jsb56/resources/sustainablehandout.pdf
    24 Oct 2022: Temperature. Depth. 40 km. 100–200 km. crust. mantle1400 C. 500–600 C.
  12. 1 Prediction of In Vivo Pharmacokinetic Parameters and Time–Exposure…

    www.tcm.phy.cam.ac.uk/~gjc29/papers/ObrezanovaGreene22.pdf
    15 Apr 2022: pharmacokinetic curves directly. In both cases Alchemite used an ensemble of 200 sub-learners.
  13. DCE_2200031 1..23

    www.tcm.phy.cam.ac.uk/~gjc29/papers/MarkandayConduitConduitPurstlChristofidouChechikBaxterHeasonStone22.pdf
    11 Oct 2022: RESEARCH ARTICLE. Design of a Ni-based superalloy for laser repair applicationsusing probabilistic neural network identification. Freddie Markanday1, Gareth Conduit2, Bryce Conduit3, Julia Pürstl1, Katerina Christofidou4 ,Lova Chechik4 , Gavin
  14. Oscillating Systems Natural SciencesPhysics Part 1A J. S. Biggins ...

    www.tcm.phy.cam.ac.uk/~jsb56/resources/oschandout.pdf
    24 Oct 2022: Oscillating Systems. Natural SciencesPhysics Part 1A. J. S. Biggins. Cavendish LaboratoryUniversity of Cambridge. Michaelmas 2014. CONTENTS CONTENTS. Contents. 1 Course Details vi1.1 Synopsis. vi1.2 Resources. vi1.3 Practicalities. vii. 2
  15. thesisforsending.dvi

    www.tcm.phy.cam.ac.uk/~jsb56/resources/thesis.pdf
    24 Oct 2022: S O FT AND HARD E L AS T I C I T Y O F. L I Q UI D C RYS T AL E L AS T O ME RS. S O F T A N D H A R D E L A S T I C I T Y O F. L I Q U I D C R Y S T A L E L A S T O M E R S. John Simeon Biggins. corpus christi college. university of cambridge. a

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