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1. Engineering the interface chemistry for scandium electron contacts in WSe ₂ transistors and diodes

   https://doi.org/10.1088/2053-1583/ab2c44  

   Smyth, Christopher M. ; Walsh, Lee A. ; Bolshakov, Pavel ; Catalano, Massimo ; Schmidt, Michael ; Sheehan, Brendan ; Addou, Rafik ; Wang, Luhua ; Kim, Jiyoung ; Kim, Moon J. ; et al ( July 2019 , 2D Materials)

   Sc has been employed as an electron contact to a number of two-dimensional (2D) materials (e.g. MoS₂, black phosphorous) and has enabled, at times, the lowest electron contact resistance. However, the extremely reactive nature of Sc leads to stringent processing requirements and metastable device performance with no true understanding of how to achieve consistent, high-performance Sc contacts. In this work, WSe₂transistors with impressive subthreshold slope (109 mV dec⁻¹) andI_ON/I_OFF(10⁶) are demonstrated without post-metallization processing by depositing Sc contacts in ultra-high vacuum (UHV) at room temperature (RT). The lowest electron Schottky barrier height (SBH) is achieved by mildly oxidizing the WSe₂in situbefore metallization, which minimizes subsequent reactions between Sc and WSe₂. Post metallization anneals in reducing environments (UHV, forming gas) degrade theI_ON/I_OFFby ~10³and increase the subthreshold slope by a factor of 10. X-ray photoelectron spectroscopy indicates the anneals increase the electron SBH by 0.4–0.5 eV and correspondingly convert 100% of the deposited Sc contacts to intermetallic or scandium oxide. Raman spectroscopy and scanning transmission electron microscopy highlight the highly exothermic reactions between Sc and WSe₂, which consume at least one layer RT and at least three layers after the 400 °C anneals. The observed layer consumption necessitates multiple sacrificial WSe₂layers duringmore »fabrication. Scanning tunneling microscopy/spectroscopy elucidate the enhanced local density of states below the WSe₂Fermi level around individual Sc atoms in the WSe₂lattice, which directly connects the scandium selenide intermetallic with the unexpectedly large electron SBH. The interface chemistry and structural properties are correlated with Sc–WSe₂transistor and diode performance. The recommended combination of processing conditions and steps is provided to facilitate consistent Sc contacts to WSe₂.

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2. Effects of Downstream Plasma Exposure on β-Ga ₂ O ₃ Rectifiers

   https://doi.org/10.1149/2162-8777/ac0500  

   Xia, Xinyi ; Xian, Minghan ; Fares, Chaker ; Ren, Fan ; Kim, Junghun ; Kim, Jihyun ; Tadjer, Marko ; Pearton, Stephen J. ( June 2021 , ECS Journal of Solid State Science and Technology)

   The effects of downstream plasma exposure with O 2 , N 2 or CF 4 discharges on Si-doped Ga 2 O 3 Schottky diode forward and reverse current-voltage characteristics were investigated. The samples were exposed to discharges with rf power of 50 W plasma at a pressure of 400 mTorr and a fixed treatment time of 1 min to simulate dielectric layer removal, photoresist ashing or surface cleaning steps. Schottky contacts were deposited through a shadow mask after exposure to avoid any changes to the surface. A Schottky barrier height of 1.1 eV was obtained for the reference sample without plasma treatment, with an ideality factor of 1.0. The diodes exposed to CF 4 showed a 0.25 V shift from the I–V of the reference sample due to a Schottky barrier height lowering around 14%. The diodes showed a decrease of Schottky barrier height of 2.5 and 6.5% with O 2 or N 2 treatments, respectively. The effect of plasma exposure on the ideality factor of diodes treated with these plasmas was minimal; 0.2% for O 2 and N 2 , 0.3% for CF 4 , respectively. The reverse leakage currents were 1.2, 2.2 and 4.8 μ A cm −2more »for the diodes treated with O 2 , and CF 4 , and N 2 respectively. The effect of downstream plasma treatment on diode on-resistance and on-off ratio were also minimal. The changes observed are much less than caused by exposure to hydrogen-containing plasmas and indicate that downstream plasma stripping of films from Ga 2 O 3 during device processing is a relatively benign approach.« less
3. Photovoltaic Response of Thin-Film CdTe Solar Cells under Accelerated Neutron Radiation in a TRIGA Reactor

