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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

ADAM: A web platform for graph-based modeling and optimization of supply chains

Modeling and optimization are essential tasks that arise in the analysis and design of supply chains (SCs). SC models are essential for understanding emergent behavior such as transactions between participants, inherent value of products exchanged, as well as impact of externalities (e.g., policy and climate) and of constraints. Unfortunately, most users of SC models have limited expertise in mathematical optimization, and this hinders the adoption of advanced decision-making tools. Here, in this work, we present ADAM, a web platform that enables the modeling and optimization of SCs. ADAM facilitates modeling by leveraging intuitive and compact graph-based abstractions that allow the user to express dependencies between locations, products, and participants. ADAM model objects serve as repositories of experimental, technology, and socio-economic data; moreover, the graph abstractions facilitate the organization and exchange of models and provides a natural framework for education and outreach. Here, we discuss the graph abstractions and software design principles behind ADAM, its key functional features and workflows, and application examples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

A contribution to the conceptualisation of quality in impact assessment

Quality is much sought after in, and a basic foundation for, good impact assessment (IA). However, the term is rarely defined, has an uncertain relationship with IA effectiveness, and it means different things to different stakeholders, which can lead to debates over the legitimacy associated with an IA process. Thus, IA quality needs conceptualising to position research and practice within broader understandings. This paper contributes to this conceptualisation by identifying nine dimensions of quality through a process of literature review drawing on three fields of study in which quality and quality management have already been debated and conceptualised: education; health care; and business. This approach sidesteps the plural views on quality existing within the field of IA itself which might otherwise bias the identification of quality dimensions. We therefore propose that the dimensions of IA quality are: Efficiency; Optimacy; Conformance; Legitimacy; Equity; Capacity Maintenance; Transformative Capacity; and Quality Management. A literature review of IA research and practice confirms the relevance of the identified quality dimensions to IA. We identify, to an extent, the relationship between quality and effectiveness. Quality aligns with procedural and transactive effectiveness, partly aligns with normative effectiveness and is distinct from, but helps to deliver, substantive effectiveness.

42 ENGINEERING↗
DOE OSTI2018

Are current effectiveness criteria fit for purpose? Using a controversial strategic assessment as a test case

Highlights: • The effectiveness framework of Bond et al. (2015) is tested on a case study. • The strategic assessment of the proposed Browse LNG Precinct is evaluated. • The effectiveness framework is modified as a result of the analysis. • “Legitimacy” encompasses both pluralism and normative effectiveness. • Substantive effectiveness should include consideration of unintended consequences. - Abstract: The aim of this paper is to test the broader utility of the sustainability assessment effectiveness framework of Bond et al. (2015) by applying it to a controversial strategic assessment case study. The effectiveness framework comprises six dimensions: procedural effectiveness, substantive effectiveness, transactive effectiveness, normative effectiveness, pluralism, and knowledge and learning. It was originally developed to evaluate sustainability assessment at a system-wide level and it has not been previously applied to a specific case study. The analysis was conducted through document review and the first-hand experience of two of the authors who were involved in the case study in different capacities. The case study selected was the strategic assessment of the proposed Browse Liquefied Natural Gas (LNG) Precinct in Western Australia, which was conducted over the period 2007–2015 under the strategic assessment provisions of both the Western Australian and Australian Commonwealth environmental legislation. The framework provided a useful structure within which this complex case study could be explored, its strengths and weaknesses brought to light, and the interactions between the dimensions highlighted. We also found opportunities for refinement of the framework. As a result of this analysis we propose to replace the final three dimensions of the framework with legitimacy, where a legitimate process is one which all stakeholders agree is fair and which delivers an acceptable outcome for all parties, though we acknowledge the need for further conceptualisation of this dimension. We also suggest that the concept of substantive effectiveness should be expanded to incorporate the unintended consequences of impact assessment. Our research thus makes both a useful addition to the literature already published on the Browse case study, as well as to the literature on impact assessment effectiveness.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Power allocation by load aggregator with heterogeneous loads using weighted projection

