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At least 91 records · Page 5

Tuning crosslinking of hybrid preceramic polymers in vat photopolymerization toward controlled ceramic yields

Control of preceramic polymer crosslinking for UV-curable processing is essential for fine 3D printing with high ceramic conversion for sustainable polymer-derived ceramics (PDC) engineering. While various factors influencing ceramic yield have been studied, the systematic exploration of the relationship between crosslinking and ceramic yield, especially when crosslinking increases volatile elements, remains open for further investigation. This study addresses this gap by utilizing vat photopolymerization (VP) additive manufacturing (AM) as a versatile platform for controlling preceramic crosslinking and ceramic yield. By rationally designing and tuning the photochemical crosslinking through digital light processing (DLP), we demonstrate that the ceramic yield can be enhanced from 64% to over 86%, even with added volatile elements. We reveal that the post-pyrolysis ceramic yield can be closely correlated with the pre-pyrolysis crosslinking of the preceramic network represented by its stiffness. This correlation thereby suggests a fast, energy-efficient, non-destructive methodology to predict and improve ceramic yield. Combined with these findings, our one-pot thiol-ene hybridization of polycarbosilane and polycarbosiloxane via DLP offers an exemplary method to generate hybrid preceramic polymers with tailored material properties toward target applications, and potentially even higher ceramic yields. This study thus contributes to achieving better resource- and energy-efficient preceramic polymer and PDC processing routes toward sustainable, advanced organic–inorganic materials manufacturing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Grid Topology Discovery Algorithm Evaluation of Suitability for Utility Deployment (CRADA 606 Final Report)

This work presents the results of a field-informed demonstration aimed at evaluating the practical suitability of a topology discovery algorithm for utility environments. We demonstrated an algorithm that uses a graph-theory-informed state estimation approach for model selection. In collaboration with Survalent and Peninsula Light Co., the algorithm was applied to real feeder models and field measurements from supervisory control and data acquisition (SCADA) and advanced metering infrastructure (AMI) systems to identify the operational topology of a power distribution system. The demonstration assessed the algorithm’s performance under realistic data conditions, including sparse and noisy measurements, and examined its ability to identify the most likely network configurations. The results confirmed that the approach can effectively narrow down feasible topologies, providing operators with improved situational awareness of network status. Key lessons learned emphasize the need for systematic data validation and strategic sensor placement to enhance observability. These insights inform future deployment strategies and guide refinements for broader adoption in utility operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Autonomous hydrogel locomotion regulated by light and electric fields

Autonomous robotic functions in materials beyond simple stimulus-response actuation require the development of functional soft matter that can complete well-organized tasks without step-by-step control. We report the design of photo- and electroactivated hydrogels that can capture and deliver cargo, avoid obstacles, and return without external, stepwise control. By incorporating two spiropyran monomers with different chemical substituents in the hydrogel, we created chemically random networks that enabled photoregulated charge reversal and autonomous behaviors under a constant electric field. In addition, using perturbations in the electric field induced by a dielectric inhomogeneity, the hydrogel could be attracted to high dielectric constant materials and autonomously bypasses the low dielectric constant materials under the guidance of the electric field vector. The photo- and electroactive hydrogels investigated here can autonomously perform tasks using constant external stimuli, an encouraging observation for the potential development of molecularly designed intelligent robotic materials.

42 ENGINEERING↗

Dynamic Interfacial Design in Adaptive Hybrid Materials Enables Reversible and Tunable Mechano-Optic Smart Responses

