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At least 919 records · Page 51

An Extremely Stable and Soluble NH 2 -Substituted Anthraquinone Electrolyte for Aqueous Redox Flow Batteries

Aqueous redox flow batteries require long-term stable redox molecules for electrical energy storage. Anthraquinones, especially ether bond-decorated ones, experience two dominant decomposition pathways, including side-chain loss and anthrone formation. Here, with the aid of DFT calculations, we designed an anthraquinone (3-NH 2 -2-2PEAQ) bearing an ether substituent and a neighboring NH 2 group, which suppresses both of these decomposition mechanisms and exhibits a high solubility of 1.1 M. When paired with ferrocyanide in a full cell, this anthraquinone, at a concentration of 1.0 M, can operate at greater than 1 V with an extremely low capacity fade rate of 0.01%/day and a Coulombic efficiency above 99.8% while cycling for over a month. The synergistic effects of the ether and parent amino substituents are extremely sensitive to the precise substitution pattern of the anthraquinone. This study demonstrates the effectiveness of the judicious use of DFT-based prediction in rapidly identifying promising candidate electrolytes from a large chemical space.

25 ENERGY STORAGE↗

Mixed gain detector configurations for time-resolved X-ray solution scattering

X-ray detection at X-ray free-electron lasers is challenging in part due to the XFEL's extremely short and intense X-ray pulses. Experimental measurements are further complicated by the large fluctuations inherent to the self-amplified spontaneous emission process producing the X-rays. At the Linac Coherent Light Source the ePix10ka2M detector offers multiple gain modes, and auto-ranging between these, to increase the dynamic range while retaining low noise. For diffuse scattering techniques, such as time-resolved X-ray solution scattering, where the shape of the scattering pattern largely does not change between exposures, a fixed mix of different gain modes offers many of the same advantages as auto-ranging. We find that configuring individual ASICs in separate gain modes does not impact the intensity linearity of the gain response and has a limited effect on the effective dynamic range in regions with different gain mode settings while avoiding the complexities of auto-ranging. Small (<5%) non-linear gain contributions arise when pixels on the same ASIC are configured in different gain modes. We present a configuration scheme that is designed to select the optimal mixed gain configuration to minimize effects of saturation in the high-/medium-gain region, while maximizing the number of pixels with higher gain to improve the signal-to-noise ratio.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

jialiu232/MetaFunPrimer_paper_info

Genes belonging to the same functional group may include numerous and variable gene sequences, making characterizing and quantifying difficult. Therefore, high-throughput design tools are needed to simultaneously create primers for improved quantification of target genes. We developed MetaFunPrimer, a bioinformatic pipeline, to design primers for numerous genes of interest. This tool also enables gene target prioritization based on ranking the presence of genes in user-defined references, such as environment-specific metagenomes. Given inputs of protein and nucleotide sequences for gene targets of interest and an accompanying set of reference metagenomes or genomes, MetaFunPrimer generates primers for ranked genes of interest. To demonstrate the usage and benefits of MetaFunPrimer, a total of 78 primer pairs were designed to target observed ammonia monooxygenase subunit A (amoA) genes of ammonia-oxidizing bacteria (AOB) in 1,550 publicly available soil metagenomes. We demonstrate computationally that these amoA-AOB primers can cover 94% of the amoA-AOB genes observed in the 1,550 soil metagenomes compared with a 49% estimated coverage by previously published primers. Finally, we verified the utility of these primer sets in incubation experiments that used long-term nitrogen fertilized or unfertilized soils. High-throughput quantitative PCR (qPCR) results and statistical analyses showed significant differences in relative quantification patterns between the two soils, and subsequent absolute quantifications also confirmed that target genes enumerated by six selected primer pairs were significantly more abundant in the nitrogen-fertilized soils. This new tool gives microbial ecologists a new approach to assess functional gene abundance and related microbial community dynamics quickly and affordably.

