Energy Impacts of Wide Band Gap Semiconductors in U.S. Light

(10) However, a widespread adoption of EVs is found to be an unwise strategy .... of using technology i; and the subscripts 0 and 1 refer to Si and WB...
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Energy Impacts of Wide Band Gap Semiconductors in U.S. Light-Duty Electric Vehicle Fleet Joshua A. Warren,† Matthew E. Riddle,‡ Diane J. Graziano,‡ Sujit Das,*,† Venkata K. K. Upadhyayula,§ Eric Masanet,§ and Joe Cresko∥ †

Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States Argonne National Laboratory, Argonne, Illinois 60439, United States § Northwestern University, Evanston 60208, Illinois, United States ∥ U.S. Department of Energy, Washington, D.C. 20585, United States ‡

S Supporting Information *

ABSTRACT: Silicon carbide and gallium nitride, two leading wide band gap semiconductors with significant potential in electric vehicle power electronics, are examined from a life cycle energy perspective and compared with incumbent silicon in U.S. light-duty electric vehicle fleet. Cradle-to-gate, silicon carbide is estimated to require more than twice the energy as silicon. However, the magnitude of vehicle use phase fuel savings potential is comparatively several orders of magnitude higher than the marginal increase in cradle-to-gate energy. Gallium nitride cradle-to-gate energy requirements are estimated to be similar to silicon, with use phase savings potential similar to or exceeding that of silicon carbide. Potential energy reductions in the United States vehicle fleet are examined through several scenarios that consider the market adoption potential of electric vehicles themselves, as well as the market adoption potential of wide band gap semiconductors in electric vehicles. For the 2015−2050 time frame, cumulative energy savings associated with the deployment of wide band gap semiconductors are estimated to range from 2−20 billion GJ depending on market adoption dynamics.

1. INTRODUCTION Increasing energy conservation and efficiency is among the most cost-effective tools for reducing the environmental impacts of energy resource consumption1 and has been a key element of US energy policy since the passage of the Energy Policy and Conservation Act of 1975 in response to the 1970s oil embargo. This legislation resulted in the first vehicle corporate average fuel economy (CAFE) standards, which have risen from 18 miles per gallon (mpg) in 1978 to 27.5 mpg in 2010.2 Simultaneously over this time frame, the semiconductor industry revolutionized information technology and communications, making electronics one of the most ubiquitous of all product types in the world. A recent study on the global electricity usage of communication technology consisting of use and production of consumer devices indicates the usage of communication networks and data centers reaching as much as 51% of global electricity in 2030 under the worst case scenario.3 Going forward, the semiconductor industry is poised next to revolutionize the automotive industry as fuel economy standards are set to nearly double from 2010 levels to 54.5 mpg in 2025.2 Due to substantial improvements in fuel economy for more efficient electric powertrain use over conventional internal combustion engine vehicles, electric vehicles, inclusive of hybrid electric vehicles (HEV), plug-in hybrid electric vehicles (PHEV), and battery electric vehicles © 2015 American Chemical Society

(BEV), are anticipated to increase in market share as automakers aim to comply with the aforementioned increasing CAFE standards. Although the share of domestic electricity consumption by electric vehicles is projected to increase from less than 0.02% in 2013 to 0.10% by 2030,4 the main driving force for this vehicle type is the improved fuel efficiency coupled with reduced vulnerability to imported oil. By managing voltage and current, power electronics semiconductors are one of the key technologies enabling the substantial fuel economy improvements seen in electric vehicles. Currently, conventional silicon-based semiconductor technology has the entire market share in electric vehicle power electronics. However, in the future, silicon (Si) is expected to yield market share to a different class of semiconductors, known as wide band gap (WBG) semiconductors, which have significantly greater energy efficiency potential than Si.5 Silicon carbide (SiC) and gallium nitride (GaN) are the two leading wide band gap semiconductor materials in terms of maturity, with several products commercially available. Received: Revised: Accepted: Published: 10294

