7 research outputs found
Engineering of microfabricated ion traps and integration of advanced on-chip features
Atomic ions trapped in electromagnetic potentials have long been used for fundamental studies in quantum physics. Over the past two decades, trapped ions have been successfully used to implement technologies such as quantum computing, quantum simulation, atomic clocks, mass spectrometers and quantum sensors. Advanced fabrication techniques, taken from other established or emerging disciplines, are used to create new, reliable ion-trap devices aimed at large-scale integration and compatibility with commercial fabrication. This Technical Review covers the fundamentals of ion trapping before discussing the design of ion traps for the aforementioned applications. We overview the current microfabrication techniques and the various considerations behind the choice of materials and processes. Finally, we discuss current efforts to include advanced, on-chip features in next-generation ion traps
Artificial Neural Network Discovery of a Switchable Metasurface Reflector
Optical materials engineered to dynamically and selectively manipulate electromag- netic waves are essential to the future of modern optical systems. In this paper, we simulate various metasurface configurations consisting of periodic 1D bars or 2D pillars made of the ternary phase change material Ge2Sb2Te5 (GST). Dynamic switching behavior in reflectance is exploited due to a drastic refractive index change between the crystalline and amorphous states of GST. Selectivity in the reflection and transmission spectra is manipulated by tailoring the geometrical parameters of the metasurface. Due to the immense number of possible metasurface configurations, we train deep neural networks capable of exploring all possible designs within the working parameter space. The data requirements, predictive accuracy, and robustness of these neural networks are benchmarked against a ground truth by varying quality and quantity of training data. After ensuring trustworthy neural network advisory, we identify and validate optimal GST metasurface configurations best suited as dynamic switchable mirrors depending on selected light and manufacturing constraints
Triplet Excitation Energy Dynamics in Metal–Organic Frameworks
Metal–organic
frameworks (MOFs) are appealing candidates
for use in energy harvesting and concentrating because of their high
chromophore density and structural tunability. The ability to engineer
electronic excitation energy transport pathways is of particular interest
for designing energy harvesting materials. In this study, theoretical
analysis was performed on energy transfer in MOFs that contain light
absorbing ruthenium complexes that serve as hopping intermediates
for energy transfer kinetics and energy trapping osmium complexes.
We find that the excitation transport kinetics is well described by
a Dexter (exchange) triplet-to-triplet energy transfer mechanism with
multistep incoherent exciton hopping. The modeling combines ab initio
electronic structure theory with kinetic network analysis. The sensitivity
of Dexter mechanism energy transfer to framework structure establishes
different kinds of energy transport paths in the different structures.
For example, the mixed Ru/Os MOF structures described here establish
one or three-dimensional hopping networks. As such, Dexter mechanism
energy harvesting materials may be amenable to designing structures
that can spatially direct exciton energy along specific pathways for
energy delivery to reaction centers