With the recently increasing adoption of transactive energy markets, the role of a load aggregator is becoming increasingly important. Among the many tasks of an aggregator, the task of managing the electricity consumption among a group of grid-interactive efficient buildings according to the demand on the grid is taken up. Specifically, here, the task of allocating a certain amount of power among the participating customers while respecting their preferences and comfort is considered. Modeling this as an aggregate flexibility, the virtual battery conditions that are employed to verify the feasibility of a candidate power profile are derived. A feasible power profile, when allocated, satisfies specified comfort bands. To determine the ideal power requirement of the loads, the model-free control method is employed. The feasible power profile is allocated by embedding the customers’ preferences through weights, posing the power constraint as a hyperplane, and employing a weighted projection from the ideal power requirements onto the constraint plane to solve the considered task. The proposed method is computationally efficient and scalable to any number of heterogeneous thermostatically controlled loads in buildings.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Coupling computational fluid dynamics with the high resolution rapid refresh model for forecasting dynamic line ratings

This study looks at forecasted dynamic line ratings in southern Idaho by using data from the High Resolution Rapid Refresh (HRRR) model for forecasted weather conditions. The HRRR model can provide accurate 18- hour forecasts with a 15-minute temporal resolution. Typical static ratings used for over head transmission lines use overly conservative assumptions for local weather conditions, such as using the maximum solar irradiance or temperature measured during the summer combined with low wind speed for an entire season. The HRRR forecast model used here has a high spatial resolution to provide local forecast conditions along the entire length of a transmission line. The area that is of interest in this study is in southern Idaho spanning a total of 15,000 square kilometers. The forecasted weather data is coupled with a computational fluid dynamics model of the wind in the region to improve the resolution to an even finer scale for resolving local convective cooling rates on each individual transmission line midpoint span. This high fidelity approach can be used to find the minimum ampacity limit across all given midpoints of a transmission line to determine the absolute minimum to be used for the line rating. The ability to increase the line rating above the conservative static approach with the forecasted weather data provides a large potential to alleviate congestion and provide data for the utility market transactions. Furthermore, this study shows that for the region of interest, using forecasted weather data coupled with CFD modeling will calculate DLR ampacity rating above static about 90% of the time, with only a small relative error in the forecasted ampacity over time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Economic dispatch for electricity merchant with energy storage and wind plant: State of charge based decision making considering market impact and uncertainties

Here this paper investigates how the market impact of electricity merchants and uncertainty of wind generation affect their co-optimized scheduling policy, specifically for merchants who have both energy storage and wind plants. In the existing literature, merchants' trading actions are usually assumed not to affect market prices; however, a large-scale energy storage merchant's actions can affect market prices. To this end, we approximate the electricity price by a linear function of the quantity of power traded by the merchant in the reward function to achieve decision-making incorporating the market impact. This paper utilizes the dynamic programming approach to analyze merchants' optimal multi-period decision-making incorporating market impact, uncertain wind generation, and energy storage constraints. First, our results demonstrate that for a merchant with co-located energy storage facilities and wind power plants, the energy storage's feasible state of charge (SOC) range can be segmented into four possible sub-ranges by three analytically developed SOC reference points. The unique optimal trading decision can be achieved by comparing the current energy inventory and the SOC references of the next period. Second, our results show that market impact and uncertainties substantially change the optimal storage scheduling policy by impacting the values of the reference points. To mitigate the negative effect of the merchant's market impact on buying and selling actions, the merchant may reduce the amount of generating or pumping electricity each period to maximize profit. Moreover, we identify and investigate the trade-off between market price and transaction quantity. Our findings provide co-optimized scheduling guidance for electricity merchants with co-located energy storage and renewable power plants systems.