March 31, 2015 August 6, 2015 August 6, 2015 August 6, 2015 DOI: 10.1021/acs.est.5b01627 Environ. Sci. Technol. 2015, 49, 10294−10302

Policy Analysis

Environmental Science & Technology

and (3) chemicals. While very important for semiconductor manufacturing from a technical standpoint, back end processing has not been a major focus of these life cycle studies due to its lesser contribution to cumulative energy demand (CED). Substrate production, inclusive of the process steps required for transforming raw quartz into the highly pure silicon (polysilicon) required for the Czochralski process, is quite energy intensive (mostly electricity), and is second in importance in terms of CED after front end processing.16−18 The complex front end processing stage requiring 83% electricity of total energy requirements, where hundreds of individual process steps and high purity chemicals, as well as large amounts of water and elemental gases, are consumed, has been the major focus of these analyses.16−18 The third major category, chemicals, specifically refers to the embodied energy of all high purity chemicals, elemental gases, and ultrapure water inputs. Of the three major categories analyzed in previous silicon semiconductor life cycle studies,16−18 it is the chemicals category that has the least contribution to CED, but is also the one with greatest uncertainty due to scarcity of data for the embodied energies of specialized semiconductor-grade chemicals. Krishnan’s17 analysis shows the chemicals category to constitute about 11% of cradle-to-gate CED and is at the upper bound of the findings by Williams16 and Boyd.18 While differences between the various studies exist, a reasonable conclusion would be that, collectively, substrate and front end electrical energy requirements appear to represent well in excess of half of total cradle-to-gate CED. In this paper, we develop a CED estimate of the materials and manufacturing life cycle stages for two WBG semiconductor architectures with significant promise, technically feasible, and mature for electric vehicle power electronics, SiC device on SiC substrate (SiC/SiC) and GaN device on silicon substrate (GaN/Si). The former is the most mature WBG technology, while the latter has significant low cost potential and can be used at relatively higher frequencies of 0.5−3 MHz by taking advantage of well-established conventional silicon technology. The emergence of GaN in power electronics is relatively recent, currently used widely in LEDs and amplifiers.24 Issues such as overcoming material challenges related to high lattice strain at the GaN and silicon interface due to mismatches in the coefficient of expansion need to be addressed. WBG CED estimates are compared with conventional silicon device on silicon substrate (Si/Si) estimates from literature.16 Our SiC/SiC estimate is based on data obtained from an industry consultant’s teardown analyses of multiple 600 volt (V) Schottky diodes from various manufacturers.26 The GaN/Si device estimate is developed by aggregating data from existing publicly available life cycle analyses.16,25 For the two architectures examined, the scope of the materials and manufacturing aspect of the study is bounded to the electrical energy requirements of substrate production and front end processing as it is believed this captures the major share of cradle-to-gate CED as well as the major differences between the various technologies examined. Results are reported in kilowatt-hours (kWh) per square centimeter (cm2) of functional die and compared with incumbent conventional Si technology. Due to relatively small contribution and more or less equivalent among various semiconductor devices, both back end processing and transport energy requirements are not estimated. The embodied energies of chemicals are also omitted for reasons of tractability and their relatively lesser importance (as seen in the case of conventional