Next-generation polymeric materials are shifting toward adaptive and interactive behaviors of living systems; however, designing materials that can reversibly modulate optical properties under mechanical deformation while maintaining mechanical robustness remains a key challenge. Here, we report a mechanically robust vitrimer-based adaptive hybrid material (AHM) that exhibits a stretch-induced reversible transparency-to-opacity transition, enabled by the integration of dynamic interactions at the polymer–silica nanoparticle interface and controlled nanoparticle self-assembly. The AHM combines boronic ester–functionalized polystyrene-b-poly(ethylene-co-butylene)-b-polystyrene (S-Bpin) with diol-functionalized silica nanoparticles (diol-SiNPs) to form a hybrid network hosting both dynamic boronic ester and hydrogen-bonding interactions. These reversible linkages facilitate controlled nanoparticle self-assembly and enable strain-induced nanoparticle alignment/aggregation. Upon stretching, SiNP-rich domains align and aggregate within the polymer matrix, while local modulus mismatch between stiff aggregated SiNP/borylated-styrene-rich regions and the softer elastomeric midblock induces surface microwrinkle formation. These internal aggregates and surface wrinkles cooperatively enhance light scattering, producing the opaque state under strain. Furthermore, the tailored AHM exhibits high toughness, thermomechanical stability, reprocessability, and programmable shape-memory behavior. This work presents a dynamic interfacial design strategy for mechanically robust, optically reconfigurable, and reusable soft materials for adaptive optics, smart windows, sensing, soft robotics, and circular smart-material platforms.

adaptive hybrid materials↗

The influence of packing structure and interparticle forces on ultrasound transmission in granular media

Ultrasound propagation through externally stressed, disordered granular materials was experimentally and numerically investigated. Experiments employed piezoelectric transducers to excite and detect longitudinal ultrasound waves of various frequencies traveling through randomly packed sapphire spheres subjected to uniaxial compression. The experiments featured in situ X-ray tomography and diffraction measurements of contact fabric, particle kinematics, average per-particle stress tensors, and interparticle forces. The experimentally measured packing configuration and inferred interparticle forces at different sample stresses were used to construct spring networks characterized by Hessian and damping matrices. The ultrasound responses of these network were simulated to investigate the origins of wave velocity, acoustic paths, dispersion, and attenuation. Results revealed that both packing structure and interparticle force heterogeneity played an important role in controlling wave velocity and dispersion, while packing structure alone quantitatively explained most of the observed wave attenuation. This research provides insight into time- and frequency-domain features of wave propagation in randomly packed granular materials, shedding light on the fundamental mechanisms controlling wave velocities, dispersion, and attenuation in such systems.

36 MATERIALS SCIENCE↗

3D Printing of Liquid Crystal Elastomer Foams for Enhanced Energy Dissipation Under Mechanical Insult

Polymer foams are an essential class of lightweight materials used to protect assets against mechanical insults, such as shock and vibration. Two features are important to enhance their energy absorption characteristics: the foam structure and the matrix phase mechanical behavior. This study investigates novel approaches to control both of these features to enhance the energy absorption capability of flexible lattice foams. First, we consider 3D printing via digital light processing (DLP) as a method to control the foam mesostructure across a suite of periodic unit cells. Second, we introduce an additional energy dissipation mechanism in the solid matrix phase material by 3D printing the lattice foams with polydomain liquid crystal elastomer (LCE), which undergo a mechanically induced phase transition under large strains. This phase transition is associated with LC mesogen rotation and alignment and provides a second mechanism for mechanical energy dissipation in addition to the viscoelastic relaxation of the polymer network. Here, we contrast the 3D printed LCE lattices with conventional, thermomechanically near-equivalent elastomer lattice foams to quantify the energy-absorbing enhancement the LCE matrix phase provides. Under cyclic quasi-static uniaxial compression conditions, the LCE lattices show dramatically enhanced energy dissipation in uniaxial compression compared to the non-LCE equivalent foams printed with a commercially available photocurable elastomer resin. The lattice geometry also plays a prominent role in determining the energy dissipation ratio between the LCE and non-LCE foams. We show that when increasing the lattice connectivity, the foam deformation transitions from bending-dominated to stretching-dominated deformations, which generates higher axial strains in the struts and higher energy dissipation in the lattice foam, as stretching allows greater mesogen rotation than bending. The LCE foams demonstrate superior energy absorption during the repeated dynamic loading during drop testing compared with the non-LCE equivalent foams, demonstrating the potential of LCEs to enhance physical protection systems against mechanical impact.

