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The production and use of semiconducting nanopost arrays made by nanofabrication is described herein. These nanopost arrays (NAPA) provide improved laser ionization yields and controllable fragmentation with switching or modulation capabilities for mass spectrometric detection and identification of samples deposited on them.
A product having at least one plasma lamp that includes plates that are approximately parallel, with at least one array of microcavities formed in a surface of at least one plate. When desirable, the plates are separated a fixed distance by spacers with at least one spacer being placed near the plate's edge to form a hermetic seal therewith. A gas makes contact with the microcavity array. Electrodes capable of delivering a time-varying voltage are located such that the application of the time-varying voltage interacts with the gas to form a glow discharge plasma in the microcavities and the fixed volume between the plates. The glow discharge plasma efficiently and uniformly emits radiation that is predominantly in the UV/VUV spectral range with at least a portion of the radiation being emitted from the plasma lamp.
The NREL Python Panel-Segmentation package is a toolkit that automates the process of extracting accurate and valuable metadata related to solar array installations, using publicly available Google Maps satellite imagery. Previously published work includes automated azimuth estimation for individual solar installations in satellite images. Our continued research focuses on automated detection and classification of solar installation mounting configuration (tracking or fixed-tilt; rooftop, ground, or carport). Specifically, a Faster-RCNN Resnet-50 feature pyramid network (FPN) model was trained and validated on 862 manually labeled satellite images. This model was used to perform object detection on satellite imagery, locating and classifying individual solar installations' mounting configuration and type. Model results showed a mean average precision score (mAP) of 77.79%, with the model strongest at detecting fixed-tilt ground mount and fixed-tilt carport installations. The object detection model and its outputs have been incorporated into the Panel-Segmentation package's automated metadata extraction pipeline, which returns the mounting configuration and azimuth for individual solar arrays in satellite imagery. The complete image data set with labels has been released on the U.S. Department of Energy (DOE) DuraMAT DataHub, to encourage further research in this area.
A cylindrical microelectrode array having an elongated cylindrical core, and a multilayer structure conformally folded around and affixed to the cylindrical core so as to extend between opposite ends of the core. The multilayer structure has integrated sections including an electrode section with electrodes exposed through electrically insulating layers, a connector section with conductive bond pads for interfacing with external electronics, and a cable section with conductive traces encapsulated in electrically insulating layers and which connect between the electrodes and their corresponding bond pads. The array may be fabricated using a planar multilayer structure having the electrode, connector, and cable sections, and conformally folding the multilayer structure around and affixing to the cylindrical core. The cable section in particular may be conformally coiled around and affixed to the cylindrical core so that the electrical conduits helically extend between the connector and electrode sections.
Substrates are disclosed that include an embedded or partially-embedded microlens array. Devices are disclosed that include an OLED disposed over a substrate having an embedded or partially embedded micro lens array. Devices as disclosed herein redirect up to 100% of the light that otherwise would be confined in organic and electrode layers toward the substrate and thus provide improved light extraction and device efficiency.
Stretchable electrical interconnects and substrate materials are increasingly used to create flexible and con-formable electronic systems for soft robotics, smart textiles, and wearable devices. Wires fabricated using composite or liquid conductive inks encapsulated in silicone enable high strain and are mechanically robust. The resistance of these inter-connects increases with strain, which can present challenges for power delivery and signaling among electronic components. However, this effect can be used directly to estimate strain within a stretchable circuit without the need for additional sensor components. In this work, we present an approach for fabricating fully-stretchable, multi-layer active circuit arrays in silicone using liquid metal paste interconnects, in which power and data wires are re-purposed as strain sensors to estimate substrate deformation. As a proof-of-principle, we demonstrate a 3×3 active circuit array that self-senses relative voltage supply at each node to estimate deformation and consumes less than 10 mA per node. Each node is digitally addressable and performs both analog measurement and digital conversion. All interconnects are fabricated using liquid metal paste, and power, data, and sensing are performed over a shared, four-wire interface in this multi-layer stretchable printed circuit board.