   Powell, Kaden ; Lund, Matthew ; Wang, Meng-Jen ; Qian, Yang ; Magginetti, David ; Reese, Matthew ; Cazalas, Edward ; Sjoden, Glenn ; Yoon, Heayoung ( June 2020 , Electronic Materials Symposium)

   Cadmium telluride (CdTe) solar cells are a promising photovoltaic (PV) technology for producing power in space owing to their high-efficiency (> 22.1 %), potential for specific power, and cost-effective manufacturing processes. In contrast to traditional space PVs, the high-Z (atomic number) CdTe absorbers can be intrinsically robust under extreme space radiation, offering long-term stability. Despite these advantages, the performance assessment of CdTe solar cells under high-energy particle irradiation (e.g., photons, neutrons, charged particles) is limited in the literature, and their stability is not comprehensively studied. In this work, we present the PV response of n-CdS / p-CdTe PVs under accelerated neutron irradiation. We measure PV properties of the devices at different neutron/photon doses. The equivalent dose deposited in the CdTe samples is simulated with deterministic and Monte Carlo radiation transport methods. Thin-film CdTe solar cells were synthesized on a fluorine-doped tin oxide (FTO) coated glass substrate (≈ 4 cm × 4 cm). CdS:O (≈ 100 nm) was reactively RF sputtered in an oxygen/argon ambient followed by a close-spaced sublimation deposition of CdTe (≈ 3.5 μm) in an oxygen/helium ambient. The sample was exposed to a 10 min vapor CdCl2 in oxygen/helium ambient at 430˚C. The samples were exposed to amore »wet CuCl2 solution prior to anneal 200ºC. A gold back-contact was formed on CdTe via thermal evaporation. The final sample contains 16 CdTe devices. For neutron irradiation, we cleaved the CdTe substrate into four samples and exposed two samples to ≈ 90 kW reactor power neutron radiation for 5.5 hours and 8.2 hours, respectively, in our TRIGA (Training, Research, Isotopes, General Atomics) reactor. We observed a noticeable color change of the glass substrates to brown after the neutron/gamma reactor exposure. Presumably, the injected high-energy neutrons caused the breaking of chemical bonds and the displacement of atoms in the glass substrates, creating point defects and color centers. The I-V characteristics showed noticeable deterioration with over 8 hour radiations. Specifically, the saturation current of the control devices was ≈ 25 nA increasing to 1 μA and 10 μA for the 5.5-hour and 8.2-hour radiated samples, respectively. The turn-on voltage of the control devices (≈ 0.85 V) decreased with the irradiated sample (≈ 0.75 V for 5.5-hour and ≈ 0.5 V for 8.2-hour exposures), implying noticeable radiation damage occurred at the heterojunction. The higher values of the ideality factor for irradiated devices (n > 2.2) compared to that of the control devices (n ≈ 1.3) also support the deterioration of the p-n junction. We observed the notable decrease in shunt resistance (RSH) and the increase in series resistance (Rs) with the neutron dose. It is possible that Cu ions introduced during the CuCl2 treatment may migrate into CdTe grain boundaries (GBs). The presence of Cu ions at GBs can create additional leakage paths for photocarrier transport, deteriorating the overall PV performance. We estimated the radiation dose of CdTe in comparison to Si (conventional PV) using a UUTR model (e.g., MCNP6 2D UTR Reactor simulations). In this model, we simulated Si and CdTe at the center point of the triangular fuel lattice and used an “unperturbed flux” tally in the water. Our simulations yielded a dose rate of 6916 Gy/s of neutrons and 16 Gy/s of photons for CdTe, and 1 Gy/s of neutrons and 21 Gy/s of photons for Si (doses +/- <1%). The large dose rate of neutrons in CdTe is mainly attributed to the large thermal neutron absorption cross-section of 113Cd. Based on this estimation, we calculate that the exposure of our CdTe PVs is equivalent to several million years in LEO (Low-Earth Orbit), or about 10,000 years for Si in LEO. Currently, we are working on a low-dose neutron/photon radiation on CdTe PVs and their light I-Vs and microstructural characterizations to gain better understanding on the degradation of CdTe PVs.« less
4. RTD Light Emission around 1550 nm with IQE up to 6% at 300 K

   https://doi.org/10.1109/DRC50226.2020.9135175  

   Brown, E. R. ; Zhang, W-D. ; Fakhimi, P. ; Growden, T. A. ; Berger, P.R. ( June 2020 , IEEE Device Research Conference (DRC), Columbus, OH (June 22-24, 2020))