3D printing↗

Pathways to Carbon Neutrality 2050 in Malaysia and Kuala Lumpur

Malaysia has recently set an ambitious target of achieving carbon neutrality as early as 2050. To accomplish this, the country will need to strategically reduce its emissions across all sectors. In 2020, Malaysia emitted approximately 368 MtCO2e, with the largest sources of emissions including electricity (36% of total emissions), transportation (17%), and industry (15%)1. We find that the greatest reductions in emissions can therefore come from decarbonizing power generation and electrifying end-use sectors. Digitalization, smart technologies, and improved energy efficiency will significantly reduce economy-wide energy consumption. By leveraging efficient technologies, both Malaysia and Kuala Lumpur can address the challenges posed by rapid urbanization and climate change. Digitalization is a broad category that includes a variety of measures; for example, the wide adoption of high-efficiency appliances and lighting or improved building energy codes in the buildings sector. Similarly, technological improvements can advance industrial energy efficiency, and for transportation, smart technologies cover a shift from private to public transportation and the greater use of electric vehicles. While renewable energy (RE) will play a crucial role in decarbonization, achieving carbon neutrality in certain sectors will be difficult without emerging technologies like carbon capture and storage (CCS) and innovative fuel sources such as hydrogen. In order for Malaysia to rely on CCS as a mitigation option, early investment and incentives to the private sector will be critical. This holds for the use of hydrogen as well: investing in the necessary technology, infrastructure, and human capital will allow Malaysia to position itself as an innovator in the region and leverage these advanced technologies as a key part of its climate strategy. Another possible carbon removal option other than CCS would be a land-use sink; however, given that Malaysia is still developing and may deforest in the near-term, this report does not focus on the mitigation potential of land-use change. With its innovative and bold climate plans, Kuala Lumpur is primed to be a leader in regional climate change efforts. Kuala Lumpur is also engaged in several international collaborations to ensure sustainable city development such as the C40 network and the ASEAN Smart Cities Partnership. As such, the city will play a critical role in contributing to Malaysia’s overall climate goals and as a policy trendsetter through ambitious, scalable plans. One key factor in these emissions reductions is that Kuala Lumpur has full control over its building guidelines, allowing for ambitious policies resulting in significant emissions reductions. However, in other sectors, Kuala Lumpur has less direct control over regulations; for example, power generation and integration of RE are largely in the hands of the Malaysian government. With limited and primarily light industry, Kuala Lumpur’s contributions to emissions reductions here are curbed. And, while Kuala Lumpur has control over local transportation policies like increasing access to and quality of public transportation, broad shifts in transportation will stem from national-level policies. As such, multi-level governance is an integral component of Malaysia’s climate strategy and coordination between local and national governments will be essential in reducing emissions and achieving other climate goals. This report addresses these and other key challenges and opportunities Malaysia faces on the road to carbon neutrality.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Gut microbiome changes with micronutrient supplementation in children with attention–deficit/hyperactivity disorder: the MADDY study

Micronutrients have demonstrated promise in managing inattention and emotional dysregulation in children with attention-deficit/hyperactivity disorder (ADHD). The biological mechanism by which micronutrients improve these symptoms remains unclear. One plausible pathway is through the gut-brain axis, the bi-directional communication network that links the gastrointestinal tract with the brain. This study examines changes in gut microbiome composition and diversity after micronutrients supplementation in children with ADHD (N=44) and sheds light on potential mechanisms responsible for the response to micronutrients as measured by clinician-rated global impression. Participants from this investigation represent a sub-group of the Micronutrients for ADHD in Youth (MADDY) study, a double blind randomized controlled study in which participants received either micronutrients or a placebo for 8 weeks, followed by an 8-week open label extension with micronutrients for all participants. Stool samples collected at baseline, week 8, and week 16 were analyzed using 16S rRNA amplicon sequencing targeting the V4 hypervariable region. Pairwise compositional analyses served as the primary means for investigating changes in gut microbiome composition between micronutrients versus placebo groups and responders versus non-responders. A significant change in microbial evenness, as measured by alpha diversity, was observed following micronutrients, and the phylum Actinobacteriota decreased in the micronutrients group compared to placebo. Additionally, two bacterial families: Rikenellaceae and Oscillospiraceae, exhibited a significant increase in change of gut microbiome composition following micronutrients between responders and non-responders. These findings suggest that micronutrients modulated the composition of the gut microbiome and point towards specific bacterial changes associated with response to micronutrients.