One of the biggest challenges for all renewable energy sources (RES) is that they are variable power generators which will require reactive power or energy storage systems (ESS) to provide reliable power quality (ideally power factor of one) at the power grid generation side. The present invention is directed to a power packet network (PPN) for integrating wave energy converter (WEC) arrays into microgrids. Specifically, an array of WECs can be physically positioned such that the incoming regular waves will produce an output emulating an N-phase AC system such that the PPN output power is constant. ESS requirements are thereby minimized whilst maintaining grid stability with high power quality. This will enable RES integration onto a future smart grid for large-scale adoption and cost reduction while preserving high efficiency, reliability, and resiliency.
Capabilities for modeling the effects of seabed bathymetry and current drag loads on a floating wind farm are now available in an open-source model for quasi-static analysis. In this model, mooring lines and dynamic cables are represented by a quasistatic solver that can quickly represent complex mooring/cabling arrangements and arrays of floating bodies. To account for seabed bathymetry, we expand the model to include a surface mesh that captures changes in water depth over a rectangular grid. We formulate modifications to the catenary equations that capture a mooring line's profile and tensions when contacting a slope seabed. To account for current drag loads on mooring lines and dynamic cables, we formulate a novel technique that rotates the reference frame so that the vector sum of the the weight and the current force are used in the catenary equations, while accounting for the seabed orientation. To complete the system, current drag loads on floating substructures are handled by inclusion of strip-theory drag calculations. These new capabilities are verified by comparing with results from the established offshore dynamics models MoorDyn and OrcaFlex in equivalent steady-state scenarios. The results show very good agreement for both sloped seabeds and current loads. With computation times of the quasi-static model typically under one second, the model additions are a useful capability toward rapidly evaluating a floating wind array's response to environmental loads under realistic site conditions.
The present disclosure relates to a thermal emissivity control system. The system may have a segmented array that makes use of a thermally conductive base layer configured to be connectable to an external heat generating subsystem, with the base layer including a thermally emissive surface. The array may also have a plurality of actuation elements at least one of positioned on or adjacent to the thermally emissive surface. A plurality of movable shutter elements is disposed adjacent one another in a grid pattern, and controlled in movement by the actuation elements to create gaps of controllably varying dimension therebetween. The shutter elements control at least one of a magnitude of, or direction of, thermal radiation through the gaps.
A metalens array is disclosed for controllably modifying a phase of a wavefront of an optical beam. The metalens array may have a substrate having at least first and second metalens unit cells, and forming a single integrated structure with no stitching being required of the first and second metalens unit cells. The first metalens unit cell has a first plurality of nanoscale features and is configured to modify a phase of a first portion of a wavefront of an optical signal incident thereon in accordance with a first predetermined phase pattern to create at least one first focal voxel within an image plane. The second metalens unit cell has a second plurality of nanoscale features configured to modify the phase of a second portion of the wavefront of the optical signal incident thereon, in accordance with a second predetermined phase pattern, to simultaneously create at least one second focal voxel within the image plane. Each metalens unit cell also has an overall diameter of no more than about 200 microns.
We present a 3D-printed millimeter-wave, octave-bandwidth, in-line waveguide-to-coplanar-waveguide transition designed to enable focal planes with dense arrays of on-chip spectrometers. These arrays will enable compelling surveys of the large-scale structure of the universe through millimeter-wave intensity mapping. The transition consists of a four-step ridge-waveguide transformer that couples light from a rectangular waveguide onto a coplanar waveguide via an electrical connection made with indium bump bonds. We develop a tolerance-aware optimization approach to identify high-performance transition geometries that are robust to manufacturing variations; the same formulation can be applied to other tolerance-sensitive design problems. We also describe the implementation of a custom apparatus and procedure for bump-bonding a silicon chip to a metallized 3D-printed component. We detail the fabrication of the coplanar waveguide chip and three-dimensional waveguide structure, simulations and metrology of a test device, and room temperature reflectance measurements of this device. The room temperature metrology and reflection measurements are consistent with a model that predicts a coupling efficiency of $\mathord{\sim} 95\%$ at cryogenic temperatures in the 85-170 GHz frequency range.
