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At least 775 records · Page 43

Advancing Autonomy in Distributed Space Systems: Insights From on-Orbit Testing with the Starling 1.0 Mission

Autonomous decision-making is crucial for enhancing mission effectiveness in Distributed Space Systems (DSS), particularly in multi-spacecraft operations where communication constraints and mission complexity pose challenges. The Distributed Spacecraft Autonomy (DSA) team at NASA’s Ames Research Center is advancing autonomy in DSS through five key technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. The DSA experiment onboard the Starling 1.0 Mission showcases collaborative resource allocation for multi-point science data collection with four small spacecraft. Autonomy in decision-making is highlighted as a crucial factor for multi-spacecraft missions, enabling spacecraft to operate independently, reducing reliance on ground control. This capability is particularly significant for future deep-space missions, where communication delays and limited data transmission capacity make traditional command and control approaches impractical. This demonstration focuses on a GPS Channel Selection Experiment, leveraging emergent capabilities like "shared sampling" and "simultaneous sampling" to optimize channel selection across the spacecraft swarm. The experiment aims to capture ionospheric phenomena such as the Equatorial Ionization Anomaly and Polar Patches. The DSA system's autonomous reconfiguration ability is showcased, emphasizing its adaptability to natural phenomena without significant integration efforts. The GPS Channel Selection Experiment utilizes a dual-band GPS receiver to estimate plasma density in the ionosphere. Explorative and exploitative channel selections are employed based on the nature of observed phenomena. The performance of DSA algorithms is evaluated in terms of optimal channel allocations and responsiveness to changes in observed features. The DSA Flight Software utilizes the Core Flight System (cFS) framework, ensuring compatibility with the Starling 1.0 flight mission software. DSA showcases results from RTI’s Connext DDS Micro communication middleware, enabling message routing over the Ad-Hoc Network of Starling 1.0. This paper provides a comprehensive overview of the DSA experiment's initial results, emphasizing the advancements in autonomy for Distributed Space Systems and the successful collaboration with the Starling 1.0 mission.

Caleb Ashmore Adams↗

"Designing, simulating, and performing the 100-AV field test for the CIRCLES consortium: Methodology and Implementation of the Largest mobile traffic control experiment to date"

Previous controlled experiments on single-lane ring roads have shown that a single partially autonomous vehicle (AV) can effectively mitigate traffic waves. This naturally prompts the question of how these findings can be generalized to field operational, high-density traffic conditions. To address this question, the Congestion Impacts Reduction via CAV-in-the-loop Lagrangian Energy Smoothing (CIRCLES) Consortium conducted MegaVanderTest (MVT), a live traffic control experiment involving 100 vehicles near Nashville, TN, USA. This article is a tutorial for developing analytical and simulation-based tools essential for designing and executing a live traffic control experiment like the MVT. It presents an overview of the proposed roadmap and various procedures used in designing, monitoring, and conducting the MVT, which is the largest mobile traffic control experiment at the time. The design process is aimed at evaluating the impact of the CIRCLES AVs on surrounding traffic. The article discusses the agent-based traffic simulation framework created for this evaluation. A novel methodological framework is introduced to calibrate this microsimulation, aiming to accurately capture traffic dynamics and assess the impact of adding 100 vehicles to existing traffic. The calibration model's effectiveness is verified using data from a six-mile section of Nashville's I-24 highway. The results indicate that the proposed model establishes an effective feedback loop between the optimizer and the simulator, thereby calibrating flow and speed with different spatiotemporal characteristics to minimize the error between simulated and real-world data. Finally, We simulate AVs in multiple scenarios to assess their effect on traffic congestion. This evaluation validates the AV routes, thereby contributing to the execution of a safe and successful live traffic control experiment via AVs.