60 APPLIED LIFE SCIENCES↗

Detector Interface for Streaming, Control, and Open-source integration (DISCO) v1.0.0

This suite consists of a multi-package ecosystem featuring detector emulators, EPICS areaDetector drivers, and remote server frameworks designed for the Advanced Light Source (ALS). Engineered for high-bandwidth devices—including VFCCD, Timepix3, Timepix4, and related pixel detectors—the software simulates hardware, wraps vendor SDKs into remote-callable servers, and integrates with open-source control systems. Key Capabilities: Distributed SDK Architecture: Server packages wrap hardware-specific SDKs, allowing areaDetector drivers to execute remote framework calls. This isolates proprietary libraries from the EPICS IOC, enhancing stability and enabling distributed computing across beamline networks. Device Support: Custom drivers for VFCCD, the Timepix family, and similar sensors optimize the data path from hardware control to high-speed transport. Full-Stack Emulation: Sophisticated emulator packages allow end-to-end pipeline testing and software development without requiring physical hardware or beam time. Integrated Workflows: Supports high-bandwidth streaming for real-time analysis and robust, metadata-rich file-based workflows (e.g., HDF5/NeXus). By standardizing interfaces across heterogeneous hardware, this suite reduces technical debt. It provides the ALS with a scalable, open-source solution to manage massive data rates within a unified control environment.

Mahl, Johannes [Lawrence Berkeley National Laborat↗

Statistical Analysis of Inter-Area Oscillations in the U.S. Eastern Interconnection: A 2017-2023 Perspective

Recent advancements and the accumulation of high-resolution, long-term phasor measurement unit (PMU) data have provided detailed insights into inter-area oscillations in power grids. This study conducts a comprehensive statistical analysis of inter-area oscillations within the United States Eastern Interconnection from 2017 to 2023. Utilizing data captured by the advanced wide-area Frequency Monitoring Network (FNET/GridEye), this investigation examines the occurrence patterns, dominant frequencies, damping ratios, and excitation mechanisms of these oscillations. Our analysis sheds light on the evolving statistical behaviors of inter-area oscillations, offering updated and critical information for grid operators and planners. The insights gained from this study can be instrumental in enhancing the operational resilience of the power network and guiding strategic developments in grid infrastructure to accommodate future challenges. Additionally, the study discusses emerging challenges associated with the modernization of the power grid, including increased renewable penetration, dynamic load variability, and cyber-physical vulnerabilities that complicate oscillation monitoring and control.

Inter-area oscillations↗

Demonstration of Utility Managed Smart Charging for Multiple Benefit Streams (Final Report)

In the summer of 2020, the U.S. Department of Energy (DOE) awarded funding to Exelon’s Maryland utilities—Baltimore Gas and Electric (BGE), Delmarva Power & Light (DPL), and Potomac Electric Power Company (Pepco)—to implement the Smart Charge Management (SCM) pilot. This initiative aimed to design and implement managed electric vehicle (EV) charging strategies, evaluate the grid impacts of EV charging, and assess the utilities' ability to control EV load based on real-time grid conditions. The SCM pilot explored four aspects for continued improvement: (1) cybersecurity and managed charging functionality testing of two vendor platforms—WeaveGrid (telematics-based) and Shell Recharge Solutions (network-based)—which pursued charge scheduling and optimization through distinct approaches; (2) an analysis by Argonne National Laboratory (ANL) modeling team of three potential SCM enrollment scenarios within BGE and Pepco service territories over the next decade to assess future scalability; (3) employing customer engagement strategies, including surveys and a responsive pricing approach; and (4) the launch and implementation of pilots in Exelon’s Maryland territories in collaboration with WeaveGrid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Heterogenous catalysis for oxygen tolerant photoredox atom transfer radical polymerization and small-molecule dehalogenation