his work presents a fully-digital high-accuracy real-time calibration procedure for frequency and time alignment of open-loop wirelessly coordinated coherent distributed antenna array (CDA) modems, enabling radio frequency (RF) phase coherence of spatially separated commercial off-the-shelf (COTS) software-defined radios (SDRs) without cables or external references such as the global navigation satellite system (GNSS). Building on previous work using high-accuracy spectrally-sparse time of arrival (ToA) waveforms and a multistep ToA refinement process, a high-accuracy two-way time transfer (TWTT)-based time–frequency coordination approach is demonstrated. Due to the two-way nature of the high-accuracy TWTT approach, the time and frequency estimates are Doppler and multipath tolerant, so long as the channel is reciprocal over the synchronization epoch. This technique is experimentally verified using COTS SDRs in a lab environment in static and dynamic scenarios and with significant multipath scatterers. Time, frequency, and phase stability were evaluated by beamforming over coaxial cables to an oscilloscope which achieved time and phase precisions of ~60– 70 ps , with median coherent gains above 99% using optimized coordination parameters, and a beamforming frequency root-mean-square error (RMSE) of 3.73 ppb in a dynamic scenario. Finally, experiments were conducted to compare the performance of this technique with previous works using an analog continuous-wave two-tone (CWTT) frequency reference technique in both static and dynamic settings.
While there is a growing appreciation of three-dimensional (3D) neural tissues (i.e., hydrogel-based, organoids, and spheroids), shown to improve cellular health and network activity to mirror brain-like activity in vivo , functional assessment using current electrophysiology techniques (e.g., planar multi-electrode arrays or patch clamp) has been technically challenging and limited to surface measurements at the bottom or top of the 3D tissue. As next-generation MEAs, specifically 3D MEAs, are being developed to increase the spatial precision across all three dimensions (X, Y, Z), development of improved computational analytical tools to discern region-specific changes within the Z dimension of the 3D tissue is needed. In the present study, we introduce a novel computational analytical pipeline to analyze 3D neural network activity recorded from a “bottom-up” 3D MEA integrated with a 3D hydrogel-based tissue containing human iPSC-derived neurons and primary astrocytes. Over a period of ~6.5 weeks, we describe the development and maturation of 3D neural activity (i.e., features of spiking and bursting activity) within cross sections of the 3D tissue, based on the vertical position of the electrode on the 3D MEA probe, in addition to network activity (identified using synchrony analysis) within and between cross sections. Then, using the sequential addition of postsynaptic receptor antagonists, bicuculline (BIC), 2-amino-5-phosphonovaleric acid (AP-5), and 6-cyano-5-nitroquinoxaline-2,3-dione (CNQX), we demonstrate that networks within and between cross sections of the 3D hydrogel-based tissue show a preference for GABA and/or glutamate synaptic transmission, suggesting differences in the network composition throughout the neural tissue. The ability to monitor the functional dynamics of the entire 3D reconstructed neural tissue is a critical bottleneck; here we demonstrate a computational pipeline that can be implemented in studies to better interpret network activity within an engineered 3D neural tissue and have a better understanding of the modeled organ tissue.
Most virus infection assays have indirect readout such as virus number following entry (e.g., PCR, cell lysis). While effective, these technologies are labor‐intensive, require specialized environments (e.g., sterile or RNA‐free), and detect later‐stage viral events like lysis or cell death, lacking sensitivity to early fusion events. To address these limitations, we present biologically relevant 2D membrane materials, host‐cell‐derived supported lipid bilayers (hcd‐SLBs), integrated with organic microelectrode arrays (OMEAs) for detection of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) fusion. By overexpressing angiotensin‐converting enzyme 2 (ACE2) receptors on the native membranes, the platform functions as a viral sensor capable of detecting virus pseudo particles (VPPs) through the late pathway. Additionally, hcd‐SLBs extracted from human lung epithelium expressing native ACE2 detect fusion events through the early pathway. The platform's utility as a drug‐screening tool is demonstrated by testing antibodies targeting either the ACE2 on the host membrane or the viral spike (S) proteins. To enhance the throughput, microfluidics are integrated for automation and OMEAs are incorporated within each channel, miniaturizing the testing units. This system supports high‐throughput data generation, automation, and scalability, providing an efficient platform for viral fusion detection that advances the study of pathogen‐host interactions and accelerates antiviral drug discovery.
