@article{J19e,

title = {Scanning Laser Lithography with Constrained Quadratic Exposure Optimization},

author = {A. J. Fleming and O. T. Ghalehbeygi and B. S. Routley and A. G. Wills},

url = {http://www.precisionmechatronicslab.com/wp-content/uploads/2020/02/J19e.pdf},

doi = {10.1109/TCST.2018.2836910},

isbn = {1063-6536},

year  = {2019},

date = {2019-09-01},

journal = {IEEE Transactions on Control Systems Technology},

volume = {27},

number = {5},

pages = {2221-2228},

abstract = {Scanning laser lithography is a maskless lithography method for selectively exposing features on a film of photoresist. A set of exposure positions and beam energies are required to optimally reproduce the desired feature pattern. The task of determining the exposure energies is inherently non-linear due to the photoresist model and the requirement for only positive energy. In this article, a nonlinear programming approach is employed to find an optimal exposure profile that minimizes the feature error and total exposure energy. This method is demonstrated experimentally to create a features with sub-wavelength geometry.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{J17j,

title = {Gradient-based optimization for efficient exposure planning in maskless lithography},

author = {O. T. Ghalehbeygi and A. G. Wills and B. S. Routley and A. J. Fleming},

url = {http://www.precisionmechatronicslab.com/wp-content/uploads/2017/09/J17j.pdf},

doi = {10.1117/1.JMM.16.3.033507},

year  = {2017},

date = {2017-09-01},

journal = {Journal of  Micro/Nanolithography, MEMS, and MOEMS},

volume = {16},

number = {3},

pages = {033507},

abstract = {Scanning laser lithography is a maskless method for exposing photoresist during semiconductor manufacturing. In this method, the energy of a focused beam is controlled while scanning the beam or substrate. With a positive photoresist material, areas that receive an exposure dosage over the threshold energy are dissolved during development. The surface dosage is related to the exposure profile by a convolution and nonlinear function, so the optimal exposure profile is nontrivial. A gradient-based optimization method for determining an optimal exposure profile, given the desired pattern and models of the beam profile and photochemistry, is described. This approach is more numerically efficient than optimal barrier-function-based methods but provides near-identical results. This is demonstrated through simulation and experimental lithography},

keywords = {},

pubstate = {published},

tppubtype = {article}

}