   Resonant tunneling diodes (RTDs) have come full-circle in the past 10 years after their demonstration in the early 1990s as the fastest room-temperature semiconductor oscillator, displaying experimental results up to 712 GHz and fmax values exceeding 1.0 THz [1]. Now the RTD is once again the preeminent electronic oscillator above 1.0 THz and is being implemented as a coherent source [2] and a self-oscillating mixer [3], amongst other applications. This paper concerns RTD electroluminescence – an effect that has been studied very little in the past 30+ years of RTD development, and not at room temperature. We present experiments and modeling of an n-type In0.53Ga0.47As/AlAs double-barrier RTD operating as a cross-gap light emitter at ~300K. The MBE-growth stack is shown in Fig. 1(a). A 15-μm-diam-mesa device was defined by standard planar processing including a top annular ohmic contact with a 5-μm-diam pinhole in the center to couple out enough of the internal emission for accurate free-space power measurements [4]. The emission spectra have the behavior displayed in Fig. 1(b), parameterized by bias voltage (VB). The long wavelength emission edge is at  = 1684 nm - close to the In0.53Ga0.47As bandgap energy of Ug ≈ 0.75 eV at 300 K.more »The spectral peaks for VB = 2.8 and 3.0 V both occur around  = 1550 nm (h = 0.75 eV), so blue-shifted relative to the peak of the “ideal”, bulk InGaAs emission spectrum shown in Fig. 1(b) [5]. These results are consistent with the model displayed in Fig. 1(c), whereby the broad emission peak is attributed to the radiative recombination between electrons accumulated on the emitter side, and holes generated on the emitter side by interband tunneling with current density Jinter. The blue-shifted main peak is attributed to the quantum-size effect on the emitter side, which creates a radiative recombination rate RN,2 comparable to the band-edge cross-gap rate RN,1. Further support for this model is provided by the shorter wavelength and weaker emission peak shown in Fig. 1(b) around = 1148 nm. Our quantum mechanical calculations attribute this to radiative recombination RR,3 in the RTD quantum well between the electron ground-state level E1,e, and the hole level E1,h. To further test the model and estimate quantum efficiencies, we conducted optical power measurements using a large-area Ge photodiode located ≈3 mm away from the RTD pinhole, and having spectral response between 800 and 1800 nm with a peak responsivity of ≈0.85 A/W at  =1550 nm. Simultaneous I-V and L-V plots were obtained and are plotted in Fig. 2(a) with positive bias on the top contact (emitter on the bottom). The I-V curve displays a pronounced NDR region having a current peak-to-valley current ratio of 10.7 (typical for In0.53Ga0.47As RTDs). The external quantum efficiency (EQE) was calculated from EQE = e∙IP/(∙IE∙h) where IP is the photodiode dc current and IE the RTD current. The plot of EQE is shown in Fig. 2(b) where we see a very rapid rise with VB, but a maximum value (at VB= 3.0 V) of only ≈2×10-5. To extract the internal quantum efficiency (IQE), we use the expression EQE= c ∙i ∙r ≡ c∙IQE where ci, and r are the optical-coupling, electrical-injection, and radiative recombination efficiencies, respectively [6]. Our separate optical calculations yield c≈3.4×10-4 (limited primarily by the small pinhole) from which we obtain the curve of IQE plotted in Fig. 2(b) (right-hand scale). The maximum value of IQE (again at VB = 3.0 V) is 6.0%. From the implicit definition of IQE in terms of i and r given above, and the fact that the recombination efficiency in In0.53Ga0.47As is likely limited by Auger scattering, this result for IQE suggests that i might be significantly high. To estimate i, we have used the experimental total current of Fig. 2(a), the Kane two-band model of interband tunneling [7] computed in conjunction with a solution to Poisson’s equation across the entire structure, and a rate-equation model of Auger recombination on the emitter side [6] assuming a free-electron density of 2×1018 cm3. We focus on the high-bias regime above VB = 2.5 V of Fig. 2(a) where most of the interband tunneling should occur in the depletion region on the collector side [Jinter,2 in Fig. 1(c)]. And because of the high-quality of the InGaAs/AlAs heterostructure (very few traps or deep levels), most of the holes should reach the emitter side by some combination of drift, diffusion, and tunneling through the valence-band double barriers (Type-I offset) between InGaAs and AlAs. The computed interband current density Jinter is shown in Fig. 3(a) along with the total current density Jtot. At the maximum Jinter (at VB=3.0 V) of 7.4×102 A/cm2, we get i = Jinter/Jtot = 0.18, which is surprisingly high considering there is no p-type doping in the device. When combined with the Auger-limited r of 0.41 and c ≈ 3.4×10-4, we find a model value of IQE = 7.4% in good agreement with experiment. This leads to the model values for EQE plotted in Fig. 2(b) - also in good agreement with experiment. Finally, we address the high Jinter and consider a possible universal nature of the light-emission mechanism. Fig. 3(b) shows the tunneling probability T according to the Kane two-band model in the three materials, In0.53Ga0.47As, GaAs, and GaN, following our observation of a similar electroluminescence mechanism in GaN/AlN RTDs (due to strong polarization field of wurtzite structures) [8]. The expression is Tinter = (2/9)∙exp[(-2 ∙Ug 2 ∙me)/(2h∙P∙E)], where Ug is the bandgap energy, P is the valence-to-conduction-band momentum matrix element, and E is the electric field. Values for the highest calculated internal E fields for the InGaAs and GaN are also shown, indicating that Tinter in those structures approaches values of ~10-5. As shown, a GaAs RTD would require an internal field of ~6×105 V/cm, which is rarely realized in standard GaAs RTDs, perhaps explaining why there have been few if any reports of room-temperature electroluminescence in the GaAs devices. [1] E.R. Brown,et al., Appl. Phys. Lett., vol. 58, 2291, 1991. [5] S. Sze, Physics of Semiconductor Devices, 2nd Ed. 12.2.1 (Wiley, 1981). [2] M. Feiginov et al., Appl. Phys. Lett., 99, 233506, 2011. [6] L. Coldren, Diode Lasers and Photonic Integrated Circuits, (Wiley, 1995). [3] Y. Nishida et al., Nature Sci. Reports, 9, 18125, 2019. [7] E.O. Kane, J. of Appl. Phy 32, 83 (1961). [4] P. Fakhimi, et al., 2019 DRC Conference Digest. [8] T. Growden, et al., Nature Light: Science & Applications 7, 17150 (2018). [5] S. Sze, Physics of Semiconductor Devices, 2nd Ed. 12.2.1 (Wiley, 1981). [6] L. Coldren, Diode Lasers and Photonic Integrated Circuits, (Wiley, 1995). [7] E.O. Kane, J. of Appl. Phy 32, 83 (1961). [8] T. Growden, et al., Nature Light: Science & Applications 7, 17150 (2018).« less
5. Phosphorus availability and leaching losses in annual and perennial cropping systems in an upper US Midwest landscape

