Please use the following to cite the IDAES project or software

Lee, A., Ghouse, J. H., Eslick, J. C., Laird, C. D., Siirola, J. D., Zamarripa, M. A., Gunter, D., Shinn, J. H., Dowling, A. W., Bhattacharyya, D., Biegler, L. T., Burgard, A. P., Miller, D. C., J Adv Manuf Process 2021, 3( 3), e10095. https://doi.org/10.1002/amp2.10095
Journals and Book Chapters

Qi Chen, IE Grossmann. 2019. “Effective GDP optimization models for modular process synthesis.” Ind. Eng. Chem. Res. Available online. (accepted) (Task 3.1)

Chen, Q. and Grossmann, I.E. “Effective GDP optimization models for modular process synthesis”, Current Opinion in Chemical Engineering. Accepted (2018) (Task 2.7)

ES Rawlings, Qi Chen, IE Grossmann, JA Caballero. 2019. “Kaibel column: Modeling, optimization, and conceptual design of multi-product dividing wall columns.” Comp. Chem. Eng. 125, 31-39. (Task 3.1)

C.O. Okoli, A. Ostace, S. Nadgouda, A. Lee, A. Tong, A.P. Burgard, D. Bhattacharyya, D.C. Miller. 2019. “A framework for the optimization of chemical looping combustion processes.” Powder Technology, https://doi.org/10.1016/j.powtec.2019.04.035 (Task 3.2)

Thierry, D. and Biegler, L. T. (2019), Dynamic real‐time optimization for a CO2 capture process. AIChE J. doi:10.1002/aic.16511 (Task 2.3)

Hanselman, C.L., Tafen, D.Y., Alfonso, D.R., Lekse, J.W., Matranga, C., Miller, D.C., Gounaris, C.E. “Tuning Oxygen Desorption in a Doped BaFe1-xInxO3 Perovskite Oxygen Carrier”, Computers & Chemical Engineering. submitted. (Task 2.4)

David L. Woodruff, Andrea Staid, Bethany Nicholson, and Katherine Klise, “PARMEST: PARAMETER ESTIMATION VIA PYOMO”, submitted to Foundations of Computer Aided Process Design 2019. (Task 3.2.3)

Sitter, S., Chen, Q., and Grossmann, I.E. “An Overview of Process Intensification Methods”, Submitted for publication (2018) (Task 2.7)

Lara, C.L., Mallapragada, D., Papageorgiou D., Venkatesh, A., Grossmann, I.E. “Electric Power Infrastructure Planning: Mixed-Integer Programming Model and Nested Decomposition Algorithm”, European Journal of Operational Research, (2018), In press. (Task 2.8)

Sauk, B., Ploskas, N., Sahinidis, N. (2018). “GPU parameter tuning for tall and skinny dense linear least squares problems,” Optimization Methods and Software. doi:10.1080/10556788.2018.1527331. (Task 3.2.1)

Rodriguez, J.S., Nicholson, B., Laird, C.D., and Zavala, V.M. “Benchmarking ADMM in Nonconvex NLPs”, Computers & Chemical Engineering, accepted (2018) (Task 3.2.3)

Yu, M., D.W. Griffith, and L.T. Biegler, Nonlinear Programming Formulations for Nonlinear and Economic Model Predictive Control, In Handbook of Model Predictive Control, S. Rackovic and W. Levine (eds.), to appear. (in preparation)

D. Miller, J. Siirola, D. Agarwal, A. Burgard, A. Lee, J. Eslick, B. Nicholson, C. Laird, L. Biegler, D. Bhattacharyya, N. Sahinidis, I. Grossmann, C. Gounaris & D. Gunter, “Next Generation Multi-Scale Process Systems Engineering Framework”, Computer Aided Chemical Engineering, 44, 2209-2214 (2018)

Wan, W., J.P. Eason, B. Nicholson, and L.T. Biegler, Parallel Cyclic Reduction Decomposition for DynamicOptimization Problems, Computers and Chemical Engineering, accepted for publication. (2017)