Ameli, Mostafa↗

Transformation of zinc-concentrate in surface and subsurface environments: Implications for assessing zinc mobility/toxicity and choosing an optimal remediation strategy

Zinc contamination in near- and sub-surface environments is a serious threat to many ecosystems and to public health. Sufficient understanding of Zn speciation and transport mechanisms is therefore critical to evaluating its risk to the environment and to developing remediation strategies. The geochemical and mineralogical characteristics of contaminated soils in the vicinity of a Zn ore transportation route were thoroughly investigated using a variety of analytical techniques (sequential extraction, XRF, XRD, SEM, and XAFS). Imported Zn-concentrate (ZnS) was deposited in a receiving facility and dispersed over time to the surrounding roadside areas and rice-paddy soils. Subsequent physical and chemical weathering resulted in dispersal into the subsurface. The species identified in the contaminated areas included Zn-sulfide, Zn-carbonate, other O-coordinated Zn-minerals, and Zn species bound to Fe/Mn oxides or clays, as confirmed by XAFS spectroscopy and sequential extraction. The observed transformation from S-coordinated Zn to O-coordinated Zn associated with minerals suggests that this contaminant can change into more soluble and labile forms as a result of weathering. For the purpose of developing a soil washing remediation process, the contaminated samples were extracted with dilute acids. The extraction efficiency increased with the increase of O-coordinated Zn relative to S-coordinated Zn in the sediment. Furthermore, this study demonstrates that improved understanding of Zn speciation in contaminated soils is essential for well-informed decision making regarding metal mobility and toxicity, as well as for choosing an appropriate remediation strategy using soil washing.

54 ENVIRONMENTAL SCIENCES↗

Towards Optimal and Executable Distribution Grid Restoration Planning With a Fine-Grained Power-Communication Interdependency Model

Distribution service restoration (DSR) under natural disasters is always a critical and challenging problem for utility companies. An effective solution must not ignore the power-communication interdependency as various systems are getting increasingly connected in the Smart Grid era. In this paper, we propose a two-layer distribution system model with both power and communication components. Based on this model, we formulate the restoration process as a routing problem that schedules the path and action sequence of utility crews that involves repairing damaged components, closing power switches, and enabling communication paths between the control center and remote field devices. Further, we develop a simulation-based method to quantitatively evaluate the restoration process with public reference models of large-scale power systems. The experimental results show that our method improves the total restored energy up to 57.6% and reduces the recovery time up to 63% by considering the power-communication interdependency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Influence of temperature, doping, and amorphization on the electronic structure and magnetic damping of iron

Hybrid magnonic quantum systems have drawn increased attention in recent years for coherent quantum information processing, but too large magnetic damping is a persistent concern when metallic magnets are used. Their intrinsic damping is largely determined by electron-magnon scattering induced by spin-orbit interactions. In the low scattering limit, damping is dominated by intra-band electronic transitions, which has been theoretically shown to be proportional to the electronic density of states at the Fermi level. In this work, we focus on body-centered-cubic iron as a paradigmatic ferromagnetic material. We comprehensively study its electronic structure using first-principles density functional theory simulations and account for finite lattice temperature, boron (B) doping, and structure amorphization. Our results indicate that temperature induced atomic disorder and amorphous atomic geometries only have a minor influence. Instead, boron doping noticeably decreases the density of states near the Fermi level with an optimal doping level of 6.25%. In addition, we show that this reduction varies significantly for different atomic geometries and report that the highest reduction correlates with a large magnetization of the material. Furthermore, this may suggest materials growth under external magnetic fields as a route to explore in experiment.

36 MATERIALS SCIENCE↗

ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO 2 , water, and energy fluxes on daily to annual scales

Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO 2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation ( V cmax ) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) ( r 2 = 0.76; Nash–Sutcliffe modeling efficiency, MEF =0.76) and ecosystem respiration (ER, r 2 = 0.78, MEF = 0.75), with lesser accuracy for latent heat fluxes (LE, r 2 2 exchange (NEE, r 2 = 0.38, MEF = 0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r 2 values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r 2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted ( r 2 < 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized V cmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average V cmax value

58 GEOSCIENCES↗

Accurate prediction of core-level spectra of radicals at density functional theory cost via square gradient minimization and recoupling of mixed configurations