   https://doi.org/10.5061/dryad.8sf7m0cpx  

   Hussain, Mir Zaman ; Hamilton, Stephen ; Robertson, G. Philip ; Basso, Bruno ( January 2021 )

   Abstract

   Excessive phosphorus (P) applications to croplands can contribute to eutrophication of surface waters through surface runoff and subsurface (leaching) losses. We analyzed leaching losses of total dissolved P (TDP) from no-till corn, hybrid poplar (Populus nigra X P. maximowiczii), switchgrass (Panicum virgatum), miscanthus (Miscanthus giganteus), native grasses, and restored prairie, all planted in 2008 on former cropland in Michigan, USA. All crops except corn (13 kg P ha−1 year−1) were grown without P fertilization. Biomass was harvested at the end of each growing season except for poplar. Soil water at 1.2 m depth was sampled weekly to biweekly for TDP determination during March–November 2009–2016 using tension lysimeters. Soil test P (0–25 cm depth) was measured every autumn. Soil water TDP concentrations were usually below levels where eutrophication of surface waters is frequently observed (&gt; 0.02 mg L−1) but often higher than in deep groundwater or nearby streams and lakes. Rates of P leaching, estimated from measured concentrations and modeled drainage, did not differ statistically among cropping systems across years; 7-year cropping system means ranged from 0.035 to 0.072 kg P ha−1 year−1 with large interannual variation. Leached P was positively related to STP, which decreased over the 7 years in all systems. These results indicate that both P-fertilized and unfertilized cropping systems may leach legacy P from past cropland management.
   