Nicholson, B.L. and J.D. Siirola, A Framework for Modeling and Optimizing Dynamic Systems Under Uncertainty. In press, special FOCAPO/CPC issue of Computers & Chemical Engineering (2017)

Nicholson, B.L., J.D. Siirola, J.-P. Watson, V.M. Zavala, and L.T. Biegler. pyomo.dae: A Modeling and Automatic Discretization Framework for Optimization with Differential and Algebraic Equations, Math Programming Computation (2017)

C.L. Hanselman and C.E. Gounaris. A Mathematical Optimization Framework for the Design of Nanopatterned Surfaces. AIChE Journal, 62(9):3250-3263. (2016)

Conferences and Workshop Proceedings

D. Miller. 2019. “Optimization of materials and processes for advanced energy systems.” American Chemical Society National Meeting & Exposition, Energy & Fuels Division. (Task 1, Task 3.2)

Qi Chen, IE Grossmann. “Economies of Numbers for a Modular Stranded Gas Processing Network: Modeling and Optimization.” FOCAPD. Copper Mountain Resort, CO. Jul. 2019. Paper accepted. (accepted) (Task 3.1)

Qi Chen, S Kale, JL Bates, R Valentin, DE Bernal, M Bynum, J Siirola, IE Grossmann. “Pyosyn: a collaborative ecosystem for process design advancement.” AIChE Annual Meeting, Orlando, FL. Nov. 2018. (submitted) (Task 3.1)

Miller, D.C., J. Siirola, D. Agarwal, A.P. Burgard, A. Lee, J.C. Eslick, B. Nicholson, C. Laird, L.T. Biegler, D. Bhattacharyya, N.V. Sahinidis, I.E. Grossmann, C.E. Gounaris, and D. Gunter, “Next Generation Multi-Scale Process Systems Engineering Framework”, Proceedings of the 13th International Symposium on Process Systems Engineering (PSE 2018), Computer-Aided Chemical Engineering, 44, pp. 2209-2214, Elsevier, Amsterdam, M. R. Eden, M. Ierapetritou and G. P. Towler (eds.) (2018) (Program Summary)

Burgard, A.P., Eason, J.P., Eslick, J.C., Ghouse, J.H., Lee, A., Biegler, L.T., and Miller, D.C. “A Smooth Square Flash Formulation for Equation-Oriented Flowsheet Optimization”, Proceedings of the 13th International Symposium on Process Systems Engineering (PSE 2018), Computer-Aided Chemical Engineering, 44, pp. 871-876, Elsevier, Amsterdam, M. R. Eden, M. Ierapetritou and G. P. Towler (eds.) (2018) (Task 2.2)

Ghouse, J., Eslick, J.C., Burgard, A.P., Lee, A., Zamarripa, M.A., Ma, J., Eason, J.P., Nicholson, B., Laird, C.D., Biegler, L.T., Bhattacharyya, D., and Miller, D.C. “Modeling and Optimization of Supercritical Pulverized Coal Power Plants Under Part Load Operation,” AICHE Annual Meeting, Pittsburgh, PA, October 2018. (Task 2.2)

Eason, J.P., Kang, J., Biegler, L.T., Chen, X “Surrogate Equations of State for Equation-Oriented Optimization of Polymerization Processes”, Proceedings of the 13th International Symposium on Process Systems Engineering (PSE 2018), Computer-Aided Chemical Engineering , 44, pp. 781-786, Elsevier, Amsterdam, M. R. Eden, M. Ierapetritou and G. P. Towler (eds.) (2018) (Task 2.2)

D. M. Thierry, B. L. Nicholson, and L. T. Biegler, “A General Framework for Sensitivity-Based Optimal Control and State Estimation,” Proceedings of the 13th International Symposium on Process Systems Engineering (PSE 2018), Computer-Aided Chemical Engineering , 44, pp. 787-792, Elsevier, Amsterdam, M. R. Eden, M. Ierapetritou and G. P. Towler (eds.) (2018) (Task 2.3/3.1)

Thierry, D., Nicholson, B., and Biegler, L.T. “A Sensitivity-Based Nonlinear Model Predictive Control and State-Estimation Framework in Python,” AICHE Annual Meeting, Pittsburgh, PA, October 2018. (Task 2.3)

