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@article{Yong2023,

title = {Thermal Protection of Piezoelectric Actuators Using Complex Electrical Power Measurements and Simplified Thermal Models},

author = {Y. K. Yong and A. A. Eielsen and A. J. Fleming},

doi = {10.1109/TMECH.2023.3277437},

year  = {2023},

date = {2023-06-05},

urldate = {2023-06-05},

journal = {IEEE/ASME Transactions on Mechatronics (Early Access)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Xavier2023,

title = {Modeling of soft fluidic actuators using fluid-structure interaction simulations with underwater applications},

author = {M. S. Xavier and S. Harrison and D. Howard and Y. K. Yong and A. J. Fleming},

url = {https://www.precisionmechatronicslab.com/wp-content/uploads/2023/06/FSI.pdf},

doi = {https://doi.org/10.1016/j.ijmecsci.2023.108437},

year  = {2023},

date = {2023-05-15},

urldate = {2023-05-15},

journal = {International Journal of Mechanical Sciences},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Single-Walled Carbon Nanotubes as One-Dimensional Scattering Surfaces for Measuring Point Spread Functions and Performance of Tip-Enhanced Raman Spectroscopy Probes},

author = {L. R. McCourt and B. S. Routley and M. G. Ruppert and V. J. Keast and C. I. Sathish and R. Borah and R. V. Goreham and A. J. Fleming},

url = {https://www.precisionmechatronicslab.com/wp-content/uploads/2023/02/J22i.pdf},

doi = {10.1021/acsanm.2c01274},

issn = {2574-0970},

year  = {2022},

date = {2022-06-21},

urldate = {2022-06-21},

journal = {ACS Applied Nano Materials},

volume = {5},

issue = {7},

pages = {9024-9033},

abstract = {This Article describes a method for the characterization of the imaging performance of tip-enhanced Raman spectroscopy probes. The proposed method identifies single-walled carbon nanotubes that are suitable as one-dimensional Raman scattering objects by using atomic force microscope maps and exciting the radial breathing mode using 785 nm illumination. High-resolution cross sections of the nanotubes are collected, and the point spread functions are calculated along with the optical contrast and spot diameter. The method is used to characterize several probes, which results in a set of imaging recommendations and a summary of limitations for each probe. Elemental analysis and boundary element simulations are used to explain the formation of multiple peaks in the point spread functions as a consequence of random grain formation on the probe surface.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ragazzon2022,

title = {The Generalized Lyapunov Demodulator: High-Bandwidth, Low-Noise Amplitude and Phase Estimation},

author = {M. R. P. Ragazzon and S. Messineo and J. T. Gravdahl and D. M. Harcombe and M. G. Ruppert},

doi = {10.1109/OJCSYS.2022.3181111},

year  = {2022},

date = {2022-06-08},

urldate = {2022-06-08},

journal = {IEEE Open Journal of Control Systems},

abstract = {Effective demodulation of amplitude and phase is a requirement in a wide array of applications. Recent efforts have increased the demodulation performance, in particular, the Lyapunov demodulator allows bandwidths up to the carrier frequency of the signal. However, being inherently restricted to first-order filtering of the input signal, it is highly sensitive to frequency components outside its passband region. This makes it unsuitable for certain applications such as multifrequency atomic force microscopy (AFM). In this article, the structure of the Lyapunov demodulator is transformed to an equivalent form and generalized by exploiting the internal model principle. The resulting generalized Lyapunov demodulator structure allows for arbitrary filtering order and is easy to implement, requiring only a bandpass filter, a single integrator, and two nonlinear transformations. The generalized Lyapunov demodulator is implemented experimentally on a field-programmable gate array (FPGA). Then it is used for imaging in an AFM and benchmarked against the standard Lyapunov demodulator and the widely used lock-in amplifier. The lock-in amplifier achieves great noise attenuation capabilities and off-mode rejection at low bandwidths, whereas the standard Lyapunov demodulator is shown to be effective at high bandwidths. We demonstrate that the proposed demodulator combines the best from the two state-of-the-art demodulators, demonstrating high bandwidths, large off-mode rejection, and excellent noise attenuation simultaneously.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{J22h,

title = {Soft Pneumatic Actuators: A Review of Design, Fabrication, Modeling, Sensing, Control and Applications},

author = {M. S. Xavier and C. D. Tawk and A. Zolfagharian and J. Pinskier and D. Howard and T. Young and J. Lai and S. Harrison and Y. K. Yong and M. Bodaghi and A. J. Fleming},

url = {https://www.precisionmechatronicslab.com/wp-content/uploads/2023/02/J22h-1.pdf},

doi = {10.1109/ACCESS.2022.3179589},

issn = {2169-3536},

year  = {2022},

date = {2022-06-02},

urldate = {2022-06-02},

journal = {IEEE Access},

volume = {10},

pages = {59442-59485},

abstract = {Soft robotics is a rapidly evolving field where robots are fabricated using highly deformable materials and usually follow a bioinspired design. Their high dexterity and safety makes them ideal for applications such as gripping, locomotion, and biomedical devices, where the environment is highly dynamic and sensitive to physical interaction. Pneumatic actuation remains the dominant technology in soft robotics due to its low cost and mass, fast response time, and easy implementation. Given the significant number of publications in soft robotics over recent years, newcomers and even established researchers may have difficulty assessing the state of the art. To address this issue, this article summarizes the development of soft pneumatic actuators and robots up until the date of publication. The scope of this article includes the design, modeling, fabrication, actuation, characterization, sensing, control, and applications of soft robotic devices. In addition to a historical overview, there is a special emphasis on recent advances such as novel designs, differential simulators, analytical and numerical modeling methods, topology optimization, data-driven modeling and control methods, hardware control boards, and nonlinear estimation and control techniques. Finally, the capabilities and limitations of soft pneumatic actuators and robots are discussed and directions for future research are identified.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{J22g,

title = {Memory efficient constrained optimization of scanning-beam lithography},

author = {C. Jidling and A. J. Fleming and A. G. Wills and T. B. Schon},

url = {https://www.precisionmechatronicslab.com/wp-content/uploads/2022/05/J22g.pdf},

doi = {10.1364/OE.457334},

issn = {1094-4087},

year  = {2022},

date = {2022-06-01},

journal = {Optics Express},

volume = {30},

number = {12},

pages = {20564--20579},

abstract = {This article describes a memory efficient method for solving large-scale optimization problems that arise when planning scanning-beam lithography processes. These processes require the identification of an exposure pattern that minimizes the difference between a desired and predicted output image, subject to constraints. The number of free variables is equal to the number of pixels, which can be on the order of millions or billions in practical applications. The proposed method splits the problem domain into a number of smaller overlapping subdomains with constrained boundary conditions, which are then solved sequentially using a constrained gradient search method (L-BFGS-B). Computational time is reduced by exploiting natural sparsity in the problem and employing the fast Fourier transform for efficient gradient calculation. When it comes to the trade-off between memory usage and computational time we can make a different trade-off compared to previous methods, where the required memory is reduced by approximately the number of subdomains at the cost of more computations. In an example problem with 30 million variables, the proposed method reduces memory requirements by 67%; but increases computation time by 27%. Variations of the proposed method are expected to find applications in the planning of processes such as scanning laser lithography, scanning electron beam lithography, and focused ion beam deposition, for example.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}