WBG semiconductors are characterized by bandgap energies approximately three or more times that of Si,6 enabling this class of semiconductors to withstand much higher voltages.5 Consequently, WBG devices can be made much thinner, allowing faster switching with less resistance.5 Because of less resistance, less energy is wasted as heat compared with Si devices, making WBG devices more energy efficient. However, while substantial improvements in energy efficiency are possible, several factors are currently limiting the commercial acceptance of WBG semiconductors, including cost, unproven reliability, and limited selection of device types.5 Numerous life cycle studies indicate that well-to-wheel (WTW) greenhouse gas (GHG) emissions of electric vehicles would depend on the fossil content of the electricity mix.7−9 Compared to conventional internal combustion engine vehicles, WTW GHG emissions could decrease by 80% if electric vehicles use renewable electricity.7 It has been estimated that an 80% domestic GHG reduction could only be achieved at a relatively high rate of electrification (40% of miles and 26% by fuel), with significant quantities of lowcarbon liquid fuel in cases with low or moderate travel demand growth.10 However, a widespread adoption of EVs is found to be an unwise strategy given the existing and near-future marginal electricity generation mix in several U.S. states.11 The use of WBG semiconductors in electric vehicles rather focuses on the fuel economy improvements, resulting in additional benefits during the vehicle life cycle use stage. In terms of WBG life cycle energy, most studies to date have focused on use phase savings potential over incumbent technologies. Zhang discusses efficiency improvement potential in HEVs and PHEVs,12 and wind turbines,13 while solar power inverters are examined by Wilhelm.14 A data gap exists in that relatively few studies have investigated the energy impacts of the raw material acquisition and part production life cycle stages of WBG semiconductors, even with conventional Si semiconductors. Reasons cited include process complexity involving hundreds of process steps and specialty chemicals, and rapidly evolving technology with short product lifetimes.15 Furthermore, these studies are primarily concerned with product categories other than power electronics, such as conventional silicon-based information technology15−18 and solar cells.19−21 For WBG semiconductors, where materials and manufacturing stage life cycle data are even more limited, those studies which do exist have focused mostly on LED applications22,23,25 where WBG technology is relatively more mature than in power electronics applications. In this paper, materials and manufacturing energy estimates for SiC and GaN are developed and compared with use phase savings potential in electric vehicles versus conventional Si. Results are interpreted within the context of the market substitution potential of these WBG semiconductors in place of conventional Si over time in the United States light-duty vehicle fleet.

2. METHODOLOGY: MATERIALS ACQUISITION AND PART PRODUCTION ENERGY Semiconductor device manufacturing is among the most complicated of all manufactured products, consisting of three major stages of substrate, front end, and back end as discussed in S1. Earlier life cycle work on conventional silicon semiconductors16−18 has generally disaggregated cradle-togate energy requirements into three major categories: (1) substrate production, (2) front end processing or fabrication, 10295

DOI: 10.1021/acs.est.5b01627 Environ. Sci. Technol. 2015, 49, 10294−10302

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Environmental Science & Technology

the market adoption of WBG, a model is used that combines the Bass diffusion model described above with a discrete choice model similar to that used in Jun and Park.39 eqs 1−4 show the full specification. The Bass model (the first part of eq 1, that is, < (Fi(t) (p + qFj(t)) > ) determines the number of potential adopters that consider switching to WBG, and the choice model (the utility function represented as the second part of eq 1) evaluates the relative benefits of the two technologies to determine how many of the potential adopters choose to switch:

Si) compared with substrate and front end processing energy. Finally, we take the same assumption as Boyd18 that end of life energy requirements are negligible compared with substrate and front end processing.