Liu, Jia↗

Metaoptics Enabled Multifunctional Imaging

Despite the fact that most microorganisms occupy two- and three-dimensional space in heterogeneous arrangements and in proximity to other microorganisms of different species, much of our current knowledge about their metabolic processes is derived from homogenizing, then analyzing, the chemical content of cultures containing a single microbial species. This project addressed this fundamental dichotomy by developing a set of optical imaging principles combining multiple new technologies. The imaging strategies developed in this project combine metaoptics structures with active in situ nanoscale control of the chemical environment and applied them to a microbial system, Myxococcus xanthus, with particular relevance to the DoE mission. The combination of metaoptical architectures and nanoscale control over the molecular environment enables: (a) precise control over the electromagnetic (EM) field at length scales smaller than the wavelength of light; (b) control of the interaction of the EM field with critical molecular systems in DOE relevant microbes; (c) control over the chemical environment – especially the presence and quantity of reactive oxygen species (ROS) that can affect redox homeostasis; and (d) the ability to ask new kinds of questions not accessible to ‘omics’ approaches or standard methods of biological imaging. These capabilities are applicable to detailed studies of metabolic pathways in microbes and to lignocellulosic biomass deconstruction. To accomplish these objectives, we pursued two over-arching technical goals: (1) the development of new metaoptics-enabled approaches to imaging and spectroscopic characterization; and (2) the development of tools to control the chemical environment of a microbial sample with nanometer-scale precision. Goal 1 was addressed through the design, fabrication, and characterization of new metasurfaces capable of super-resolution imaging through extreme confinement of the optical field. Goal 2 was addressed by controlling the redox potential on the nanoscale in microbial communities and characterizing their effect on intrinsic bacterial fluorophores which act as molecular sentinels and through characterization of soluble factors secreted by Myxococcus xanthus by confocal Raman imaging. The optical imaging/sensing approaches developed here make it possible to use these powerful new imaging and sensing modalities in metabolic studies by making it possible to visualize and track the spatial and temporal expression patterns of natural or engineered pathways in microorganisms.

09 BIOMASS FUELS↗

Critical Literature Review of Quantitative Sustainability Assessment Methods for the Circular Economy

The circular economy (CE) has been proposed to be an operational framework for sustainable development that decouples economic growth from resource consumption. The CE ambition is to maximize the retention of value in products, materials, and resources in the economy over time with the help of CE strategies such as selling a service rather than a product, reusing and repairing products or their components, and recycling. The social, economic, and environmental performances of CE strategies need to be measured against their linear counterparts to avoid strategies that increase circularity but have other unintended externalities. However, there is currently no tool specifically designed to compare circular to linear systems and, thus, various methods from different fields have been applied. This session aims at reviewing, contrasting, and critiquing different methods that have been applied to assess the CE until now, along with an up to date state of the science in this field. Methods from the industrial ecology field have most often been applied to study the CE. However, the transition to CE involves both technological improvements as well as social changes. New business models such as collaborative consumption models (e.g., Uber or Airbnb) are examples of the new patterns of production and consumption of the CE, which may be difficult to analyze from a purely industrial ecology perspective. Methods from complexity science and humanities could therefore complement the industrial ecology perspective to extend the scope of the analysis. Such an approach could also answer a longstanding criticism of the CE which, in contrast with sustainability, solely focuses on the environment and the economy. Moreover, the hybridization of two or more existing methods can yield additional capabilities, which may enable the exploration of additional CE-related research questions. The 90 minutes session will have several presentations and conclude with a moderated, interactive panel discussion on how methods from different fields could be combined to harness their relative strengths.

circular economy↗

Symmetry-breaking in patch formation on triangular gold nanoparticles by asymmetric polymer grafting

Synthesizing patchy particles with predictive control over patch size, shape, placement and number has been highly sought-after for nanoparticle assembly research, but is fraught with challenges. Here we show that polymers can be designed to selectively adsorb onto nanoparticle surfaces already partially coated by other chains to drive the formation of patchy nanoparticles with broken symmetry. In our model system of triangular gold nanoparticles and polystyrene-b-polyacrylic acid patch, single- and double-patch nanoparticles are produced at high yield. These asymmetric single-patch nanoparticles are shown to assemble into self-limited patch-patch connected bowties exhibiting intriguing plasmonic properties. To unveil the mechanism of symmetry-breaking patch formation, we develop a theory that accurately predicts our experimental observations at all scales—from patch patterning on nanoparticles, to the size/shape of the patches, to the particle assemblies driven by patch-patch interactions. Both the experimental strategy and theoretical prediction extend to nanoparticles of other shapes such as octahedra and bipyramids. Our work provides an approach to leverage polymer interactions with nanoscale curved surfaces for asymmetric grafting in nanomaterials engineering.

