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DOE OSTI2022

Exploring the benefits of utilizing small modular device for sustainable and flexible shale gas water management

Growing shale gas extraction in recent years has triggered wide discussions on the associated freshwater requirement and wastewater management. Many optimization approaches have been developed for shale gas water management; however, most of the studies assumed permanent utilization of wastewater treatment facilities with fixed capacities. Considering the rapidly declining characteristics of shale gas wastewater production, these treatment facilities could remain largely underutilized after the first few months/years of production, making them less economically attractive. To maximize the capacity utilization of treatment facilities and further improve the economic performance of shale gas development, this study develops a systematic optimization framework, where the capacity strategy of conventional treatment facilities and utilization of the recent concept of modular manufacturing are both considered for flexible shale gas water management. The proposed mixed-integer linear programming (MILP) model simultaneously optimizes the design and planning of integrated shale gas and water supply chain, with a focus on capacity planning for both large-scale conventional treatment facilities and small-scale modular devices. A series of Marcellus-based case studies are performed to illustrate the applicability of the proposed model and provide general insights into the trade-offs between the multiple types of treatment facilities. The optimization results reveal that the combinatorial utilization of conventional facilities and modular devices for wastewater treatment (66% by conventional facilities and 34% by modular devices) brings 9.3% more reused water for other well development and 6.2% savings in water-related costs, compared to flexible management of only conventional facilities. Furthermore, this work suggests that taking modular device as auxiliary equipment for shale gas water management is most beneficial to increase the capacity utilization of treatment facilities and achieve a more economic and sustainable shale gas production system.

04 OIL SHALES AND TAR SANDS↗

DOE OSTI2023

Distributed Renewables for Arctic Energy: A Case Study

Alaska is a vast state that stretches into the Arctic Circle. Roughly 140,000 people in the state are dependent on isolated electric grids, traditionally burning expensive fossil fuels. This has negative impacts on air quality and climate. As the climate warms, fuel supply chains and traditional ways of life are threatened. Renewable electric sources offer a clean, resilient alternative with less volatile costs, but there are a variety of technical, social, economic, and political challenges to developing renewable energy systems in remote Arctic communities. Examples include harsh operating conditions, lack of local technical and managerial capacity, complex funding mechanisms, and glacial permitting processes. In this study, we interview one group of communities that are interested in adding renewable energy to their systems to understand the needs and challenges they face, and then another group that has successfully installed renewable energy, to understand how they overcame such challenges and the lessons they learned. Notable results include the importance of local buy-in, education, and technical involvement, procuring external funding sources, inter-community collaboration, installing bespoke systems, and working with reliable equipment suppliers. The goal of this report is to orient and inspire Arctic communities that want to begin their renewable transition, by providing helpful examples and points of contact.

17 WIND ENERGY↗

DOE OSTI2025

Application of Raman Spectroscopy to Determine Uranium Content in ADUN Solution

The work presented in this report is part of the ongoing efforts to address the nuclear material control and accounting needs for advanced reactor fuel fabrication facilities. This work was supported by the Materials Protection, Accounting, and Control Technologies (MPACT) program under the US Department of Energy Office of Nuclear Energy‘s Nuclear Fuel Cycle and Supply Chain program. The activities and engagements under the MPACT program are designed to support a robust US civilian nuclear energy enterprise. In the work described in this report, we supported MPACT objectives by developing measurement techniques that could be used for material accounting and process monitoring and by working with industry partners to identify existing gaps and areas for improvement. Oak Ridge National Laboratory has been working with commercial tristructural isotropic (TRISO) fuel fabricators such as Standard Nuclear to develop technology for rapid and cost-effective uranium content assessment. This work has focused on demonstrating advanced measurement techniques (e.g., Raman spectroscopy) that can be used for rapid, reliable, and cost-effective routine measurements of uranium content in feed solutions and liquid waste streams as well as for monitoring in-line process measurements and product streams. Specifically, this report explores techniques for accurately determining uranium content in acid-deficient uranyl nitrate (ADUN) solutions and detecting low uranium concentrations in ammonia solutions. Developing such measurement techniques will benefit TRISO fuel fabrication facilities, facilities involved in other parts of the fuel cycle that require online monitoring of aqueous solutions, and potentially molten salt fuel reactors. This work supports developing Raman spectroscopy procedures to determine uranium concentrations in ADUN solutions, which are used as feedstock in the sol–gel process for creating TRISO fuel. Some additional benefits of using Raman spectroscopy for uranium quantification in fabrication facilities include enabling online monitoring of the chemical process, which would provide near real-time feedback; eliminating the need for sample transfers, preparation, or dilution; providing nondestructive measurements; and user friendliness. In this fiscal year, FY25, we determined the identity of the unknown Raman band at approximately 853 cm−1 that was discovered in ADUN Raman spectra in FY24, created calibration curves and determined uranium concentrations of two ADUN solutions, and compared the Raman results to results obtained from inductively coupled plasma mass spectrometry and Davies–Gray titration. Furthermore, we have identified focus areas for experimentation in future fiscal years. A key result is that the accuracy of using Raman can provide accuracy comparable to destructive analysist techniques, With a well-developed calibration curve, using standards and a large number of samples (more than five samples), uncertainty on the order of 1%–3% is achievable. Given that the uncertainties achieved by Raman spectroscopy were on the order of the uncertainties achieved using ICP-MS, we conclude that with a well-developed procedure Raman spectroscopy can be used to determine uranium concentrations in ADUN solutions for NMC&A applications. The benefits of such an approach are that the time and effort will be less than that of comparable destructive analysis techniques, with approximately the same level of technical expertise. This will be attractive to operators of fuel fabrication facilities as it will lower costs and improve efficiencies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