Heterogeneous photocatalysts (PCs) have garnered attention for their sustainability and cost-effectiveness. Despite the existence of various types of these PCs, their synthesis often involves complex, multi-step procedures and laborious purification. Herein, we propose a simple method for attaching small-molecule photocatalytic species onto crosslinked 3-D polymer networks as insoluble scaffolds to create robust heterogeneous PCs. The highly swellable poly(ethylene glycol)-based ChemMatrix (CM) resin, known for its amphiphilic properties and high functional group loading, facilitated the covalent immobilization of the photoredox dye Eosin Y (EY), but also streamlined functionalization with Ir( III ) complexes. The resulting heterogeneous CM-EY demonstrated efficient photocatalytic performance in open-to-air dual photoredox catalysis of atom transfer radical polymerization (photo-ATRP) under green light. This was confirmed by the well-controlled synthesis of polymers with molecular masses ranging from 20 kDa to 300 kDa and low dispersities. Furthermore, CM-EY exhibited excellent photostability and recyclability over multiple cycles of ATRP. The heterogeneous catalysis of photo-ATRP provided high temporal control and enabled benign conditions for synthesizing protein-polymer hybrids (PPH). When combined with the initiator-modified CM (CM-BIB), CM-EY facilitated the solid-phase synthesis of homopolymers and block copolymers with recyclable performance. However, the coordinatively bound Ir@CM showed decreased catalytic activity and efficiency toward photoredox dehalogenation due to the leaching of active species during recycling. This study highlights the advantages of the covalent linking of catalysts to solid supports over non-covalent interactions, underscoring the potential of functionalized polymer resin as a promising scaffold. Such an approach offers customization and tunability, presenting opportunities for innovation in green chemistry.

Kapil, Kriti↗

Application of deep learning methods for beam size control during user operation at the Advanced Light Source

Past research at the Advanced Light Source (ALS) provided a proof-of-principle demonstration that deep learning methods could be effectively employed to compensate for the significant perturbations to the transverse electron beam size induced by user-controlled adjustments of the insertion devices. However, incorporating these methods into the ALS’ daily operations has faced notable challenges. The complexity of the system’s operational requirements and the significant upkeep demands has restricted their sustained application during user operation. Here, we introduce the development of a more robust neural network (NN)-based algorithm that utilizes a novel online fine-tuning approach and its systematic integration into the day-to-day machine operations. Our analysis emphasizes the process of NN model selection, demonstrates the superior performance of the NN-based method over traditional feedback methods, and examines the effectiveness and resilience of the new algorithm during user-operation scenarios. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

Examining Nuisance Aerosol Detections in Light of the Origin of the Screening Process (November 2021)