3. METHODOLOGY: USE-PHASE In addition to the cradle-to-gate energy analysis of WBG devices, use-phase deployment scenarios of WBG devices within the U.S. light-duty vehicle (LDV) fleet are presented and utilized to estimate the potential use-phase U.S. LDV fleet impacts from WBG semiconductors. The use-phase deployment scenarios provide a framework for presenting the potentially significant energy efficiency potentials enabled by WBG devices in comparison to the cradle-to-gate life cycle analysis. Argonne National Laboratory’s VISION model27 is used to evaluate the end-use stage of WBG power electronics adopted in the vehicle market. In this evaluation, we explore the usephase energy consumption associated with the adoption of WBG materials in HEV, PHEV, and BEV. Specifically, we estimate annual cradle-to-gate energy consumed in manufacturing semiconductors for HEV, PHEV, and BEV sales plus vehicle usage expressed as CED of the U.S. vehicle fleet, projected from 2015 to 2050. The VISION model provides a baseline market case for sales of different types of vehicles, calibrated to Annual Energy Outlook (AEO) 2012 predictions through 2035 and extrapolated to 2050. Additionally, an alternative market case is evaluated that assumes a more aggressive adoption of alternative vehicles (HEV, PHEV, and BEV) generated for the DOE’s Transportation Energy Futures (TEF) study.28 The two vehicle market cases are labeled “AEO” and “TEF.” Among several transportation future studies,29−32 these two cases provide reasonable low and high projections of alternative vehicle adoption for evaluating the potential energy savings impact of WBG technologies. For each of two forecasts of new vehicle sales, the composition of the U.S. vehicle fleet (i.e., vehicle types and vintages) for each year from 2015 to 2050 is determined using the stock turnover model in VISION that incorporates survival rate estimates developed by the National Highway Transportation Safety Administration (NHTSA).33 Figure S2 shows the resulting vehicle fleet composition for the AEO and TEF vehicle market cases in years 2010 through 2050. The use-phase energy impacts of WBG power electronics in electric vehicles are assessed for technical potential and cost sensitive adoption scenarios, by assuming 100% penetration of WBGs in power electronics for HEVs, PHEVs, and BEVs in the former case. In the technical potential adoption scenarios, the use-phase impacts are evaluated for WBG replacing Si following a Bass curve, beginning at 0% and initiated in 2015. The adoption rate in the Bass diffusion model depends on two parameters: the coefficient of innovation, p, and the coefficient of imitation, q.34 These parameters were chosen to be consistent with adoption rates that have been observed for other vehicle technologies reported in EPA35 and summarized in a Transportation Energy Futures report.36 The parameters p = 0.007 and q = 0.34 provide a reasonable fit to these data, as illustrated in Figure S3. High cost and uncertain reliability have been identified as significant hurdles to the market adoption of WBG-based power electronics in hybrid and electric vehicles.37,38 To explore the sensitivity of cost and competing technologies on

fij (t ) = Fi(t )[p + qFj(t )]

exp(Vj(t )) exp(Vi (t )) + exp(Vj(t ))

(1)

Vi (t ) = βCi(t )

(2)

F0(t ) = 1; F ′0 (t ) = −f01

(3)

F1(t ) = 0; F ′1(t ) = f01

(4)

Here, f ij(t) is the rate of switching from technology i to technology j; Fi(t) is the share of the population that uses technology i; Vi(t) is the nonstochastic portion of the utility function for technology i used in the choice model; Ci(t) is the full cost of using technology i; and the subscripts 0 and 1 refer to Si and WBG respectively. The parameters p and q are the Bass innovation and imitation parameters, respectively, and are given values of 0.007 and 0.34, as in the technical potential model. The parameter β, which determines the impact of relative costs on adoption rate, is chosen to match the average price elasticity of −9.33 found in an analysis of semiconductor technology diffusion.40 If the new technology is significantly less expensive than the technology it replaces, this model approaches the Bass model, so the technical potential adoption rate can be generated as a special case of this more general model. Although the costs and reliability of WBG currently limit its application in power electronics, these problems are expected to be overcome and cost parity with its Si counterparts eventually achieved. 41−43 Cost parity is considered to encompass total costs for the application, taking into account the potential for less semiconductor material, smaller packaging, reduced cooling requirements, and other benefits. Given uncertain forecasts for WBG costs, we evaluate two costsensitive scenarios for the TEF vehicle market case, assuming WBG reaches cost parity with Si in 2020 and 2030.41,42,44 The estimated cost-sensitive adoption curves for these two alternatives compared to the technical potential adoption curve are shown in Figure S4. A summary of the six use phase scenarios evaluated using Argonne’s VISION model is given in Table S2. For the VISION modeling, vehicle fuel economy (discussed in a later section) and vehicle miles traveled (VMT) influence the energy impacts. The total VMT grows slowly over time and is an aggregate of the individual vehicle VMTs that respond to fuel costs and vary with vehicle age per the relationship developed by the NHTSA.33 Fuel costs depend on fuel prices and fuel efficiency. The elasticity of the VMT response to fuel costs is set to −0.1 (consistent with review by Ajanovic).45 Therefore, a 10% fuel efficiency improvement is partially offset by a 1% increase in miles traveled, leading to a 9% net fuel savings. The elasticity can be explained in part by the rebound 10296