C.L. Hanselman, D.N. Tafen, D.R. Alfonso, J.W. Lekse, C. Matranga, D.C. Miller and C.E. Gounaris, “Design of Doped Perovskite Oxygen Carriers Using Mathematical Optimization”, Proceedings of the 13th International Symposium on Process Systems Engineering (PSE 2018), Computer-Aided Chemical Engineering , 44, pp. 2461-2466, Elsevier, Amsterdam, M. R. Eden, M. Ierapetritou and G. P. Towler (eds.) (2018) (Task 2.4)

Hanselman, C.L., Alfonso, D., Lekse, J.W., Tafen, D.N., Matranga, C., Miller, D.C., and Gounaris, C.E. “Identification of Optimal Dopant Patterns in a Doped Perovskite Oxygen Carrier,” AICHE Annual Meeting, Pittsburgh, PA, October 2018. (Task 2.4)

Wilson, Z.T., Sahinidis, N.V. “ALAMO: Machine Learning from first Principles”, AIChE Process Development Symposium, Chicago, IL, June 2018 (Task 2.5)

Engle, M. and Sahinidis, N. “Constrained Subset Selection for the Regression of Multi-Component Helmholtz Energy Equations,” AICHE Annual Meeting, Pittsburgh, PA, October 2018. (Task 2.5)

Engle, M. and Sahinidis, N. “Symbolic Regression of Alpha Functions for Cubic Equations of State,” AICHE Annual Meeting, Pittsburgh, PA, October 2018. (Task 2.5)

Wilson, Z. and Sahinidis, N. “Data Driven Modeling in Alamo: Feature Selection and Non-Parametric Modeling Applications,” AICHE Annual Meeting, Pittsburgh, PA, October 2018. (Task 2.5)

Eslick, John C., P.T. Akula, Debangsu Bhattacharyya, David C. Miller, “Simultaneous Parameter Estimation in Reactive-Solvent-Based Processes”, Proceedings of the 13th International Symposium on Process Systems Engineering (PSE 2018), Computer-Aided Chemical Engineering , 44, pp. 901-906, Elsevier, Amsterdam, M. R. Eden, M. Ierapetritou and G. P. Towler (eds.) (2018) (Task 2.6)

Akula, P., Eslick, J.C., Bhattacharyya, D., and Miller, D.C. “Multi-Scale Simultaneous Parameter Estimation in Rate-Based Processes,” AICHE Annual Meeting, Pittsburgh, PA, October 2018. (Task 2.6)

Chen, Q., E. Johnson, J.D. Siirola, I.E. Grossmann, “Pyomo.GDP: Disjunctive Models in Python,” Proceedings of the 13th International Symposium on Process Systems Engineering (PSE 2018), Computer-Aided Chemical Engineering , 44, pp. 889-894, Elsevier, Amsterdam, M. R. Eden, M. Ierapetritou and G. P. Towler (eds.) (2018) (Task 2.7)

Chen, Q., Grossmann, I.E. “Pyomo.GDP: An Integrated Ecosystem for Generalized Disjunctive Programming Modeling and Optimization,” accepted to INFORMS Annual Meeting, Phoenix, AZ, November 2018. (Task 2.7)

Chen, Q. and Grossmann, I.E. “Effective Generalized Disjunctive Programming (GDP) Models for Modular Plant Design,” AICHE Annual Meeting, Pittsburgh, PA, October 2018. (Task 2.7)

Lara, C.L., Omell, B., Miller, D., Grossmann, I. E. “Expanding the Scope of Electric Power Infrastructure Planning”, Proceedings of the 13th International Symposium on Process Systems Engineering (PSE 2018), Computer-Aided Chemical Engineering , 44, pp. 1309-1314, Elsevier, Amsterdam, M. R. Eden, M. Ierapetritou and G. P. Towler (eds.) (2018) (Task 2.8)

Lara, C.L., Omell, B.P., Miller, D.C., and Grossmann, I.E. “Stochastic Programming Framework for Electric Power Infrastructure Planning,” AICHE Annual Meeting, Pittsburgh, PA, October 2018. (Task 2.8)