American-Made Challenges: FLoating Offshore Wind ReadINess (FLOWIN) Prize

The goal of this prize is to establish a pathway to cost-effective domestic manufacture and deployment of gigawatt-scale floating wind farms in U.S. waters. Toward realization of that goal, the prize will: (1) incentivize and support further development of technically and economically viable floating wind platform structures that can support 12-MW-rated or larger wind turbines in water depths over 40 meters. (2) incentivize the creation of a supply chain that will enable domestic on-site manufacturing of floating offshore wind farm components utilizing a skilled and trained workforce. (3) promote awareness of the importance and principles of inclusion and environmental justice.

American-Made Challenges↗

DOE OSTI2018

The Case for Recycling: Overview and Challenges in the Material Supply Chain for Automotive Li-Ion Batteries

Lithium ion batteries (LIB) continue to gain market share in response to the increasing demand for electric vehicles, consumer electronics, and energy storage. The increased demand for LIB has highlighted potential problems in the supply chain of raw materials needed for their manufacture. Some critical metals used in LIB, namely lithium, cobalt, and graphite are scarce, are not currently mined in large quantities, or are mined in only a few countries whose trade policies could limit availability and impact prices. The environmental and social impacts of mining these materials have also drawn attention as production ramps up to meet the increased demand. Closed-loop systems with recycling at the end-of-life provide a pathway to lower environmental impacts and a source of high value materials that can be used in producing new batteries. Because environmental regulations concerning end-of-life batteries are not fully developed or implemented, most of these batteries currently end up in the landfills, with a very small number of spent batteries sent to the existing recycling facilities. However, with proactive regulations, an increasing supply of spent batteries, and innovations in recycling technologies, end-of-life batteries could supply a significant fraction of the materials needed for manufacturing of new LIB. This paper reviews the current state of the LIB manufacturing supply chain, addresses some issues associated with battery end-of-life, and sheds light on the importance of LIB recycling from the environmental and value chain perspectives. We also discuss the expected benefits of recycling on the global LIB supply chain.

25 ENERGY STORAGE↗

DOE OSTI2021

Systems Analysis Approach to Polyethylene Terephthalate and Olefin Plastics Supply Chains in the Circular Economy: A Review of Data Sets and Models

The environmental and economic impacts of implementing a circular economy in plastic waste supply chains are not well understood. The proposed systems analysis framework assesses environmental, social, and economic impacts of plastic waste supply chains in a circular economy. The first objective of this article is to identify datasets, models and knowledge gaps associated with waste plastic supply chain processes, mainly in the U.S. Our literature review indicated that the best datasets exist for virgin plastic resin production, mechanical recycling, landfilling, and incineration, with materials recovery facility being intermediate, and with chemical recycling the lowest. The second objective of this article is to develop an illustrative application of the framework by conducting a preliminary systems analysis of PET bottles with closed-loop recycling. Here, the preliminary systems analysis of PET bottles utilized a linear programming optimization method. Our optimization model indicated that both chemical and mechanical recycling processes are needed to achieve a true circular economy of PET bottles with the least greenhouse gas emissions, specifically reductions of 24% when compared with the linear economy. Good quality and standardized life cycle assessment and techno-economic analysis studies are needed to better understand the environmental, economic, and social impacts of advanced sorting and chemical recycling technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Final Report for Industrial Base Cybersecurity Initiative (IBCI) Project (FY2019)