DOI: 10.1021/acs.est.5b01627 Environ. Sci. Technol. 2015, 49, 10294−10302

Policy Analysis

Environmental Science & Technology effect,51,52 which has been observed to offset energy efficiency gains.

concentration of precursor chemicals (mainly silane) and the type of carrier gas (hydrogen or helium). Our energy estimate for the HTCVD process is based on the 50 kW reactor used by Elhaddad which was used to produce 100 mm diameter substrates.47 We assume a 350 μm/h growth rate, leading to 2 h and 100 kWh to obtain a 700 μm thick, 100 mm diameter raw substrate. This energy estimate is scaled linearly to adjust for the small difference in area between 100 mm diameter substrates and 4 in. diameter substrates, such that a raw 4 in. substrate is estimated to require 103.2 kWh. It is further assumed the 700 μm thick raw substrate will have a final thickness of 350 μm, that is, the same as assumed in the modified Lely case, after slicing and polishing losses. Similarly, we assume that a sliced and polished substrate produced by HTCVD will incur the same subsequent substrate and front end processing steps as those assumed in the modified Lely case and detailed in Table S1. As in the case of modified Lely, it assumed that total good die area is 44.94 cm2. Thus, the HTCVD process is estimated to require 2.30 kWh/cm2 before considering the additional substrate steps of core fabrication, slicing, beveling, polishing, and cleaning as shown in Table S1. With these additional steps added to the HTCVD energy estimate, substrate and front end processing electrical energy requirements are estimated to be 2.78 kWh/cm2 and 2.43 kWh/cm2, respectively, or 5.21 kWh/cm2 in total. This is a nearly 20% decrease from the modified Lely case, but is a conservatively high estimate as these data are based on lab scale equipment and die yields equivalent to modified Lely. 4.3. Si/Si. Publicly available life cycle data for a Si/Si power electronics device were not identified. As such, substrate and front end processing energy estimates developed by Williams16 for dynamic random-access memory (DRAM) chips on 200 mm diameter wafers are adopted for this analysis. Presently, most insulated-gate bipolar transistors (IGBTs), a Si/Si power electronics device used extensively in electric vehicles, are also manufactured on 200 mm wafers.53 Williams estimates substrate and front end processing of Si/Si DRAM to require 0.34 kWh/cm2 and 1.5 kWh/cm2, respectively.16 Adjusting for a stated yield of 75%, Williams’ estimates indicate 0.45 kWh/ cm2 and 2.00 kWh/cm2 for substrate and front end processing, respectively.16 Thus, our manufacturing energy estimate for Si/ Si power electronics devices is 2.45 kWh/cm2, suggesting SiC/ SiC requires greater than 2.5 times the energy of Si/Si. 4.4. GaN/Si. GaN/Si estimates are developed by aggregating two previous life cycle assessments. The Williams estimate of 0.34 kWh/cm2 is used for substrate production.16 Front end processing energy estimates of a GaN device are taken from25 which examines the life cycle energy requirements of GaN LEDs on sapphire substrates. In ref 25, 42.57 kWh are expended in the front end processing of 3 in. diameter wafers having a planform area of 45.60 cm2. A total of 2438 good die, each with planform area of 0.98 mm2, are obtained from each wafer, indicating 23.89 cm2 of functional die area per wafer or 1.78 kWh/cm2.25 Thus, the energy requirements for a GaN/Si device are estimated to be 0.65 kWh/cm2 (yield adjusted) and 1.78 kWh/cm2 for substrate and front end processing, respectively, or 2.43 kWh/cm2 total. This estimate is more or less equivalent to the Si/Si estimate of 2.45 kWh/cm2. The manufacturing energy estimates of the four pathways discussed above are summarized in Table 1. In electric vehicles, power electronics are present in the motor inverter and buck/boost converter for HEVs, PHEVs, and BEVs, while the latter two have power electronics also