17 WIND ENERGY↗
DOE OSTI2022

Enhanced deep neural networks with transfer learning for distribution LMP considering load and PV uncertainties

As the flexibility of generation and demand increases in distribution systems, the residential loads are emerging as a promising means to participate in demand response and the transactive energy market. Market pricing is an instrumental mechanism for the distribution system operator to exploit the full potential of the flexible resources. The distribution locational marginal price (DLMP) can be used to guide the residential load consumption. This type of market signal helps the distribution system operator to optimize the scheduling of all resources while satisfying related network constraints through a day-ahead market. However, solving the optimization problem for large-scale systems can be computationally expensive. To address the scalability and practicability limitations of the DLMP framework, a learning-based approach is proposed in this paper to complement the day-ahead distribution market framework. Here, the proposed approach combines long short-term memory and transfer learning to develop deep neural network that can capture the spatial–temporal correlation of the input data. The model can determine the optimal DLMP for each node in a distribution system without the system parameters required to formulate the optimization problem. Testing results on IEEE 33-bus and 123-bus systems show that the proposed approach can generate a comparable DLMP against the optimization solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Potential Benefits in Remapping the Special Flood Hazard Area: Evidence from the U.S. Housing Market

A typical U.S. homebuyer's understanding of whether a property faces flood risk is based on whether the property is located inside the National Flood Insurance Program's (NFIP) Special Flood Hazard Area (SFHA). The SFHA boundary, however, may bias homebuyers’ perceptions of flood risk relative to unobserved true risk because the SFHA is an incomplete, and sometimes inaccurate, representation of flood hazards. Using a national dataset of property transactions, flood hazard data from the First Street Foundation, state-level measures of flood disclosure laws, and a spatially restricted triple-difference design, we distinguish capitalization effects of policy-driven (SFHA) versus quasi-objective (First Street) indicators of flood hazard. We identify these effects by assessing thousands of local spatial interactions between property SFHA designations, measures of quasi-objective flood hazard, and being in a state that mandates flood history disclosures. Being inside the SFHA generates a risk discount, but the signal is muted relative to underlying hazard exposure. Further, the SFHA signal can result in inefficient discounts for properties erroneously mapped in the SFHA. Disclosure requirements about flood history accentuate price effects for hazardous properties and result in more adequate risk internalization. In the absence of disclosures, however, we find either no or a weak risk signal for houses outside the SFHA that face flood hazard. Our results highlight potential benefits of updating SFHA boundaries to include all houses that may experience flooding, and argue in favor of requiring flood-related disclosures from sellers to improve the market's ability to internalize flood risk.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Dynamics of virtual water networks: Role of national socio-economic indicators across the world

Intensified water usage due to rapid industrialization is often dictated by economic policies based on monetary growth rather than sustainable use of environmental resources. In addition, interdependence within economic sectors further interweaves water usage through product transactions, which further makes it difficult to quantify the dynamics of hydro-economic systems at regional, national and global scale. In this study, we investigated the dynamics of domestic virtual water networks (VWN) of 189 countries based on concept of information theory by quantifying network metrics that describes VWN flow capacity, robustness, efficiency and flexibility. These networks represent virtual water interconnected through economic sectors within a specified country built based on environmentally extended multi region input output (EE-MRIO) approach. We further estimated trends associated with network metrics, as well as coupling intensity between metrics with respect to socio-economic indicators, such as, population, Gross Domestic Product (GDP) and Gross National Income (GNI). It was observed that capacity and flexibility of VWNs are strongly and positively correlated indicating that a high capacity VWN can be more flexible. Our results also indicate that, in general a higher percentage of developing countries (i.e. both least developing and developing nations) have exhibited increasing trends in capacity, robustness, efficiency and flexibility of VWN compared to developed nations. It was revealed that the dynamics of VWNs are positively coupled with socio-economic growth for few countries, which indicates the sustainable behavior of VWN with socio-economic growth. Our results argue that the information theory-based metrics by embedding water footprints can holistically capture sustainability aspect of the VWN dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Targeted energy transfer in laminar vortex-induced vibration of a sprung cylinder with a nonlinear dissipative rotator