Lee, A., J.H. Ghouse, Q. Chen, J.C. Eslick, J.D. Siirola, I.E. Grossmann, and D.C. Miller. “A Flexible Framework and Model Library for Process Simulation, Optimization, and Control”, Proceedings of the 13th International Symposium on Process Systems Engineering (PSE 2018), Computer-Aided Chemical Engineering , 44, pp. 937-942, Elsevier, Amsterdam, M. R. Eden, M. Ierapetritou and G. P. Towler (eds.) (2018) (Task 2.9)

Siirola, J.D. Power Systems, Process Systems, and Equation-Oriented Optimization. Samuel Ginn College of Engineering Chemical Engineering Distinguished Seminar Series. Auburn University. March 2018. (Task 2.7/2.8/3.1)

J. Siirola., “The IDAES Framework: Process Modeling and Optimization in Pyomo”, INFORMS Annual Meeting, Phoenix, AZ, November 2018. (Task 2.7/2.8/3.1)

Rodriguez, J. S., Nicholson, B. L., Siirola, J. D., Laird, C. D., “PyNumero: Python Numerical Optimization”, AIChE Annual Meeting, Pittsburgh, PA, October, 2018 (Task 3.1)

Nicholson, B. L., Siirola, J. D., “Pyomo.DAE: A Framework for Modeling and Solving Dynamic Optimization Problems”, INFORMS Annual Meeting, Phoenix, AZ, November, 2018 (Task 3.1)

Sauk, B. and Sahinidis, N. “Accelerating the Generation of Coal Power Plant Property Models,” AICHE Annual Meeting, Pittsburgh, PA, October 2018. (Task 3.2.1)

Sauk, B. and Sahinidis, N. “Autotuning with Derivative-Free Optimization,” AICHE Annual Meeting, Pittsburgh, PA, October 2018. (Task 3.2.1)

Klise, K., Laird, C.D., Nicholson, B., Staid, A. and Woodruff, D., “Parameter Estimation, Uncertainty Quantification, and Scenarios”, Proceedings of the 13th International Symposium on Process Systems Engineering (PSE 2018), Computer-Aided Chemical Engineering , 44, pp. 1531-1536, Elsevier, Amsterdam, M. R. Eden, M. Ierapetritou and G. P. Towler (eds.) (2018) (Task 3.2.3)

Rodriguez, J.S., Nicholson, B., Zavala, V., and Laird, C.D., “Parallel Decomposition On Nonconvex Time-discretized Systems”, INFORMS Optimization 2018, Denver, CO, USA, March, 2018. (Task 3.2.3)

Siirola, J.D., Rodriguez, J.S., Nicholson, B., Zavala, V., and Laird, C.D., “Parallel Schur-complement and ADMM Decomposition Strategies for Dynamic Optimization Problems”, DIMACS Workshop on ADMM and Proximal Slitting Methods in Optimization, 2018, Rutgers University, Piscataway, NJ, USA, July, 2018. (Task 3.2.3)

Ostace, A., Lee, A., Okoli, C. O., Burgard, A. P., Miller, D. C., and Bhattacharyya, D., “Mathematical Modeling of a Moving-Bed Reactor for Chemical Looping Combustion of Methane”, Proceedings of the 13th International Symposium on Process Systems Engineering (PSE 2018), Computer-Aided Chemical Engineering , 44, pp. 325-330, Elsevier, Amsterdam, M. R. Eden, M. Ierapetritou and G. P. Towler (eds.) (2018) (Task 4.1)

Okoli, C.O., Lee, A., Burgard, A.P., and Miller, D.C., “A Fluidized Bed Process Model of a Chemical Looping Combustion Fuel Reactor”, Proceedings of the 13th International Symposium on Process Systems Engineering (PSE 2018), Computer-Aided Chemical Engineering , 44, pp. 325-330, Elsevier, Amsterdam, M. R. Eden, M. Ierapetritou and G. P. Towler (eds.) (2018) (Task 4.1)