The evolution of philosophy and computations in the International Data Center (IDC) related to aerosol samples have had profound impacts on the number of recorded detections in the network since routine operations began in 2000. Key decisions from policymakers have been the list of triggering radionuclides, the scheme for categorizing these into interest levels 1-5, and an algorithm for determining when an anthropogenic isotope is seen so often that it is no longer interesting, known as the Exponential Weighted Moving Average (EWMA). These are described in the Operations Manual of the IDC. Key parameters that are controlled by the IDC but for which the IDC receives occasional input from policymakers include the constants in EWMA and the peak significance threshold for individual gamma rays, the latter of which directly leads to determination of the presence or absence of a radionuclide in a sample. There are also changes in computations which the IDC makes and informs policy makers about, such as changes in how background is computed, which could also affect the ease of detecting a peak – real or false. Rather than focus on the quantitative changes due to computation changes, this work records some thinking on how isotopes and peak significance levels were chosen, and the resulting detections seen over 18 years during the buildup of the International Monitoring System (IMS). These detections are considered on a global scale to try to determine the relative impact on monitoring, and in some cases, the nature of their existence. Repeated detections of 131I and 133I are the most troublesome, but they are not so frequent to be a major problem for the Verification Regime. These detections could probably be handled adequately using scientific methods currently under development for xenon backgrounds. It is also somewhat problematic that top-level analysis of aerosol backgrounds has not been reported previous to this. The steep increase in the rate of detections after 2016 are a concern, either in the actual backgrounds or from changes in the calculations methods used to generate the Reviewed Radionuclide Report (RRR.) Final conclusions of the authors are that the computational stability of the RRR is very important. With computational stability, changes can be usefully analyzed as being due to changes in radioactivity in Earth’s atmosphere This report is a distillation into text of a talk given in the Radionuclide Experts Group (RNEG) in Vienna during Working Group B (WGB) in February of 2019. This report does not directly contain any IDC data, only summaries by year, or by isotope, or by location. No specific IDC detection by time, location, or isotope is included.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A machine learning approach for clinker quality prediction and nonlinear model predictive control design for a rotary cement kiln

Abstract Cement manufacturing is energy‐intensive (5Gj/t) and comprises a significant portion of the energy footprint of concrete systems. Incorporating modern monitoring, simulation and control systems will allow lower energy use, lower environmental impact, and lower costs of this widely used construction material. One of the goals of the CESMII roadmap project on the Smart Manufacturing of Cement included developing an analytical process model for clinker quality that includes the chemistry of the kiln feed and accounts for critical process variables. This predictive model will be used in nonlinear model predictive control system designed to significantly reduce process energy use while maintaining or improving product quality. In the cement manufacturing plant used in this study, the kiln feed (meal) is tested every 12 h and used to estimate the mineral composition of the cement kiln output (clinker) using the stoichiometry‐based Bogue's model and the expertise of the plant operators. During kiln operation, kiln output (clinker) is sampled and tested every 2 h to measure its chemical and mineral composition. The predicted and measured values of the clinker composition are used by the plant operators to adjust the kiln input stream and the production process characteristics to maintain stable operation and uniform product quality. However, the time delay between prediction and testing, along with inaccuracies inherent in the Bogue's model have made any process changes designed to minimize energy use problematic, especially in‐light of potential clinker quality issues that process changes often pose. A new analytical model that integrates quality information and process operation information has been developed from data collected from 2 years of production from an operating cement facility. To make the model fuel‐type‐independent, consumed heat energy was computed in the model instead of fuel type and amount. A Feedforward Network was trained and tailored from collected data. Many data‐based simulations were conducted to quantitatively evaluate the proposed model and the 5‐fold cross‐validation procedure was used to test the models. The resulting predictive model was shown to have a low root mean square error (MSE) with respect to the estimated clinker mineral composition compared to that using the industry standard “Bogue’ model”. The end goal of this work was to develop a single machine learning tool that allows the use of quality control data and process control variables to improve energy efficiency of the process in a continuous fashion. The proposed nonlinear model predictive control system (NMPC) can generate predicted kiln production characteristics based on manipulated variables in manner that accurately follows the target product quality values. Simulation results also show that the proposed model produced accurate predictions of kiln outputs that fell within the required constraints, while manipulating control variables within typical operational ranges.