We computationally investigate the dynamics of a linearly-sprung circular cylinder immersed in an incompressible flow and undergoing transverse vortex-induced vibration (VIV), to which is attached a rotational nonlinear energy sink (NES) consisting of a mass that freely rotates at constant radius about the cylinder axis, and whose motion is restrained by a rotational linear viscous damper. The inertial coupling between the rotational motion of the attached mass and the rectilinear motion of the cylinder is “essentially nonlinear”, which, in conjunction with dissipation, allows for one-way, nearly irreversible targeted energy transfer (TET) from the oscillating cylinder to the nonlinear dissipative attachment. At the intermediate Reynolds number , the NES-equipped sprung cylinder undergoes repetitive cycles of slowly decaying oscillations punctuated by intervals of chaotic instabilities. During the slowly decaying portion of each cycle, the dynamics of the cylinder is regular and, for large enough values of the ratio of the NES mass to the total mass (i.e., NES mass plus cylinder mass), can lead to significant vortex street elongation with partial stabilization of the wake. As approaches zero, no such vortex elongation is observed and the wake patterns appear similar to that for a sprung cylinder with no NES. Here we apply proper orthogonal decomposition (POD) to the velocity flow field during a slowly decaying portion of the solution and show that, in situations where vortex elongation occurs, the NES, though not in direct contact with the surrounding fluid, has a drastic effect on the underlying flow structures, imparting significant and continuous passive redistribution of energy among POD modes. We construct a POD-based reduced-order model for the lift coefficient to characterize energy transactions between the fluid and the cylinder throughout the slowly decaying cycle. We introduce a quantitative signed measure of the work done by the fluid on the cylinder over one quasi-period of the slowly decaying response and find that vortex elongation is associated with a sign change of that measure, indicating that a reversal of the direction of energy transfer, with the cylinder “leaking energy back” to the flow, is responsible for partial stabilization and elongation of the wake. We interpret these findings in terms of the spatial structure and energy distribution of the POD modes, and relate them to the mechanism of transient resonance capture into a slow invariant manifold of the fluid–structure interaction dynamics.

42 ENGINEERING↗
DOE OSTI2017

A model for simulating adaptive, dynamic flows on networks: Application to petroleum infrastructure

Simulation models can greatly improve decisions meant to control the consequences of disruptions to critical infrastructures. We describe a dynamic flow model on networks purposed to inform analyses by those concerned about consequences of disruptions to infrastructures and to help policy makers design robust mitigations. We conceptualize the adaptive responses of infrastructure networks to perturbations as market transactions and business decisions of operators. We approximate commodity flows in these networks by a diffusion equation, with nonlinearities introduced to model capacity limits. To illustrate the behavior and scalability of the model, we show its application first on two simple networks, then on petroleum infrastructure in the United States, where we analyze the effects of a hypothesized earthquake.

02 PETROLEUM↗
DOE OSTI2019

Overbuilding & curtailment: The cost-effective enablers of firm PV generation

Current thinking considers that PV output curtailment is a last resort measure to be avoided. In this article, we argue that supply-shaping, achieved through proactive curtailment associated with PV oversupply, is actually critical to achieving intermittency mitigation and delivering firm PV generation at the lowest cost. We investigate the premium to transform a low-cost, but intermittent solar kWh into a firm, effectively dispatchable kWh. We show that a fundamental ingredient of minimizing this premium is to optimally overbuild and, as necessary and appropriate, curtail PV generation. Drawing on a case study in the State of Minnesota, we show that firm, high-penetration-ready PV generation could be achieved at a production cost at or below current conventional generation, especially when optimally coupled with wind generation. Here, we conclude with a recommendation that in order to achieve this lowest cost firm generation potential, proactive curtailment strategies should inform future transactional PV remuneration systems.