Information security issues impact all manufacturing sectors and are particularly troublesome when designs for advanced weapons systems are lost via attacks that propagate through the relatively unprotected lower tiers of the nation's supply chains. The US Manufacturing Industrial Base (MIB) consists of suppliers and distributors that range in size from large prime contractors with extensive cybersecurity resources to small shops with little or no in-house information technology capabilities. The acquisition and maintenance of the technologies, systems, and financial resources needed to assure secure collaborations can be an overwhelming challenge for many manufacturers yet the cost of poor cybersecurity practices can lead to the compromise of national security information worth hundreds of millions of dollars. The Department of Defense Manufacturing Industrial Base Policy organization and the Department of Energy, Energy Efficiency and Renewable Energy Advanced Manufacturing Office have chartered the Los Alamos National Laboratory (LANL) and the Oak Ridge Y-12 National Security Complex (Y-12) to design, develop, and demonstrate a Manufacturing Threat Evaluation Wargaming System (MTEWS). The MTEWS concept is based on the use of a virtual model of the computer networks and cybersecurity protocols used across the MIB that will be continuously updated to reflect the dynamic threat environment. The MTEWS cyber-physical test range will demonstrate a prototype wargaming system that analyzes the impact of new and existing cybersecurity threats while also providing the information needed to sustain the integrity of the MIB supply chains. A long-term goal is the establishment of an enduring national manufacturing operations center that proactively responds to the continuously changing attacks that threaten the MIB and US national security. LANL and Y-12 have formed an Industrial Base Cybersecurity Initiative Team (IBCI), consisting of partners from the public, private and academic sectors, that is developing the MTEWS. To date, most of the project tasks have been centered on the technologies required to create a representative model of the MIB because this is a foundational element for the entire project. Modeling activities at the University of North Carolina at Charlotte (UNC Charlotte) have demonstrated a VMware-based prototype system that can accommodate a network model with up to 350 nodes and includes features such as the option to incorporate network scanning information when building the model and the ability to down select the elements of duplicative networks to a statistically significant subset that avoids redundantly duplicating network configurations. Broad Ordering Agreements have been established with UNC Charlotte and the University of West Florida (UWF) that support a variety of cybersecurity for manufacturing tasks and wide-spread endorsement has been received from government, industry and academia sectors concerning the IBCI goals and technical direction.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2026

Rare Earth Production in the United States: A Concise Review of Resource Development and Commercial Processes

This review article presents a concise review of estimated resources, processing methods and challenges involved in domestic rare earth mining projects in the United States (US). It also highlights the current status of major mining projects, anticipated rare earth production in the near future, and commercial projects utilizing non-traditional feedstocks for rare earth production and recycling. Based on the current industry outlook, opportunities for R&D have also been highlighted. Perspective on domestic rare earth production capability is essential because global rare earth production is currently dominated by China. Given potential export controls by China, this imbalance has created supply chain risk. The US and other countries have limited rare earth production capacity and relatively little expertise in rare earth processing. However, in the last decade, efforts have been made by several nations, including the US, to reduce their reliance on China for rare earth and other critical minerals. The US is currently investing in projects to develop domestic rare earth separation and refining capacity. These projects are discussed here. When backed by R&D and government support, these projects have potential to make significant progress towards establishment of domestic rare earth separation capabilities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Process design for recovering rare-earth elements from mine tailings with low rare-earth concentrations via sequential leaching and solvent extraction