4. MATERIALS AND MANUFACTURING PHASE ANALYSIS We conducted energy analysis of substrate and front end processing for four power electronics device architectures: SiC/ SiC-Modified Lely; SiC/SiC-High Temperature Chemical Vapor Deposition; Si/Si; and GaN/Si. 4.1. SiC/SiC-Modified Lely. A major difference between SiC/SiC and Si/Si semiconductor manufacturing is the substrate production phase where the modified slower energy-intensive vapor phase Lely process is typically used in the former for boule growth as the liquid phase Czochralski process is not possible.46 Micropipes are crystal defects which occur in SiC boules when grown with the modified Lely process, resulting in reduced die yields compared with Si/Si. Furthermore, SiC is one of the hardest known substances, complicating wafer sawing. The question arises, then, if SiCbased power electronics will be advantageous in electric vehicles from a life cycle energy perspective. An industry consultant’s teardown analysis26 of 600 V SiC/ SiC Schottky diodes from various manufacturers is the source for our SiC/SiC−modified Lely energy estimate and is based on 4 in. diameter wafers. The functional unit is one square centimeter of functional die, that is, material losses from the wafer perimeter, sawing, and nonfunctional die are accounted for. We assume a total wafer planform area of 81.07 cm2 from which 1904 good die may be potentially obtained. The actual number of good die obtained is assumed to be 1314, indicating a 69% yield. Furthermore, each die is assumed to have a planform area of 3.42 mm2 (mm2), leading to 44.94 cm2 of functional die area obtained from each wafer. Upstream substrate production is assumed to entail a 100 000 μm (μm) boule having a 66 000 μm usable height, from which 94 potential substrates of 350 μm final thickness are obtained after accounting for slicing and polishing losses per substrates of 200 and 150 μm, respectively. Substrate yield is assumed to be 50% such that 47 usable substrates are obtained per boule. With these assumptions, substrate and front end processing electrical energy requirements are estimated to be 4.04 kWh/cm2 and 2.43 kWh/cm2, respectively, or 6.47 kWh/cm2 in total. The yield adjusted energy consumption obtained from18 for each of the process steps in substrate and front end processing is listed in Table S1. 4.2. SiC/SiC, High Temperature Chemical Vapor Deposition. Recently, the growth of SiC substrates using the high temperature chemical vapor deposition (HTCVD) process has attracted the attention of semiconductor manufacturers because of its ability to overcome the key hurdle of producing a relatively defect-free structure compared with the modified Lely process.47−49 Due to the potential for very low micropipe density and concomitant improved processing yield and device reliability,50 the HTCVD process is also considered for substrate processing in this analysis. Literature suggests that growth rates up to 1.0 mm/h can be achieved with the HTCVD process,49 but may result in a higher micropipe density.47 However, at higher growth rates (0.8−1.0 mm/h), micropipe density is observed to be high.47 Further research is needed to reduce crystal defects while maintaining exceptionally high growth rates such as 350 μm/h in HTCVD.47 The consumption of electrical energy in the HTCVD process is affected by many factors such as temperature gradients, 10297

DOI: 10.1021/acs.est.5b01627 Environ. Sci. Technol. 2015, 49, 10294−10302

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Environmental Science & Technology Table 1. Substrate and Front End Electrical Energy Estimates (kWh/cm2) manufacturing stage

Si/Si (incumbent)

substrate

0.45 kWh/ cm2 2.00 kWh/ cm2 2.45 kWh/ cm2

front end total

SiC/SiC (modified lely)

SiC/SiC (HTCVD)

GaN/Si (state of the art)