14 SOLAR ENERGY↗
DOE OSTI2017

Resolution Versus Error for Computational Electron Microscopy

Images that are collected via scanning transmission electron microscopy (STEM) can be undersampled to avoid damage to the specimen while maintaining resolution [1, 2]. We have used BPFA to impute missing data and reduce noise [3]. The reconstruction is typically evaluated using the peak signal-to-noise ratio (PSNR). This measure is too conservative for STEM images and we propose that the Fourier ring correlation (FRC) is used instead to evaluate the reconstruction. We are not concerned with exact reconstruction of the truth image, and therefore PSNR is a conservative estimation of the quality of the reconstruction. Instead, we are concerned with the visual resolution of the image and whether atoms can be distinguished. We have evaluated the reconstruction of a simulated STEM image using the FRC and compared the results with the PSNR measurements. The FRC captures the resolution of the image and is not affected by a large MSE if the atom peaks are still distinguishable. The noisy and reconstructed images are shown in Figure 1. The simulated STEM image was sampled at 100%, 80%, 40%, and 20% of the original pixels to simulate an undersampled scan. The reconstruction was done using BPFA with a patch size of 10 x 10 and no overlapping patches. Not having overlapping patches produces inferior results but they are still acceptable. The dictionary size is 64 and 30 iterations were completed during each reconstruction. The 100% image was denoised instead of reconstructed. Poisson noise was applied to the simulated image with λ values of 500, 50, and 5 to simulate lower imaging dose. The original simulated STEM image was also included in our calculations and was generated using a dose of 1000. The simulated STEM image is 100 by 100 pixels and has essentially no high frequency components. The image reconstruction tends to smooth the data, also resulting in no high frequency components. This causes the FRC of the two images to be large at higher resolutions and may be misleading. For this reason, the BPFA has no overlap to avoid excessive smoothing. Moreover, the resolution of the simulated image is approximately 9.2 (1/nm), so we only look that far in the frequency domain when performing FRC. If the FRC curve does not crossover the threshold, a resolution value of 9.2 is used. We emphasize that our reported results are conservative. The FRC and PSNR values using the ground truth and the reconstructed images are shown in Tables 1 and 2. The left side show the metrics without using BPFA (missing pixels) and the right side show the metrics after using BPFA. When we did not use BPFA, the Fourier transform was estimated [4]. Some threshold curves have been studied [5], but they are derived for additive noise models. Since we have a Poisson noise model, we have used the more conservative threshold of 0.5 for our calculations. Ten images were used to construct each cell of tables in the form of the mean of the metric plus or minus its standard deviation. As expected, the PSNR dies off much quicker than the FRC values for the same image. For the 100% and 80% sampled versions of the truth image, the resolution only dies off when the dose is 5. However, the PSNR dies off rapidly as the dose is reduced. For the 1000, 500, and 50 dose images, the FRC is the maximum, or close, until we undersample at 20%. The PSNR for these values tapers down as we get into the bottom right hand corner of the table, even though the resolution remains high. Overall, we find that undersampled images can be reconstructed to acceptable resolution even when the dose per pixel is also reduced[6]. References: [1]A Stevens, H Yang, L Carin et al. Microscopy 63(1), (2014), pp. 41. [2]A Stevens, L Kovarik, P Abellan et al. Advanced Structural and Chemical Imaging 1(1), (2015), pp. 1. [3]M Zhou, H Chen, J Paisley et al. Image Processing, IEEE Transactions on 21(1), (2012), pp. 130. [4]V. Y. Liepin’sh. Automatic control and computer sciences 30(3), (1996), pp. 20.

Luzi, Lorenzo↗
DOE OSTI2017

Electron Bifurcation: Thermodynamics and Kinetics of Two-Electron Brokering in Biological Redox Chemistry

How can proteins drive two electrons from a redox active donor onto two acceptors at very different potentials and distances? And how can this transaction be conducted without dissipating very much energy or violating the laws of thermodynamics? Nature appears to have addressed these challenges by coupling thermodynamically uphill and downhill electron transfer reactions, using two-electron donor cofactors that have very different potentials for the removal of the first and second electron. Although electron bifurcation is carried out with near perfection from the standpoint of energy conservation and electron delivery yields, it is a biological energy transduction paradigm that has only come into focus recently. This Account provides an exegesis of the biophysical principles that underpin electron bifurcation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

110th Anniversary: Bridging the Time and Length Scales of Process Systems with Data

Here we report on the role of data as a "bridge" connecting the different time/length scales of chemical processes in mathematical modeling and multi-scale, integrated decision making. We argue that this is a fitting role of "big data" in the chemical industry, an area that comprises complicated yet deterministic physical systems. Such systems can be described using physical and chemical laws that are generally well-understood. Accordingly, data and data analysis are less likely to provide the unexpected and/or surprising insights that they have generated in other sectors (e.g., the transactional economy, social sciences). Nevertheless, historical operating data (which are often plentiful and available at little cost) can be converted to very useful information for multi-scale mathematical modeling of chemical processes. Several examples of integration are provided, mapped on the continuum of time and length scales of process systems. Current research challenges and potential directions for future work are discussed.