42 ENGINEERING↗

Tailored topotactic chemistry unlocks heterostructures of magnetic intercalation compounds

The construction of thin film heterostructures has been a widely successful archetype for fabricating materials with emergent physical properties. This strategy is of particular importance for the design of multilayer magnetic architectures in which direct interfacial spin-spin interactions between magnetic phases in dissimilar layers lead to emergent and controllable magnetic behavior. However, crystallographic incommensurability and atomic-scale interfacial disorder can severely limit the types of materials amenable to this strategy, as well as the performance of these systems. Here, we demonstrate a method for synthesizing heterostructures comprising magnetic intercalation compounds of transition metal dichalcogenides (TMDs), through directed topotactic reaction of the TMD with a metal oxide. The mechanism of the intercalation reaction enables thermally initiated intercalation of the TMD from lithographically patterned oxide films, giving access to a family of multi-component magnetic architectures through the combination of deterministic van der Waals assembly and directed intercalation chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stiffness anisotropy coordinates supracellular contractility driving long-range myotube-ECM alignment

The ability of cells to organize into tissues with proper structure and function requires the effective coordination of proliferation, migration, polarization, and differentiation across length scales. Skeletal muscle is innately anisotropic; however, few biomaterials can emulate mechanical anisotropy to determine its influence on tissue patterning without introducing confounding topography. Here, we demonstrate that substrate stiffness anisotropy coordinates contractility-driven collective cellular dynamics resulting in C2C12 myotube alignment over millimeter-scale distances. When cultured on mechanically anisotropic liquid crystalline polymer networks (LCNs) lacking topography, C2C12 myoblasts collectively polarize in the stiffest direction. Cellular coordination is amplified through reciprocal cell-ECM dynamics that emerge during fusion, driving global myotube-ECM ordering. Conversely, myotube alignment was restricted to small local domains with no directional preference on mechanically isotropic LCNs of the same chemical formulation. These findings provide valuable insights for designing biomaterials that mimic anisotropic microenvironments and underscore the importance of stiffness anisotropy in orchestrating tissue morphogenesis.

59 BASIC BIOLOGICAL SCIENCES↗

Interpreting and Accelerating Transformers for Jet Tagging

Attention-based transformers are ubiquitous in machine learning applications from natural language processing to computer vision. In high energy physics, one central application is to classify collimated particle showers in colliders based on the particle of origin, known as jet tagging. In this work, we study the interpretatbility and prospects for acceleration of Particle Transformer (ParT), a state-of-the-art model, leverages particle-level attention to improve jet-tagging performance. We analyzing ParT's attention maps and particle-pair correlations in the eta-phi plane, revealing intriguing features, such as a binary attention pattern that identifies critical substructure in jets. These insights enhance our understanding of the model's internal workings and learning process and hint at ways to improve its efficiency. Along these lines, we also explore low-rank attention, attention alternatives, and dynamic quantization to accelerate transformers for jet tagging. With quantization, we achieve a 50% reduction in model size and a 10% increase in inference speed without compromising accuracy. These combined efforts enhance both the performance and the interpretability of transformers in high-energy physics, opening avenues for more efficient and physics-driven model designs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurement of Convective Heat Transfer Coefficients with Supercritical CO2 in Novel Additively Manufactured Helically Patterned Pin Fin Tubes Using the Wilson Plot Technique