State-specific orbital optimized approaches are more accurate at predicting core-level spectra than traditional linear-response protocols, but their utility had been restricted due to the risk of "variational collapse" down to the ground state. We employ the recently developed square gradient minimization algorithm to reliably avoid variational collapse and study the effectiveness of orbital optimized density functional theory (DFT) at predicting second period element 1s core-level spectra of open-shell systems. Several density functionals (including SCAN, B3LYP, and ωB97X-D3) are found to predict excitation energies from the core to singly occupied levels with high accuracy (≤0.3 eV RMS error) against available experimental data. Higher excited states are, however, more challenging by virtue of being intrinsically multiconfigurational. We thus present a configuration interaction inspired route to self-consistently recouple single determinant mixed configurations obtained from DFT, in order to obtain approximate doublet states. This recoupling scheme is used to predict the C K-edge spectra of the allyl radical, the O K-edge spectra of CO + , and the N K-edge of NO 2 with high accuracy relative to experiment, indicating substantial promise in using this approach for the computation of core-level spectra for doublet species [vs more traditional time dependent DFT, equation of motion coupled cluster singles and doubles (EOM-CCSD), or using unrecoupled mixed configurations]. Finally, we also present general guidelines for computing core-excited states from orbital optimized DFT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improving Performance of III-V Solar Cells Grown on Spalled Germanium with Ex Situ Substrate Planarization

Controlled spalling allows removal of devices and provides an opportunity for cost reduction through substrate reuse. However, the fracture-based process can leave behind morphological surface features, notably river lines, that can disrupt epitaxial growth and degrade device performance. We investigate the viability of various wet etch chemistries to planarize river lines to ensure high-quality device growth and performance without mechanical repolishing, and so maintain a route towards cost-effective reuse. Etching in a HF: HNO 3 :CH 3 COOH solution effectively planarizes river lines and produces a surface that yields devices with equivalent performance to those grown on epi-ready Ge wafer surfaces. Further studies will focus on optimizing etch composition, temperature, and time to minimize material removal while maintaining a suitable surface for high-quality epitaxy.

germanium↗

Orchestrated trios: compiling for efficient communication in Quantum programs with 3-Qubit gates

Current quantum computers are especially error prone and require high levels of optimization to reduce operation counts and maximize the probability the compiled program will succeed. These computers only support operations decomposed into one- and two-qubit gates and only two-qubit gates between physically connected pairs of qubits. Typical compilers first decompose operations, then route data to connected qubits. We propose a new compiler structure, Orchestrated Trios, that first decomposes to the three-qubit Toffoli, routes the inputs of the higher-level Toffoli operations to groups of nearby qubits, then finishes decomposition to hardware-supported gates. This significantly reduces communication overhead by giving the routing pass access to the higher-level structure of the circuit instead of discarding it. A second benefit is the ability to now select an architecture-tuned Toffoli decomposition such as the 8-CNOT Toffoli for the specific hardware qubits now known after the routing pass. Furthermore, we perform real experiments on IBM Johannesburg showing an average 35% decrease in two-qubit gate count and 23% increase in success rate of a single Toffoli over Qiskit. We additionally compile many near-term benchmark algorithms showing an average 344% increase in (or 4.44x) simulated success rate on the Johannesburg architecture and compare with other architecture types.