42 ENGINEERING↗
DOE OSTI2020

Carbon Dioxide Production in Bedrock Beneath Soils Substantially Contributes to Forest Carbon Cycling

Abstract Soils are widely considered the primary terrestrial organic matter pool mediating carbon transactions with the atmosphere and groundwater. Because soils are both a host and a product of rhizosphere activity, they are thought to mark the location where photosynthetic fixation of carbon dioxide (CO 2 ) is balanced by the oxidation of organic matter. However, in many terrestrial environments, the rhizosphere extends below soils and into fractured bedrock, and it is unknown if the resulting biological and hydrologic dynamics in bedrock have a significant impact on carbon cycling. Here we show substantial production of CO 2 in weathered bedrock at 4–8 m below the thin soils (<0.5 m thick) of a Northern California forest using innovative monitoring technology for sampling gases and water in fractured rock. The deep CO 2 production supports a persistent upward flux of CO 2(g) year‐round from bedrock to soil, constituting between 2% and 29% of the average daily CO 2 efflux from the land surface. When water is rapidly transported across the fractured bedrock vadose zone, nearly 50% of the CO 2 produced in the bedrock dissolves into water, promoting water‐rock interaction and export of dissolved inorganic carbon (DIC) from the unsaturated zone to groundwater, constituting as much as 80% of the DIC exiting the hillslope. Such CO 2 production in weathered bedrock is subject to unique moisture, temperature, biological, and mineralogical conditions which are currently missing from terrestrial carbon models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Two-tiered enforcement of high-fidelity DNA ligation

DNA ligases catalyze the joining of DNA strands to complete DNA replication, recombination and repair transactions. To protect the integrity of the genome, DNA ligase 1 (LIG1) discriminates against DNA junctions harboring mutagenic 3'-DNA mismatches or oxidative DNA damage, but how such high-fidelity ligation is enforced is unknown. Here, X-ray structures and kinetic analyses of LIG1 complexes with undamaged and oxidatively damaged DNA unveil that LIG1 employs Mg 2+ -reinforced DNA binding to validate DNA base pairing during the adenylyl transfer and nick-sealing ligation reaction steps. Our results support a model whereby LIG1 fidelity is governed by a high-fidelity (HiFi) interface between LIG1, Mg 2+ , and the DNA substrate that tunes the enzyme to release pro-mutagenic DNA nicks. In a second tier of protection, LIG1 activity is surveilled by Aprataxin (APTX), which suppresses mutagenic and abortive ligation at sites of oxidative DNA damage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Enhanced anti-counterfeiting measures for additive manufacturing: coupling lanthanide nanomaterial chemical signatures with blockchain technology

The significant rise of additive manufacturing (AM) in recent years is in part due to the open sourced nature of the printing processes and reduced cost and capital barriers relative to traditional manufacturing. However, this democratization of manufacturing spurs an increased demand for producers and end-users to verify the authenticity and quality of individual parts. To this end, we introduce an anti-counterfeiting method composed of first embedding engineered nanomaterials into features of a 3D-printed part followed by non-destructive interrogation of these features to quantify a chemical signature profile. The part specific chemical signature data is then linked to a securitized, distributed, and time-stamped blockchain ledger entry. To demonstrate the utility of this approach, lanthanide-aspartic acid nanoscale coordination polymers (Ln3+- Asp NCs) / poly(lactic) acid (PLA) composites were formulated and transformed into a filament feedstock for fused deposition modeling (FDM) 3D printing. In the present case, a quick-response (QR) code containing the doped Ln3+-Asp NCs was printed using a dual-extruder FDM printer into pure PLA parts. The QR code provides a searchable reference to an Ethereum-based blockchain entry. The QR code physical features also serve as defined areas to probe the signatures arising from the embedded Ln3+-Asp NCs. Visible fluorescence emission with UV-excitation was quantified in terms of color using a smartphone camera and incorporated into blockchain entries. Ultimately, linking unique chemical signature data to blockchain databases is anticipated to make the costs of counterfeiting AM materials significantly more prohibitive and transactions between those in the supply chain more trustworthy.

Additive Manufacturing↗