This paper describes the measurement of convective heat transfer coefficients and friction factors for sCO2 flowing in pin-fin patterned pipes in the Heat Exchange and Experimental Testing (HEET) facility at the US DoE’s National Energy Technology Laboratory (NETL) in Morgantown, WV. The measurement procedures in the HEET rig were validated by conducting benchmark tests with smooth stainless-steel tube and comparing the results with published correlations for Nusselt number (Nu) and friction factor. Over typical Reynolds number range in sCO2, the measured Nu and friction factors were within 7% of classical correlations for smooth tube flow.The candidate pin fin patterned pipes were additively manufactured (AM) at the Oak Ridge National Laboratory. The pins were circular or elliptical in cross-section. Pin length to diameter aspect ratios were 1.33 and 2, while the pin diameter to tube diameter ratio was 0.188 and 0.125. Tests were performed for ReD varying from 6.9×104 to 2.2×105 and at conditions equivalent to the low pressure outlet (8.69 MPa, 361 K) of the low temperature recuperator (LTR) in an indirect sCO2 power cycle. The Wilson plot technique was utilized to measure the bulk heat transfer coefficients.For the better performing design (tube A, pin length to tube diameter ratio: 1.33, pin diameter to tube diameter ratio: 0.188), the local heat transfer coefficient increased by 112% relative to the Dittus-Boelter correlation at the LTR low pressure outlet. This corresponded to a 282% increase in the product of the heat transfer coefficient and the surface area. Large pressure drops across the test articles were observed.

Searle, Matthew↗

First-Principles Modeling of Sodium Ion and Water Intercalation into Titanium Disulfide Interlayers for Water Desalination

Recent experiments revealed the possibility of using titanium disulfide (TiS 2 ) as the cathode material in capacitive deionization (CDI) devices for water desalination. Although it performed stably up to 70 cycles with a salt removal capacity of 14 mg/g (corresponding to a sodium ion removal capacity of 35.8 mg/g) at high molar concentration (600 mM NaCl), the maximum capacity of TiS 2 as a CDI electrode was much lower (~70 mAh/g) than as a supercapacitor (239 mAh/g). Understanding why the ion capacities of these two configurations of the same material differ will entail elucidating detailed charge/discharge mechanisms at the atomic scale. Here, we present density functional theory simulations of sodium intercalation into TiS 2 interlayers in order to gain such understanding. We systematically investigated TiS 2 stacking patterns and ion intercalation sites, energetics of the intercalated compounds, and phase transformation during sodium intercalation. The calculated structural evolution and capacitance–voltage curve agree quite well with previous measurements. We conclude that the different maximum capacities of TiS 2 measured in aqueous and dry environments originate from weaker interlayer interactions with respect to shear strain after ~33% intercalation of Na + –H 2 O pairs, which is detrimental to the mechanical stability of TiS 2 . In conclusion, this study sheds light on the underlying mechanisms of ion intercalation into layered materials and contributes to understanding requirements for future design and optimization of CDI electrode materials for water desalination.

36 MATERIALS SCIENCE↗

Ibis Networks/WattIQ (IN2 Final Report)

Ibis Networks is a full-stack cleantech company that provides plug-level energy monitoring and control to solve energy and asset management problems for the enterprise. During DATES – DATES, an NREL research team worked with the Ibis team to validate their product, the InteliSocket. The Ibis InteliSocket is a pass-through plug-load energy monitor and controller that is designed to reduce energy wasted by common 120 V plug-in devices in commercial office buildings, such as computer peripherals, conference room AV equipment, and break-room appliances. The system can shut off supply power to these end uses via remote control, manual switches, pre-set schedules, or automated control algorithms. The scope of this IN2 project was the development and refinement of “smart” learning behavior algorithms (LBAs), which could help installation processes and dramatically expand the sockets’ capabilities and energy-saving potential by suggesting suitable control schedules that are based on monitored use patterns. While Ibis has the analytical and software expertise for algorithm development, the lack of test data, both in a controlled laboratory setting and in real-life deployment scenarios, represented a key barrier toward commercialization of the product. Assistance through the IN2 program provided an opportunity to conduct the needed “trial and error” algorithm development. The project included baseline field-data collection, laboratory testing, and field validation components, all of which were conducted at the NREL campus between April 2017 and July 2019.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Substation Secondary Asset Health Monitoring and Management System (SSHM)