compiler↗

OR-AGENT framework – Architecting electrified heavy-duty drayage applications

The widespread adoption of zero-emission vehicles in heavy-duty (HD) commercial freight transportation faces considerable technoeconomic challenges. For heavy-duty trucks, ensuring high uptime, cost parity with diesel, and safety standards is especially critical as these vehicles operate over long distances with heavy loads, where any downtime or off-nominal behaviors significantly impacts logistics, productivity, and the total cost of ownership. Unlike traditional diesel refueling, BEV charging infrastructure must be co-optimized with vehicle deployment, operational demands, and grid capacity to ensure cost-effective and reliable freight operations. However, the lack of a standardized ownership and service model has led to a fragmented approach—where commercial vehicle operators may invest in, own, and maintain both vehicle/batteries and charging/energy infrastructure. This disconnect may exclude energy service providers from the equation, forcing fleet operators to explore ‘behind-the-fence’ energy solutions that increase capital investment, operational downtime, overhead costs, and, in some cases, net carbon emissions. To address these issues, this study introduces OR-AGENT (Optimal Regional Architecture Generation for Efficient National Transport), a comprehensive modeling framework that integrates powertrain architectures, charging infrastructures, and energy backbone systems into a cohesive strategy. In this paper, OR-AGENT is applied to develop an interconnected systems architecture for energy efficiency and resiliency enhancement of heavy-duty drayage vehicles at the Port of Savannah, GA. This framework showcases an interconnected systems approach to electrifying heavy-duty drayage vehicles at the Port of Savannah, GA. The study assessed BEVs with 400–1200 kWh battery capacities, accounting for seasonal variations in weather and freight routing. A diverse charging mix (150 kW–1250 kW) was evaluated alongside grid capacity constraints, cost, and carbon intensity analysis, leading to the development of a strategic microgrid/Distributed Energy Resources (DER) deployment architecture to ensure a reliable and sustainable transition. However, the findings also highlight the need for alternative zero-emission solutions for remaining trips, such as larger batteries, electrified roadways, hydrogen powertrains, or net-zero emission fuels. In conclusion, the findings are incorporated into a Total Cost of Ownership (TCO) model to identify optimal architectures for an interconnected electrified ecosystem.

Commercial vehicles↗

Enhanced UAS Availability via Vehicle to Vehicle Routing Scaled Experiments

The safe integration of modern unmanned aerial systems into the national airspace requires the ability to be able to confirm that the vehicles are working as planned. This means the availability of the vehicle and latency of the communication is critical. These requirements, along with a complex and multifaceted environment as well as the unmanned air traffic management framework, present a unique optimization problem. In this paper, we articulate our envisioned problem space and create a scaled-down version to test the functional feasibility of utilizing the vehicle to vehicle communication as a secondary communication assurance mechanism. We present our framework, experimental approach, and some lessons learned through the process.

Nicholas B Cramer↗

Modeling Ti–6Al–4V using crystal plasticity, calibrated with multi-scale experiments, to understand the effect of the orientation and morphology of the α and β phases on time dependent cyclic loading

Classically, crystal plasticity modeling has used a range of constitutive equations, in which the incorporation of additional physics-based relationships typically results in additional model parameters. These additional parameters need to be reliably calibrated, which often necessitates the use of a range of experimental data acquired at multiple length scales. In this work, a crystal plasticity based finite element (CPFE) model for a dual-phase Titanium alloy, Ti–6Al–4V, is developed. The α and β phases of the microstructure are explicitly modeled. The model is calibrated using a systematic optimization routine and experimental data that consist of macroscopic stress-strain curves coupled with lattice strains on different crystallographic planes for the two phases. These experimental data were obtained from in situ high energy X-ray diffraction experiments for multiple material pedigrees, with varying crystallographic orientation distribution and β volume fractions. Depending on the thermomechanical-processing route and the heat treatment used to manufacture the alloy, Ti–6Al–4V can exist in a wide number of microstructural forms, which often results in the α and β phases either having well aligned slip systems (following the Burgers orientation relationship (BOR)) or possessing no alignment of the slip systems across the interphase boundary (not following the BOR). In this study, the fully-calibrated CPFE model is used to gain a comprehensive understanding of the deformation behavior of Ti–6Al–4V, specifically, the effect of microstructures that follow the BOR (or not) on time-dependent cyclic loading (including the effects of dwell hold times).

36 MATERIALS SCIENCE↗

Development in corrosion resistance by microstructural refinement in Zr-16 SS 304 alloy using suction casting technique

