Launch week offerEnds in00h00m00s

annual Promonthly Pro

Xiaonan Lu

Pacific Northwest National Laboratory

United States

Research Interests

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Explore related searches

Articles (20)

Collaborators (6)

Jim Neeway

Pacific Northwest National Laboratory

UNITED STATES

Xiaonan Lu

McGill University

John Hedengren

Brigham Young University

UNITED STATES

Joelle Reiser

Pacific Northwest National Laboratory

UNITED STATES

Jincheng Du

University of North Texas

UNITED STATES

Morten M. Smedskjaer

Aalborg University

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Xiaonan Lu

Research Interests

Make your next move.

Explore related searches

Articles (20)

Collaborators (6)

Jim Neeway

Xiaonan Lu

John Hedengren

Joelle Reiser

Jincheng Du

Morten M. Smedskjaer

Make your next move.

Xiaonan Lu

Research Interests

Make your next move.

Explore related searches

Articles (20)

Boron Coordination in Multicomponent Glasses: Analytical Models and Machine Learning With Uncertainty

Impact of crystalline phases on low-activity waste glass durability: Insights from PCT and VHT

Predicting Nepheline Formation in Nuclear Waste Glasses Using Machine Learning With Uncertainty Quantification

Leveraging Inequality‐Constrained Data for Enhanced Liquidus Temperature Prediction in Nuclear Waste Glass Melts

Low activity waste glass optimization with property models from machine learning, part 2: Experimental validation and active learning

Glass-Bonded Monazite Waste Forms for Lanthanide and Actinide Immobilization: From Theoretical Design to Scale-Up Production and Characterization

Structure–property relations of sodium iron phosphate nuclear waste glasses: Effects of iron redox ratio and glass composition

Liquidus temperature of phosphate crystalline phases in borosilicate waste glasses

Uncertainty propagation and sensitivity analysis for constrained optimization of nuclear waste vitrification

Organic Acid-Assisted Thermal Dehalogenation of Halide Salt Nuclear Wastes: From Waste Salts to Borosilicate Glass

Revealing the Structure–Property Relationships of Nd2O3-Containing Alkali Iron Phosphate Glasses from Molecular Dynamics Simulations

Unveiling the effect of composition on nuclear waste immobilization glasses’ durability by nonparametric machine learning

Evaluation of GlassNet for physics‐informed machine learning of glass stability and glass‐forming ability

Insights on the structure and properties of sodium iron phosphate glasses from molecular dynamics simulations

Glass design using machine learning property models with prediction uncertainties: Nuclear waste glass formulation

Structure and structure-property relationships in sodium iron phosphate glasses from molecular dynamics simulations and QSPR analysis

Synthesis and properties of anhydrous rare-earth phosphates, monazite and xenotime: a review

Temperature and composition dependence modeling of viscosity and electrical conductivity of low-activity waste glass melts

Towards informatics-driven design of nuclear waste forms

Glass formulation and composition optimization with property models: A review

Collaborators (6)

Jim Neeway

Xiaonan Lu

John Hedengren

Joelle Reiser

Jincheng Du

Morten M. Smedskjaer

Make your next move.