Electric Power Group, LLC (EPG) was awarded DOE OE0000850 to design, develop, and demonstrate a real-time software application for substation secondary equipment health monitoring and management at host utility American Electric Power (AEP), a cost share partner. This project addresses the need for monitoring substation equipment health and providing operators with tools to identify and take pre-emptive action to avoid catastrophic equipment failure. By monitoring synchrophasor data in real time, data anomalies that indicate potential asset failure can be detected and alerts can be sent to operators in time to take corrective actions. EPG developed two data driven algorithms to identify abnormal equipment signature patterns as well as a method using substation linear state estimation (SLSE). The software has been deployed on hardened PC’s and tested and validated for cost share partner AEP’s substations - 138kV and 765 kV. The SSHM software has been accepted by AEP and final demonstration of DOE - OE0000850 for AEP and DOE was successfully completed on March 17th, 2020. EPG developed the Substation Secondary Asset Health Monitoring (SSHM) Platform to analyze equipment failure signatures in PMU data and alert substation personnel when pre-emptive inspection, repairs and other actions are warranted to prevent potential catastrophic failures. This is the first system that automatically monitors the health of substation secondary assets and alerts users to emerging failures using synchrophasor measurements. SSHM uses high resolution PMU data from PTs, CTs, and CCVTs to analyze equipment signatures and identify anomalies that are precursor indicators of potential equipment failure. When an anomaly is detected, there is a likelihood of potential failure of monitored equipment, the system alerts the user with visual alarms including alarm trend charts and indicator lights on a oneline diagram of the substation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

$\mathrm{SageNet}$: Fast Neural Network Emulation of the Stiff-amplified Gravitational Waves from Inflation

Accurate modeling of the inflationary gravitational waves (GWs) requires time-consuming, iterative numerical integrations of differential equations to take into account their backreaction on the expansion history. To improve computational efficiency while preserving accuracy, we present the Stiff-amplified Gravitational-wave Emulator Network (SageNet), a deep learning framework designed to replace conventional numerical solvers (code available at https://github.com/YifangLuo/SageNet). SageNet employs a long short-term memory architecture to emulate the present-day energy density spectrum of the inflationary GWs with possible stiff amplification, Ω GW (f). Trained on a data set of 25,689 numerically generated solutions, SageNet allows accurate reconstructions of Ω GW (f) and generalizes well to a wide range of cosmological parameters; 90.9% of the test emulations with randomly distributed parameters exhibit errors of under 4%. In addition, SageNet demonstrates its ability to learn and reproduce the artificial, adaptive sampling patterns in numerical calculations, which implement denser sampling of frequencies around changes in spectral indices in Ω GW (f). The dual capability of learning both physical and artificial features of the numerical GW spectra establishes SageNet as a robust alternative to exact numerical methods. Finally, our benchmark tests show that SageNet reduces the computation time from tens of seconds to milliseconds, achieving a speedup of ∼10 4 times over standard CPU-based numerical solvers with the potential for further acceleration on GPU hardware. These capabilities make SageNet a powerful tool for accelerating Bayesian inference procedures for extended cosmological models. In a broad sense, the SageNet framework offers a fast, accurate, and generalizable solution to modeling cosmological observables whose theoretical predictions demand costly differential equation solvers.

Astronomy data modeling↗

Quantifying and Understanding the Access Time to Dockless Micromobility: A Case Study in Washington, D.C.

Micromobility has been widely deployed in many cities. Similar as how access time/distance affects the travel demand to use public transit and informs transit system design, access time/distance to micromobility service measures its service efficiency and also serves as an equity indicator to inform city agencies from a regulation perspective. Though there is an increasing need to understand it, access to micromobility has not been sufficiently studied. This paper developed a framework to quantity the access time to dockless micromobility service (i.e., the minimum time needed to walk to reach the closest dockless micromobility vehicles). Based on the real-time vehicle location data collected from Washington, DC, this research quantified the access time to dockless micromobility, analyzed its spatial and temporal variation patterns and investigated its relationship with socio-demographic variables (i.e., population density, employment density and low-income population). The results revealed that the access time to dockless micromobility ranges between 0 to 4 minutes with the most frequently observed range of 0.5 to 1 minutes, and the city center area tends to have shorter access time than the outskirts areas. Results also indicate a quite stable access time level in DC with access time standard deviation of 0.2 to 0.5 minutes. After correlating the access time at census-block-group level with socio-demographic data, it was discovered that shorter access time usually aligns with larger population and employment density, and the proportion of low-income population was found not helpful with explaining the access time variation, which indicating a relatively equitable micromobility program.