Highlights: • Grain refinement was made in Zr–16 wt.% SS alloy while prepared by suction casting process. • Distribution of Laves phase, e.g., Zr{sub 2}(Fe, Cr) was raised in suction cast (SC) Zr–16 wt.% SS. • Corrosion resistance was improved in SC alloy compared to that of arc-melt-cast alloy. • Grain refinement in SC alloy assisted for an increase in its corrosion resistance. - Abstract: Zirconium (Zr)-stainless steel (SS) hybrid alloys are being considered as baseline alloys for developing metallic-waste-form (MWF) with the motivation of disposing of Zr and SS base nuclear metallic wastes. Zr–16 wt.% SS, a MWF alloy optimized from previous studies, exhibit significant grain refinement and changes in phase assemblages (soft phase: Zr{sub 2}(Fe, Cr)/α-Zr vs. hard phase: Zr{sub 3}(Fe, Ni)) when prepared by suction casting (SC) technique in comparison to arc-cast-melt (AMC) route. Variation in Cr-distribution among different phases are found to be low in suction cast alloy, which along with grain refinement restricted Cr-depletion at the Zr{sub 2}(Fe, Cr)/Zr interfaces, prone to localized attack. Hence, SC alloy, compared to AMC alloy, showed lower current density, higher potential at the breakdown of passivity and higher corrosion potential during polarization experiments (carried out under possible geological repository environments, viz., pH 8, 5 and 1) indicating its superior corrosion resistance.

36 MATERIALS SCIENCE↗

Enhanced photocatalytic degradation of methylene blue: Preparation of TiO{sub 2}/reduced graphene oxide nanocomposites by direct sol-gel and hydrothermal methods

Highlights: • TiO{sub 2}-RGO nanocomposites presented, in all the cases studied, improved photocatalytic properties compared to bare TiO{sub 2}. • An optimal composition, in terms of TiO{sub 2}/RGO ratio was found in both series nanocomposites. • Nanocomposites of sol-gel method presented improved textural properties than those of hydrothermal method. • Optimization in the preparation, needed to obtain materials with finer properties for effective application in environmental. - Abstract: In this study, two different preparation methods of titanium dioxide nanoparticles/reduced graphene oxide nanocomposites were investigated using direct sol-gel method followed by hydrothermal treatment or simple hydrothermal route. A different amount of graphene (1- 20%) was mixed with TiO{sub 2} for both series of samples in order to improve the photocatalytic activity. The influence of the preparation method on the physico-chemical properties was established by different characterization methods and the photocatalytic degradation of methylene blue (MB) under UV light irradiation was used as test reaction. The highest photocatalytic activity was observed for the nanocomposites containing 10 wt% of graphene. The elimination of MB can reach 93% and 82% for the nanocomposites with 10 wt% graphene prepared by the sol-gel and hydrothermal methods, respectively. These photocatalysts are promising for practical application in nanotechnology.

36 MATERIALS SCIENCE↗

Dual-nitrogen-source engineered Fe–N x moieties as a booster for oxygen electroreduction

Metal–air batteries, particularly Zn–air batteries, have triggered considerable enthusiasm of communities due to their high theoretical power density. Developing highly active, cost-effective and alternative non-precious metal catalysts for the oxygen reduction reaction (ORR) is pivotal for popularizing zinc–air batteries. The rational design and synthesis of this type of catalyst are therefore critical, but it is still challenging to control the well-defined active sites as expected. In this paper, we report a dual-nitrogen-source mediated route for synergistically controlling the formation of active Fe–N x moieties that are embedded in the carbon matrix. The facile control of coordination structures of precursors by this dual-nitrogen-source approach is revealed to play a key role in this report. Impressively, the optimized dual-nitrogen-source derived catalyst (i.e. Fe–N–C-800) exhibits prominently enhanced ORR activity with a half-wave potential of 0.883 V in alkaline electrolyte, higher by 32 mV and 72 mV than those derived from individual nitrogen sources, which is also further evaluated in primary Zn–air batteries. The enhanced ORR activity of Fe–N–C-800 is attributed to the rich Fe–N x active sites derived from the dual-nitrogen-source approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Designing high-performance superconductors with nanoparticle inclusions: Comparisons to strong pinning theory