Rare earth elements (REEs) are essential for advanced technologies and yet face significant supply chain risks due to their concentrated global production and limited domestic availability. Addressing this challenge requires efficient processes capable of upgrading low-grade secondary resources such as mine tailings. In this study, we developed a novel separation flowsheet that integrates sequential leaching and 2-stage solvent extraction (SX) processes to recover high-purity heavy REEs (HREEs) and light REEs (LREEs) from a simulated mine-tailing concentrate containing 2.4 wt% total REEs (TREEs; 0.6 wt% LREEs and 1.8 wt% HREEs). Sequential leaching with controlled pH adjustment selectively precipitated REEs while retaining the large amount of impurities in the solution, producing an REE-enriched leachate by following leaching processes with roughly twice the REE concentration and half the impurity concentration compared to that of single-step leaching. The optimized SX flowsheet employed Cyanex 572 to extract HREEs and Fe over LREEs, followed by Fe removal using tributyl phosphate (TBP), while the raffinate stream was processed by SX with di(2-ethylhexyl)phosphoric acid (D2EHPA) to recover LREEs under optimized conditions balancing both extraction efficiency and purity. Although increased extractant availability in the organic phase improved LREE recovery, it also increased co-extraction of Ca, underscoring trade-offs in process optimization. Both HREE- and LREE-rich solutions were subsequently precipitated into solid products via oxalate precipitation, resulting in high-purity REE solids containing ∼92.0 wt% HREEs (∼95.7 wt% TREEs) and ∼92.8 wt% LREEs (∼94.0 wt% TREEs). In conclusion, this proof-of-concept study using simulated mine tailings demonstrates a promising approach for upgrading low-grade REE resources, while highlighting the need for future validation with real materials.

Mine tailings↗

DOE OSTI2025

Advanced Transmission Technologies –GETs and HPCs Session 3: HPCs and Building Actions Plans to Digital Assurance Risks

The third session of the Idaho National Laboratory’s (INL) Technical Assistance for Digital Assurance (TADA) program, held on November 11, 2025, centered on High Performance Conductors (HPCs) and the formulation of action plans to address digital assurance risks associated with Grid-Enhancing Technologies (GETs). This session convened experts from utilities, vendors, and government agencies to examine the technical, operational, and cybersecurity aspects of HPC deployment. Discussions highlighted the benefits of HPCs, such as their ability to rapidly increase transmission capacity using existing corridors, improve grid resilience, reduce system losses, and align with FERC Orders 2023 and 1920. Participants evaluated supply chain and digital assurance risks, including reliance on imported materials, limited domestic manufacturing capacity, workforce shortages, and traceability issues. The session also emphasized the importance of digital trust, integration-layer cybersecurity, and unified risk frameworks, introducing tools like intrusion detection systems, encryption, zero trust networking, and firmware integrity. Recaps of earlier workshops on Dynamic Line Ratings (DLRs), Advanced Power Flow Control (APFC), and Transmission Topology Optimization (TTO) underscored institutional barriers and integration challenges. Action plans were proposed to mitigate issues such as inconsistent cybersecurity practices, SBOM usage, supply chain visibility, operator trust, and misaligned incentives. Additionally, INL presented its supply chain risk management tools and Cyber-Informed Engineering (CIE) principles to support secure procurement and system design. The session concluded with a commitment to share key takeaways, incorporate cohort feedback into future policy development, and continue collaborative engagement through upcoming pilot activities. Session 3 of 3.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Fast Learning for Immersive Engagement in Energy Simulations

The fast computation which is critical for immersive engagement with and learning from energy simulations would be furthered by developing a general method for creating rapidly computed simplified versions of NREL's computation-intensive energy simulations. Created using machine learning techniques, these 'reduced form' simulations can provide statistically sound estimates of the results of the full simulations at a fraction of the computational cost with response times - typically less than one minute of wall-clock time - suitable for real-time human-in-the-loop design and analysis. Additionally, uncertainty quantification techniques can document the accuracy of the approximate models and their domain of validity. Approximation methods are applicable to a wide range of computational models, including supply-chain models, electric power grid simulations, and building models. These reduced-form representations cannot replace or re-implement existing simulations, but instead supplement them by enabling rapid scenario design and quality assurance for large sets of simulations. We present an overview of the framework and methods we have implemented for developing these reduced-form representations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2009