4.04 kWh/ cm2 2.43 kWh/ cm2 6.47 kWh/ cm2

2.78 kWh/ cm2 2.43 kWh/ cm2 5.21 kWh/ cm2

0.65 kWh/ cm2 1.78 kWh/ cm2 2.43 kWh/ cm2

Table 2. Comparison of Manufacturing and Use Phase Energy Requirements of Si/Si-Based and SiC/SiC-Based Motor Inverter Si/Si 2

total die area cm substrate and front end electrical energy kWh/cm2 total vehicle substrate and front end electrical energy kWh fuel economy L/100 km lifetime driving distance km lifetime fuel consumption L lifetime fuel consumption kWh total substrate, front end, and use phase direct energy kWh net life cycle energy change from Si/Si kWh

present in the battery charger. Total die area per vehicle varies across different vehicle types according to vehicle mass, degree of electrification, and other factors. One study54 reports the motor inverter total die area in three popular Japanese HEVs using Si/Si IGBTs and diodes to be in the range of 20.71 cm2 − 34.43 cm2. Due to dominant market share of a popular Japanese hybrid vehicle in the market today, we extend our analysis to the lower range value of the motor inverter total die area used in that particular Japanese hybrid vehicle. We conservatively assume a SiC/SiC-based motor inverter has the same die area as the Si/ Si-based motor inverter, that is, 20.71 cm2. However, it is noted that the potential for die area reductions of up to 50% have been shown for other components such as the buck/boost converter due to the outperformance of SiC.55 It is further assumed that a GaN/Si-based vehicle will also have motor inverter die area equivalent to that of a Si/Si-based vehicle. Total substrate and front end electrical energy requirements per vehicle are estimated to be 133.83 kWh, 50.81 kWh, and 50.34 kWh for SiC/SiC-modified Lely, Si/Si, and GaN/Si, respectively. Thus, the SiC/SiC vehicle requires more than twice the substrate and front end electrical energy requirements of the conventional Si/Si vehicle. The GaN/Si and Si/Si vehicles are nearly the same.

SiC/SiC

20.71 2.45 50.81

20.71 6.47 133.83

3.94 250 000 9850 95 764 95 815

3.36 250 000 8 400 81 667 81 801 −14 014

than the conventional Si/Si vehicle. Clearly, the additional investment of 83.02 kWh in the materials and manufacturing phase for the SiC/SiC vehicle is favorable in terms of life cycle direct energy consumption, which is reduced by 14 014 kWh. The previously discussed materials and manufacturing energy inputs outside the study boundary (e.g., chemicals, transport, etc.) cause the net savings estimate to be only slightly overstated, and their inclusion would not alter the overall conclusion that any additional cradle-to-gate energy consumption for the WBG pathway is nearly negligible. Although we do not develop the manufacturing case for a PHEV or BEV, it is noted that the fuel economies of the SiC/ SiC and Si/Si PHEVs modeled in12 have been estimated to be 2.44 L/100 km and 2.98 L/100 km, respectively, representing an 18.1% improvement, which is greater than the 14.7% improvement in the HEV case. Furthermore, its all-electric driving range shows a 27.5% improvement from 425.1 Joules per meter (J/m) to 308.1 J/m.12 The life cycle energy benefit with GaN/Si versus Si/Si is expected to exceed the SiC/SiC cases due to lower cradle-to-gate energy and better material properties (larger band gap and higher electron mobility) than SiC. Additional energy reductions are also anticipated with using WBG semiconductors in other components such as the buck/boost converter and battery charger, although no attempt to quantify these has been made in the present study. In our analysis of WBG in vehicle use for the scenarios detailed in Table S2, we apply a 14.7% improvement in fuel economy to all HEVs using WBGs, an 18.1% improvement to all PHEVs using WBGs, and a 27.5% improvement to all BEVs using WBGs. The HEV and PHEV savings are taken directly from Zhang,12 and the BEV savings are based on the improvement in all-electric driving range for PHEVs they report. While the analysis by Zhang12 is performed for SiC/SiC semiconductors, we apply these results to GaN/Si semiconductors as well. Theoretical performance levels suggest that GaN/Si could provide even greater efficiency improvements, but we adopt the conservative assumption that the same fuel economy savings could be achieved by GaN as has been found for SiC. Given this assumption, we evaluate the use-phase impacts considering a generic WBG that could be SiC/SiC or GaN/Si. The results for the six use-phase scenarios are provided in Table 3. These energy results include the cradle-to-gate energy to manufacture the semiconductors in HEV, PHEV, and BEV sold each year (