Constructing a Magneto-Optical Trap for Cold Atom Trapping

A magneto-optical trap, or MOT, is a device that traps atoms between three pairs of opposing perpendicular laser beams for cooling the atoms to temperatures near absolute zero. The MOT uses Doppler cooling and a magnetic quadrupole field to trap the atoms; in our case, Rb87 atoms. In the future, the MOT will be used in experiments pertaining to the advancement of quantum computing. In this paper, I explain some of the processes required for construction and operation of the MOT

By how much can closed-loop frameworks accelerate computational materials discovery?

The implementation of automation and machine learning surrogatization within closed-loop computational workflows is an increasingly popular approach to accelerate materials discovery. However, the scale of the speedup associated with this paradigm shift from traditional manual approaches remains an open question. In this work, we rigorously quantify the acceleration from each of the components within a closed-loop framework for material hypothesis evaluation by identifying four distinct sources of speedup: (1) task automation, (2) calculation runtime improvements, (3) sequential learning-driven design space search, and (4) surrogatization of expensive simulations with machine learning models. This is done using a time-keeping ledger to record runs of automated software and corresponding manual computational experiments within the context of electrocatalysis. From a combination of the first three sources of acceleration, we estimate that overall hypothesis evaluation time can be reduced by over 90%, i.e., achieving a speedup of $\sim$$10\times$. Further, by introducing surrogatization into the loop, we estimate that the design time can be reduced by over 95%, i.e., achieving a speedup of $\sim$$15$-$20\times$. Our findings present a clear value proposition for utilizing closed-loop approaches for accelerating materials discovery.Comment: added Supplementary Informatio

Optimization of film morphology for the performance of organic thin film solar cells

The power conversion efficiency of organic thin film solar cells must be improved before they can become commercially competitive alternatives to silicon-based photovoltaics. Exciton diffusion and charge carrier migration in organic films are strongly influenced by film morphology, which can be controlled by the substrate temperature during film growth. Zinc-phthalocyaninelbuckminsterfullerene bilayer film devices are fabricated with substrate temperatures between 25°C and 224°C and their solar cell performance is investigated here. The device open-circuit voltage, efficiency, and fill factor all exhibit peaks when films are grown at temperatures between 160°C and 180°C, which is likely a result of both the increase in shunt resistance and reduction in undesirable back diode effects which occur between l00°C and 180°C. The device performance can also be attributed to changes in the film crystallite size, roughness, and abundance of pinholes, as well as the occurrence of crystalline phase transitions which occur in both zinc-phthalocyanine and buckminsterfullerene between 150°C and 200°C. The unusually high open-circuit voltage (1.2 V), low short-circuit current density (0.03 mA/cm2), and low device efficiency (0.04%) reported here are reminiscent of single layer phthalocyanine-based Schottky solar cells, which suggests that pinholes in bilayer film devices can effectively lead to the formation of Schottky diodes

Application of Multiharmonic QCM-D for Detection of Plasmin at Hydrophobic Surfaces Modified by β-Casein

Plasmin protease plays an important role in many processes in living systems, including milk. Monitoring plasmin activity is important for control of the nutritional quality of milk and other dairy products. We designed a biosensor to detect the proteolytic activity of plasmin, using multiharmonic quartz crystal microbalance with dissipation (QCM-D). The β-casein immobilized on the hydrophobic surface of 1-dodecanethiol on the AT-cut quartz crystal was used to monitor plasmin activity. We demonstrated detection of plasmin in a concentration range of 0.1–20 nM, with the limit of detection about 0.13 ± 0.01 nM. The analysis of viscoelastic properties of the β-casein layer showed rapid changes of shear elasticity modulus, μ, and coefficient of viscosity, η, at plasmin sub-nanomolar concentrations, followed by modest changes at nanomolar concentrations, indicating multilayer architecture β-casein. A comparative analysis of viscoelastic properties of β-casein layers following plasmin and trypsin cleavage showed that the higher effect of trypsin was due to larger potential cleavage sites of β-casein

SMART Transfer Method to Directly Compare the Mechanical Response of Water-Supported and Free-Standing Ultrathin Polymeric Films

Intrinsic mechanical properties of sub-100 nm thin films are markedly difficult to obtain, yet an ever-growing necessity for emerging fields such as soft organic electronics. To complicate matters, the interfacial contribution plays a major role in such thin films and is often unexplored despite supporting substrates being a main component in current metrologies. Here we present the shear motion assisted robust transfer technique for fabricating free-standing sub-100 nm films and measuring their inherent structural–mechanical properties. We compare these results to water-supported measurements, exploring two phenomena: 1) The influence of confinement on mechanics and 2) the role of water on the mechanical properties of hydrophobic films. Upon confinement, polystyrene films exhibit increased strain at failure, and reduced yield stress, while modulus is reduced only for the thinnest 19 nm film. Water measurements demonstrate subtle differences in mechanics which we elucidate using quartz crystal microbalance and neutron reflectometry

Multimodality of Structural, Electrical, and Gravimetric Responses of Intercalated MXenes to Water

Understanding of structural, electrical, and gravimetric peculiarities of water vapor interaction with ion-intercalated MXenes led to design of a multimodal humidity sensor. Neutron scattering coupled to molecular dynamics and <i>ab initio</i> calculations showed that a small amount of hydration results in a significant increase in the spacing between MXene layers in the presence of K and Mg intercalants between the layers. Films of K- and Mg-intercalated MXenes exhibited relative humidity (RH) detection thresholds of ∼0.8% RH and showed monotonic RH response in the 0–85% RH range. We found that MXene gravimetric response to water is 10 times faster than their electrical response, suggesting that H₂O-induced swelling/contraction of channels between MXene sheets results in trapping of H₂O molecules that act as charge-depleting dopants. The results demonstrate the use of MXenes as humidity sensors and infer potential impact of water on structural and electrical performance of MXene-based devices

Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge

The 2019 fastMRI challenge was an open challenge designed to advance research in the field of machine learning for MR image reconstruction. The goal for the participants was to reconstruct undersampled MRI k-space data. The original challenge left an open question as to how well the reconstruction methods will perform in the setting where there is a systematic difference between training and test data. In this work we tested the generalization performance of the submissions with respect to various perturbations, and despite differences in model architecture and training, all of the methods perform very similarly