Okoli, C.O., Lee, A., Burgard, A.P., and Miller D.C. “Development of a One-Dimensional Bubbling Fluidized Bed Model for a Coal-Fed Chemical Looping Combustion Fuel Reactor,” AICHE Annual Meeting, Pittsburgh, PA, October 2018. (Task 4.1)

Ostace, A., Okoli, C.O., Lee, A., Burgard, A.P., Bhattacharyya, D., and Miller, D.C. “Optimal Design of Gas-Fired Moving-Bed Chemical Looping Combustion Systems,” AICHE Annual Meeting, Pittsburgh, PA, October 2018. (Task 4.1)

Yu, M. and L.T. Biegler, Economic NMPC Strategies for Solid Sorbent-Based CO2 Capture, conference paper submitted to ADCHEM 2018, Shenyang, China. (Task 2.3)

Staid, Andrea and David L. Woodruff, Software for Creating Stochastic Scenarios for Optimization from Data, Process Systems Engineering, San Diego, CA, July 2018. (in preparation)

Wan, W., J. P. Eason, B. L. Nicholson, L. T. Biegler, Parallel Cyclic Reduction Decomposition for Dynamic Optimization Problems, Paper 599f presented at Annual AIChE Meeting, Minneapolis, MN, November, 2017.

Eason, J.P., Y. Ma, X. Chen, and L.T. Biegler, Dynamic Optimization of Polymerization Processes with Detailed Molecular Weight Distributions, Paper 599g presented at Annual AIChE Meeting, Minneapolis, MN, November, 2017.

Theirry, D.M., Fast-Nonlinear Model Predictive Control Implementation with Open-Source Tools, Paper 756e presented at Annual AIChE Meeting, Minneapolis, MN, November, 2017.

Engle, Marissa; Sahinidis, N. V., Constrained Best Subset Selection Methodology for the Regression of Helmholtz Energy, presented at Annual AIChE Meeting, Minneapolis, MN, November, 2017.

Wilson, Z. and N. V. Sahinidis, Reaction identification and parameter estimation from chemical process data, presented at Annual AIChE Meeting, Minneapolis, MN, November, 2017.

Nicholson, B. L. and Siirola, J. D., A Framework for Modeling and Optimizing Complex Structured Problems, presented at Annual AIChE Meeting, Minneapolis, MN, November, 2017.

Siirola, J.D., W.E. Hart, C.D. Laird, B.L. Nicholson, Q. Chen, and G. Seastream, Recent Developments in Pyomo, presented at Annual AIChE Meeting, Minneapolis, MN, November, 2017.

Sauk, B., N. Ploskas and N. V. Sahinidis, GPU parameter tuning for dense linear least squares problems, presented at Annual AIChE Meeting, Minneapolis, MN, November, 2017.

Hart, W., An Overview of Recent Advances in Pyomo, INFORMS Annual Meeting, Nov 25, 2017.

C.L. Hanselman and C.E. Gounaris (2017, Nov 2). Design of Metallic Surface Nanostructures Using Mathematical Optimization. At: 2017 American Institute of Chemical Engineers Annual Meeting, AIChE-2017, 29 October-3 November, Minneapolis, MN, USA

C.L. Hanselman, D. Alfonso, J.W. Lekse, D.N. Tafen, C. Matranga, D.C. Miller and C.E. Gounaris (2017, Oct 29). Designing Dopant Patterns in Indium-Doped Perovskite Oxygen Carriers. At: 2017 American Institute of Chemical Engineers Annual Meeting, AIChE-2017, 29 October-3 November, Minneapolis, MN, USA

C.L. Hanselman and C.E. Gounaris (2016, Nov 18). Rational Design of Nanostructured Metallic Surfaces Via Mathematical Optimization. At: 2016 American Institute of Chemical Engineers Annual Meeting, AIChE-2016, 13-18 November, San Francisco, CA, USA

C.L. Hanselman and C.E. Gounaris (2016, Nov 15). A Mixed-Integer Linear Programming Approach for the Design of Nanostructured Catalysts. At: 2016 American Institute of Chemical Engineers Annual Meeting, AIChE-2016, 13-18 November, San Francisco, CA, USA