Ali, Asem M.↗

Acoustic Travel-Time Tomography for Wind Energy

New remote sensing technologies for direct observation of the atmospheric flow in the proximity of operating wind turbines are necessary for the advancement of wind turbine design, wind plant control, and the validation of high-fidelity numerical models; fundamental goals of the DOE Wind Energy Technology Office's (WETO's) A2e program. Modern remote sensing technologies for commercial and research applications rely on the backscatter of light or sound waves, which limits spatial and temporal resolution and cannot produce reliable flow estimates near solid bodies or reflective surfaces. Acoustic tomography (AT) is an innovative sensing technology based on fundamental thermodynamic properties of the atmosphere and an inverse algorithm that can reconstruct both velocity and temperature fields within a network of acoustic transducers. AT relies on the direct travel path of acoustic signals between speakers and microphones in the network and can achieve much higher resolutions than conventional backscatter technologies. For wind energy R&D applications, AT represents an extremely economical option over other remote sensing technologies, integrating mature and commonly available acoustic and signal processing hardware. This report is intended as an update on the development of the AT array on the NREL Flatirons Campus (FC) and includes a brief review of the instrumentation, the calibration of equipment, signal processing, and resulting flow field estimates. Designs for future AT systems and applications are detailed in this report, including summaries of new capabilities, engineering and theoretical challenges, and anticipated costs help to outline future directions for AT technology R\&D. The potential for application of AT to utility-scale turbines is also discussed. Investing in the development of the proposed instrument will establish AT as a transformational RS technique that represents a significant advance in measurement instrumentation, enabling new fundamental insights into the structure of the atmospheric boundary layer and supporting applications for wind energy, pollution transport, and resource characterization. AT is also an extremely economical option over other RS instruments, integrating mature and commonly available acoustic and signal processing hardware.

17 WIND ENERGY↗

Malware Analysis Report for SolarWinds.Orion.Core.BusinessLayer.dll

SolarWinds Orion is a software suite designed to provide “single pane of glass” monitoring of network devices and applications. On December 13 2020, FireEye revealed that SolarWinds Orion was the victim of a supply chain attack and that the SolarWinds signed file SolarWinds.Orion.Core.BusinessLayer.dll contained a backdoor. SolarWinds deployed the back-doored patch to customers beginning in March 2020. FireEye first identified this backdoor and labeled it SUNBURST. The backdoor is composed of roughly 4,000 lines1 of lightly obfuscated .NET within the SolarWinds.Orion.Core.BusinessLayer.OrionImprovementBusinessLayer class of the malicious dll. The backdoor’s capabilities include: the ability to detect and potentially disable antivirus and forensics tools, basic command and control via DNS, and more advanced command and control via HTTP.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Wavelength- and irradiance-dependent changes in intracellular nitric oxide level

Photobiomodulation (PBM) refers to beneficial effects of low energy light absorption. Although there is a large and growing body of literature describing down-stream physiological benefits of PBM, there is limited understanding of the molecular mechanisms that initiate and mediate these effects at the level of photon absorption. At present, the leading hypothesis is that light absorption induces release of nitric oxide (NO) from the active site of cytochrome c oxidase (COX), allowing it to bind O 2 instead. This is believed to increase mitochondrial respiration, and result in greater overall health of the cell due to increased ATP production. Aim: Although NO itself is a powerful signaling molecule involved in a host of biological responses, less attention has been devoted to the mechanisms of NO release and subsequent effects on cell signaling. The purpose of this work is to investigate wavelength-specific effects on intracellular NO release in living cells. Approach: We have conducted in depth dosimetry analyses of NO production and function in an in vitro retinal model in response to low energy exposure to one or more wavelengths of laser light. Results: We found statistically significant wavelength-dependent elevations (10-30%) in intracellular NO levels following laser exposures at 447, 532, 635 or 808 nm. Sequential or simultaneous exposures to light at two different wavelengths enhanced the NO modulation up to 50% of unexposed controls. Additionally, the immediate increases in cellular NO levels were independent of the function of nitric oxide synthase, depended greatly on the substrate source of electrons entering the electron transport chain, and did not result in increased levels of cGMP. Conclusions: This study concludes the simple model of light-mediated release of NO from COX is unlikely to explain the wide variety of PBM effects reported in the literature. Our multi-wavelength method provides a novel tool for studying immediate and early mechanisms of PBM, as well as exploring intracellular NO signaling networks.

59 BASIC BIOLOGICAL SCIENCES↗