One of the most promising routes for achieving high critical currents in superconductors is to incorporate dispersed, non-superconducting nanoparticles to control the dissipative motion of vortices. However, these inclusions reduce the overall superconducting volume and can strain the interlaying superconducting matrix, which can detrimentally reduce T c . Consequently, an optimal balance must be achieved between the nanoparticle density n p and size d. Determining this balance requires garnering a better understanding of vortex–nanoparticle interactions, described by strong pinning theory. Here, we map the dependence of the critical current on nanoparticle size and density in (Y 0.77 , Gd 0.23 )Ba 2 Cu 3 O 7-δ films in magnetic fields of up to 35 T and compare the trends to recent results from time-dependent Ginzburg–Landau simulations. We identify consistency between the field-dependent critical current J c (B) and expectations from strong pinning theory. Specifically, we find that J c ∝ B -α , where α decreases from 0.66 to 0.2 with increasing density of nanoparticles and increases roughly linearly with nanoparticle size d/ξ (normalized to the coherence length). At high fields, the critical current decays faster (~B -1 ), suggesting that each nanoparticle has captured a vortex. When nanoparticles capture more than one vortex, a small, high-field peak is expected in J c (B). Due to a spread in defect sizes, this novel peak effect remains unresolved here. Finally, we reveal that the dependence of the vortex creep rate S on nanoparticle size and density roughly mirrors that of α, and we compare our results to low-T nonlinearities in S(T) that are predicted by strong pinning theory.

36 MATERIALS SCIENCE↗

Precursor prioritization for p-cymene production through synergistic integration of biology and chemistry

Abstract The strategy of synergistic application of biological and chemical catalysis is an important approach for efficiently converting renewable biomass into chemicals and fuels. In particular, the method of determining the appropriate intermediate between the two catalytic methods is critical. In this work, we demonstrate p -cymene production through the integration of biosynthesis and heterogenous catalysis and show how a preferred biologically derived precursor could be determined. On the biological side, we performed the limonene and 1,8-cineole production through the mevalonate pathway. Titers of 0.605 g/L and a 1.052 g/L were achieved, respectively. This difference is in agreement with the toxicity of these compounds toward the producing microorganisms, which has implications for subsequent development of the microbial platform. On the heterogeneous catalysis side, we performed the reaction with both biological precursors to allow for direct comparison. Using hydrogenation/dehydrogenation metals on supports with acid sites, both limonene and 1,8-cineole were converted to p -cymene with similar yields under equivalent reaction conditions. Thus, we could determine that the most promising strategy would be to target 1,8-cineole, the higher titer and lower toxicity bio-derived precursor with subsequent catalytic conversion to p -cymene. We further optimized the biological production of 1,8-cineole via fed-batch fermentation and reached the titer of 4.37 g/L which is the highest known 1,8-cineole titer from microbial production. This work provides a valuable paradigm for early stage considerations to determine the best route for the high-efficiency production of a target biobased molecule using an integration of biology and chemistry.

09 BIOMASS FUELS↗

STTR Phase I: Low-Cost, High-Accuracy, Whole-Building Carbon Dioxide Monitoring for Demand Control Ventilation

This STTR Phase I project assessed the feasibility of a new CO 2 sensing system optimized for low-cost, high-accuracy, whole-building monitoring for use in demand control ventilation. The focus was on the development of a wireless networking platform and associated firmware to provide signal conditioning and conversion, fault- and disruptiontolerant networking, and multi-hop routing at building scales to avoid wiring costs. Early exploration of a bridge (or “gateway”) to direct digital control services was also explored. Results of the project contributed to an improved understanding of a new electrochemical sensor for monitoring indoor CO 2 concentrations, as well as the electronics and networking infrastructure required to deploy those sensors at building scales. New knowledge was acquired concerning the sensor’s accuracy, environmental response, and failure modes, and the acquisition electronics required to achieve accuracy over a wide range of CO 2 concentrations. The project demonstrated that the new sensor offers repeatable correspondence with commercial optical sensors, with supporting electronics that offer gain accuracy within 0.5%, and acquisition accuracy within 1.5% across three orders of magnitude variation in generated current. Considering production, installation, and maintenance costs, the technology presents a foundation for achieving whole-building CO 2 sensing at a price point below $0.066 / sq-ft – meeting economic feasibility criteria established by the Department of Energy. The technology developed under this award addresses obstacles on the critical path to enabling whole-building CO 2 sensing and demand control ventilation in commercial retrofits, small commercial buildings, residential complexes, and other highpotential structures that have been slow to adopt these technologies. It presents an opportunity to significantly reduce energy use throughout the United States.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