Developing Ultra Reliable Life Support for the Moon and Mars

Recycling life support systems can achieve ultra reliability by using spares to replace failed components. The added mass for spares is approximately equal to the original system mass, provided the original system reliability is not very low. Acceptable reliability can be achieved for the space shuttle and space station by preventive maintenance and by replacing failed units, However, this maintenance and repair depends on a logistics supply chain that provides the needed spares. The Mars mission must take all the needed spares at launch. The Mars mission also must achieve ultra reliability, a very low failure rate per hour, since it requires years rather than weeks and cannot be cut short if a failure occurs. Also, the Mars mission has a much higher mass launch cost per kilogram than shuttle or station. Achieving ultra reliable space life support with acceptable mass will require a well-planned and extensive development effort. Analysis must define the reliability requirement and allocate it to subsystems and components. Technologies, components, and materials must be designed and selected for high reliability. Extensive testing is needed to ascertain very low failure rates. Systems design should segregate the failure causes in the smallest, most easily replaceable parts. The systems must be designed, produced, integrated, and tested without impairing system reliability. Maintenance and failed unit replacement should not introduce any additional probability of failure. The overall system must be tested sufficiently to identify any design errors. A program to develop ultra reliable space life support systems with acceptable mass must start soon if it is to produce timely results for the moon and Mars.

Jones, Harry W.↗

DOE OSTI2025

High entropy alloys as catalysts: A focused review

A brief literature review of recent experimental and computational efforts on the use of high entropy alloys (HEAs) as catalysts is presented, while also sharing some perspectives and future insights. To fully broach the vast compositional possibilities of HEA materials, integrating computational modeling with high-throughput experimental synthesis and validation is necessary to accelerate their design and development. Once identified, specific HEAs can be a class of materials for the next generation of catalysts when addressing global challenges related to energy independence, commodity chemical production, environmental remediation, abating emissions, and modernized domestic supply chain resilience.

42 - ENGINEERING↗

DOE OSTI2023

Assignment of Freight Traffic in a Large-scale Intermodal Network under Uncertainty

This paper presents a methodology for freight traffic assignment in a large-scale road-rail intermodal network under uncertainty. Network uncertainties caused by natural disasters have dramatically increased in recent years. Several of these disasters (e.g., Hurricane Sandy, Mississippi River Flooding, and Hurricane Harvey) severely disrupted the U.S. freight transportation network, and consequently, the supply chain. To account for these network uncertainties, a stochastic freight traffic assignment model is formulated. An algorithmic framework, involving the sample average approximation and gradient projection algorithm, is proposed to solve this challenging problem. The developed methodology is tested on the U.S. intermodal network with freight flow data from the Freight Analysis Framework. The experiments consider three types of natural disasters that have different risks and impacts on transportation networks: earthquakes, hurricanes, and floods. It is found that for all disaster scenarios, freight ton-miles are higher compared to the base case without uncertainty. The increase in freight ton-miles is the highest under the flooding scenario; this is because there are more states in the flood-risk areas, and they are scattered throughout the U.S.

42 ENGINEERING↗

NASA NTRS2021

Greenhouse Gas Emissions from Food Systems: Building the Evidence Base

New estimates of greenhouse gas (GHG) emissions from the food system were developed at the country level, for the period 1990–2018, integrating data from crop and livestock production, on-farm energy use, land use and land use change, domestic food transport and food waste disposal. With these new country-level components in place, and by adding global and regional estimates of energy use in food supply chains, we estimate that total GHG emissions from the food system were about 16 CO2eq yr−1 in 2018, or one-third of the global anthropogenic total. Three quarters of these emissions, 13 Gt CO2eq yr−1, were generated either within the farm gate or in pre- and post-production activities, such as manufacturing, transport, processing, and waste disposal. The remainder was generated through land use change at the conversion boundaries of natural ecosystems to agricultural land. Results further indicate that pre- and post-production emissions were proportionally more important in developed than in developing countries, and that during 1990–2018, land use change emissions decreased while pre- and post-production emissions increased. We also report results on a per capita basis, showing world total food systems per capita emissions decreasing during 1990–2018 from 2.9 to 2.2 t CO2eq cap−1, with per capita emissions in developed countries about twice those in developing countries in 2018. Our findings also highlight that conventional IPCC categories, used by countries to report emissions in the National GHG inventory, systematically underestimate the contribution of the food system to total anthropogenic emissions. We provide a comparative mapping of food system categories and activities in order to better quantify food-related emissions in national reporting and identify mitigation opportunities across the entire food system.