Drug studies targeting neuronal ion channels are crucial to understand neuronal function and develop therapies for neurological diseases. The traditional method to study neuronal ion-channel activities heavily relies on the whole-cell patch clamp as the industry standard. However, this technique is both technically challenging and labour-intensive, while involving the complexity of keeping cells alive with low throughput. Therefore, the shortcomings are limiting the efficiency of ion-channel-related neuroscience research and drug testing. Here, this work reports a new system of integrating neuron membranes with organic microelectrode arrays (OMEAs) for ion-channel-related drug studies. This work demonstrates that the supported lipid bilayers (SLBs) derived from both neuron-like (neuroblastoma) cells and primary neurons are integrated with OMEAs for the first time. The increased expression of voltage-gated calcium (CaV) ion channels on differentiated SH-SY5Y SLBs compared to non-differentiated ones is sensed electrically. Also, dose-response of the CaV ion-channel blocking effect on primary cortical neuronal SLBs from rats is monitored. The dose range causing ion channel blocking is comparable to literature. This system overcomes the major challenges from traditional methods (e.g., patch clamp) and showcases an easy-to-test, rapid, ultra-sensitive, cell-free, and high-throughput platform to monitor dose-dependent ion-channel blocking effects on native neuronal membranes.
HgCdTe is one of the most important materials for the fabrication of infrared detectors and focal plane arrays (FPAs) deployed in environments where high-energy particles, such as protons and neutrons, are present. We designed and fabricated HgCdTe-based FPAs that can be used in high neutron radiation environments and we measured their characteristics. The influence of the radiation on the infrared FPAs and cameras is investigated. HgCdTe material and devices are capable of maintaining high performances in a high energy neutron irradiation environment. For MWIR FPA directly facing a $2.59 × 10^8$ n/cm$^2$ s neutron flux beam (with the highest energy 66 MeV) for 1 h, the noise equivalent differential temperature (NEDT) increased ~8 times after irradiation. However, NEDT decreased to 33 mK (compared to the original value of 21 mK) after one warming-up (to room temperature) and cooling-down cycle. The NEDT for the MWIR FPAs mounted parallel to the beam did not degrade (16 mK and 28 mK before irradiation, changed to 18 mK and 26 mK after irradiation, respectively).
Misfit dislocation arrays (MDAs) at semi-coherent heterogeneous interface have been demonstrated effectiveness to trap and then outgas helium (He) for alleviating void swelling in metals, but limited by atomic-level thin film deposition that is difficult to scale-up for industrial production. In this work, we proposed an innovative strategy that could generate semi-coherent homophase interfaces in a same grain by varying surface energy density assisted by high-temperature graphene (Gr) deposition. This strategy transforms strain energy and surface energy, two originally distinctive processes into successive processes, and demonstrates experimentally and theoretically by introducing {111} copper (Cu) in a {100} Cu grain. Subsequent He implantation and electrical resistivity measurement results suggest that high-density MDAs originated at this {111}/{100} interface could form stable He nanochannels near Cu surface with Gr assistance, manifesting by ultra-low increased ratio of the electrical resistivity (i.e. ~3800% of Cu vs. ~90% of Gr/Cu) after He implantation. Finally, the present findings may provide a new strategy for efficiently managing He and achieving surface protection of advanced metals, merely by depositing a super-rigid material on metal surface to greatly reduce surface energy density.
In contrast to existing silicon, CIGS, and multi-junction cells that exhibit remarkable mechanical durability, perovskite solar cells have been shown to delaminate when subjected to the mechanical loads that occur during processing and field exposures, limiting their potential as a reliable solar technology. Mechanical reinforcement is thus essential for durable and reliable perovskite technologies. One current strategy to overcome the thermomechanical fragility of perovskite solar cells is to extrinsically shield them by introducing reinforcing scaffolds which partition the cell into many distinct microcells, but improvements in mechanical stability coincide with a reduced device efficiency due to parasitic absorption by the scaffold. We address this reduced efficiency by integrating concentrating immersion-lens arrays (CILAs) into scaffold-reinforced solar cells. These scaffolds are lithographically patterned by a maskless process, in which ultraviolet light is used to pattern the scaffolds through the CILAs, ensuring self-alignment and optical contact with the microcells. Perovskite devices are deposited into the microcells, and during operation, light is concentrated into the microcells and away from the insulating scaffolds, resulting in mechanically resilient solar cells with efficiencies comparable to planar devices. The CILAs also exhibit passive tracking of incident light—verified experimentally and with ray-tracing simulations—which is critical for optimal power output as the sun moves across the sky during the day. The simplicity of the fabrication process and the efficiency of the resulting scaffolded devices show that a lens-integrated scaffold-reinforced structure is a potential pathway to high-performance, robust, commercially viable perovskite solar cells.