access time↗

Modeling the co-assembly of binary nanoparticles

Abstract In this work, we present a binary assembly model that can predict the co-assembly structure and spatial frequency spectra of monodispersed nanoparticles with two different particle sizes. The approach relies on an iterative algorithm based on geometric constraints, which can simulate the assembly patterns of particles with two distinct diameters, size distributions, and at various mixture ratios on a planar surface. The two-dimensional spatial-frequency spectra of the modeled assembles can be analyzed using fast Fourier transform analysis to examine their frequency content. The simulated co-assembly structures and spectra are compared with assembled nanoparticles fabricated using transfer coating method are in qualitative agreement with the experimental results. The co-assembly model can also be used to predict the peak spatial frequency and the full-width at half-maximum bandwidth, which can lead to the design of the structure spectra by selection of different monodispersed particles. This work can find applications in fabrication of non-periodic nanostructures for functional surfaces, light extraction structures, and broadband nanophotonics.

Mohanty, Saurav (ORCID:0009000302592855)↗

Accuracy Enhancement of Nuclear Power Plant Simulators Utilizing High Accuracy Simulation Predictions

More recently, reactor core simulators for core designs associated with commercial nuclear power plants that utilize what is believed to be higher fidelity models have been developed. Features such as neutronics models that utilize transport equation solvers with fine spatial meshes and many energy-groups, thermal-hydraulic models that utilize sub-channel solvers with fine spatial mesh and capable of treating a wide range of fluid conditions, and fuel-coolant chemistry interaction models capable of treating CRUD deposition are to be found in these higher fidelity core simulators. These reactor core simulators require access to higher performance computers, characterized by many processors, cores and large memory. So associated with utilization of these simulators is access to high performance computers and ability to accommodate in one’s workflow longer execution times. By contrast, currently used core simulators by the nuclear industry can execute on engineering workstations and have execution times of seconds to minutes. The desirability for having short execution times is not only desired for support of time critical tasks but supports the mental process of decision making by engineers. The goal of the work reported upon here has the objective of retaining the fidelity of higher fidelity models while retaining the ability to utilize engineering workstations. Beyond the core simulator goal, additional goals of this work include incorporating the just described core simulator capability into a Nuclear Steam Supply System (NSSS) simulator, and to incorporate the resulting capability into an environment supportive of design and operational decision making associated with nuclear power stations. The model selected for the core neutronics model is the NESTLE code, for the core thermal-hydraulic model is the CTF code utilizing coarse mesh, and for the NSSS model is the RELAP5-3D code. WSC’s proprietary 3KEYMASTERTM platform is being used to provide software coupling, user interface, visualization, and reporting. The NESTLE core neutronics simulator was first integrated with the CTF core thermal-hydraulic simulator using CTF developed communication commands which are also used for CTF to communicate with RELAP5-3D under WSC’s proprietary 3KEYMASTERTM platform. To assure NESTLE prediction consistency with higher fidelity core neutronic simulators, buffer codes have been created to automatically generate from output files written by the VERA core simulator the NESTLE nodal neutronic parameter’ library, geometry, and pin-power reconstruction input files, thereby avoiding a number of challenges associated with utilizing lattice physics codes and providing consistency with VERA predictions. To treat absorber rod effects a multi-set library is utilized, where a set refers to a specific absorber rod fully inserted pattern. A coarse spatial mesh CTF model was developed with features added that support using CTF as envisioned in the engineering quality simulator. A hybrid meshing approach was implemented to allow for automated construction of models with mixed levels of refinement. Specifically, a core model could resolve some assemblies at a nodal level (4 subchannels per assembly) and others at a pin-resolution (one subchannel per coolant subchannel in the assembly). The intention is that this will allow for better resolution of limiting conditions such as DNBR and PCT, which are based on local rod and subchannel conditions. Further development was done of features that enhance the capabilities for the envisioned engineering quality simulator that has been developed, but now for RELAP-3D. The RELAP5-3D code development includes ability to model more than 999 components and the addition of the cross-channels turbulence mixing model and the void drift model that are implemented in CTF, aiming to achieve closer prediction agreement of the two codes for transient simulations, specifically, more accurate matches of the overall mass, momentum, and energy exchanges of both the liquid and gas phases between the neighboring core assemblies. Graphics were also developed for the Instructor Station for this project under WSC’s proprietary 3KEYMASTERTM platform to facilitate design and operational decision making.

42 ENGINEERING↗