greenhouse gas emissions↗

DOE OSTI2022

Supply Chain Risk Management: Data Structuring

Supply chain risk management (SCRM) is an area of research that addresses both logistics concepts to maximize efficiency, reliability, and revenue as well as risk features, such as potential weak points, break points, and vulnerabilities within the supply chain. SCRM is used to find risks introduced at each node in a supply chain and how these risks can impact a company’s products, individuals, customers, and reputation. SCRM is a relatively new field, so standardized processes including data structuring are not fully documented. This paper explains the importance of a standard data structuring methodology and how it can enhance current SCRM efforts. Data ingest, structuring, and analysis are predominantly managed by humans. Automating some of the less complex steps can positively impact SCRM by allowing human analysts to focus on more strategic analyses. Types of data to be collected and structured are collected via publicly available information related to hardware, software, and corporate entities. After the data has been collected, the information is formatted in a specific manner, conforming to a schema, to allow for more effective and efficient ingest for further analysis. This paper outlines data structures used by Pacific Northwest National Laboratory for SCRM research and analysis purposes. These structures have been used for hundreds of analyses and have been successful in developing a common baseline. Data structuring is one of the first steps in data standardization, which will further mature and enhance the SCRM research area.

supply chain risk management, data structuring, re↗

DOE OSTI2022

Solar Photovoltaics: Supply Chain Deep Dive Assessment

This is one of a series of reports and deep dive assessments produced in response to Executive Order 14017 “America’s Supply Chains,” which directs the Secretary of Energy to submit a report on supply chains for the energy sector industrial base. The Executive Order is helping the federal government to build more secure and diverse U.S. supply chains, including energy supply chains. Over the past decade, solar power has gone from an emerging, niche technology to a mature energy industry. By 2035, solar power could supply 40% or more of U.S. electricity demand, dramatically accelerating the decarbonization of buildings, transportation, and industry; and, if current technology trends continue, it could do so without increasing the price of electricity. The rapid expansion of solar energy has the potential to yield broad benefits in the form of economic activity and workforce development. The solar industry already employs roughly 230,000 people in the United States, at an average wage that is higher than the national average for most comparable positions. By decarbonizing the electricity sector by 2035, the U.S. solar industry could employ 500,000–1,500,000 people by 2030. The components that are assembled to install a photovoltaic power system are produced by a global supply chain. Photovoltaic (PV) modules (also called panels) are made of cells that use a variety of technologies. There are two leading types of solar modules used in the United States, with crystalline silicon (c-Si) modules representing 84% of the market and cadmium telluride (CdTe) modules representing 16% of the market. Modules of either type require mounting structures to provide mechanical support (racking), which may be configured to follow the sun (tracking). The output of any PV module is direct current (dc), which is almost always converted to alternating current (ac) by an inverter.

14 SOLAR ENERGY↗

DOE OSTI2019

Crystalline Silicon Photovoltaic Module Manufacturing Costs and Sustainable Pricing: 1H 2018 Benchmark and Cost Reduction Road Map

In this paper we provide an overview of the accounting methods and most recent input data used within NREL's bottom-up crystalline silicon (c-Si) solar photovoltaic (PV) module supply chain cost models. The costs accounting framework that is detailed in this paper provides a methodology to prepare bottom-up c-Si PV supply chain cost models in accordance with the U.S. Generally Accepted Accounting Principles (GAAP) and the International Financial Reporting Standards (IFRS). For the polysilicon, ingot, wafer, cell conversion, and module assembly steps of the c-Si supply chain, we outline what is relevant for calculations of the costs of goods sold (consisting of the materials, labor, electricity, maintenance, and depreciation of capital equipment); as well as the additional operating expenses of research and development (R&D); and sales, general, and business administration (S, G, &A). This 2017 benchmark analysis is applied to current state-of-the-art manufacturing sites located within the United States, China, Taiwan, South Korea, Malaysia, the Philippines, and Germany. Primarily due to country-dependent labor and electricity rates, tax rates, and cost-of-capital considerations, we calculate differences in minimum sustainable pricing for all of these countries. In this paper we also include technical descriptions and bottom-up cost model results for several emerging c-Si technologies including larger Czochralski (Cz) ingots, kerfless wafers, reduced silicon utilization by thinner wafers and advanced diamond wire wafering, new encapsulants and backsheets, shingled cells, and the cell architectures passivated emitter and rear cells (PERC), bifacial passivated emitter and rear totally diffused (PERT) cells, bifacial heterojunction intrinsic thin layer (HIT) cells, and interdigitated all back-contact cells (IBC).

14 SOLAR ENERGY↗