   Methods

   Experimental details The Biofuel Cropping System Experiment (BCSE) is located at the W.K. Kellogg Biological Station (KBS) (42.3956° N, 85.3749° W; elevation 288 m asl) in southwestern Michigan, USA. This site is a part of the Great Lakes Bioenergy Research Center (www.glbrc.org) and is a Long-term Ecological Research site (www.lter.kbs.msu.edu). Soils are mesic Typic Hapludalfs developed on glacial outwash54 with high sand content (76% in the upper 150 cm) intermixed with silt-rich loess in the upper 50 cm55. The water table lies approximately 12–14 m below the surface. The climate is humid temperate with a mean annual air temperature of 9.1 °C and annual precipitation of 1005 mm, 511 mm of which falls between May and September (1981–2010)56,57. The BCSE was established as a randomized complete block design in 2008 on preexisting farmland. Prior to BCSE establishment, the field was used for grain crop and alfalfa (Medicago sativa L.) production for several decades. Between 2003 and 2007, the field received a total of ~ 300 kg P ha−1 as manure, and the southern half, which contains one of four replicate plots, received an additional 206 kg P ha−1 as inorganic fertilizer. The experimental design consists of five randomized blocks each containing one replicate plot (28 by 40 m) of 10 cropping systems (treatments) (Supplementary Fig. S1; also see Sanford et al.58). Block 5 is not included in the present study. Details on experimental design and site history are provided in Robertson and Hamilton57 and Gelfand et al.59. Leaching of P is analyzed in six of the cropping systems: (i) continuous no-till corn, (ii) switchgrass, (iii) miscanthus, (iv) a mixture of five species of native grasses, (v) a restored native prairie containing 18 plant species (Supplementary Table S1), and (vi) hybrid poplar. Agronomic management Phenological cameras and field observations indicated that the perennial herbaceous crops emerged each year between mid-April and mid-May. Corn was planted each year in early May. Herbaceous crops were harvested at the end of each growing season with the timing depending on weather: between October and November for corn and between November and December for herbaceous perennial crops. Corn stover was harvested shortly after corn grain, leaving approximately 10 cm height of stubble above the ground. The poplar was harvested only once, as the culmination of a 6-year rotation, in the winter of 2013–2014. Leaf emergence and senescence based on daily phenological images indicated the beginning and end of the poplar growing season, respectively, in each year. Application of inorganic fertilizers to the different crops followed a management approach typical for the region (Table 1). Corn was fertilized with 13 kg P ha−1 year−1 as starter fertilizer (N-P-K of 19-17-0) at the time of planting and an additional 33 kg P ha−1 year−1 was added as superphosphate in spring 2015. Corn also received N fertilizer around the time of planting and in mid-June at typical rates for the region (Table 1). No P fertilizer was applied to the perennial grassland or poplar systems (Table 1). All perennial grasses (except restored prairie) were provided 56 kg N ha−1 year−1 of N fertilizer in early summer between 2010 and 2016; an additional 77 kg N ha−1 was applied to miscanthus in 2009. Poplar was fertilized once with 157 kg N ha−1 in 2010 after the canopy had closed. Sampling of subsurface soil water and soil for P determination Subsurface soil water samples were collected beneath the root zone (1.2 m depth) using samplers installed at approximately 20 cm into the unconsolidated sand of 2Bt2 and 2E/Bt horizons (soils at the site are described in Crum and Collins54). Soil water was collected from two kinds of samplers: Prenart samplers constructed of Teflon and silica (http://www.prenart.dk/soil-water-samplers/) in replicate blocks 1 and 2 and Eijkelkamp ceramic samplers (http://www.eijkelkamp.com) in blocks 3 and 4 (Supplementary Fig. S1). The samplers were installed in 2008 at an angle using a hydraulic corer, with the sampling tubes buried underground within the plots and the sampler located about 9 m from the plot edge. There were no consistent differences in TDP concentrations between the two sampler types. Beginning in the 2009 growing season, subsurface soil water was sampled at weekly to biweekly intervals during non-frozen periods (April–November) by applying 50 kPa of vacuum to each sampler for 24 h, during which the extracted water was collected in glass bottles. Samples were filtered using different filter types (all 0.45 µm pore size) depending on the volume of leachate collected: 33-mm dia. cellulose acetate membrane filters when volumes were less than 50 mL; and 47-mm dia. Supor 450 polyethersulfone membrane filters for larger volumes. Total dissolved phosphorus (TDP) in water samples was analyzed by persulfate digestion of filtered samples to convert all phosphorus forms to soluble reactive phosphorus, followed by colorimetric analysis by long-pathlength spectrophotometry (UV-1800 Shimadzu, Japan) using the molybdate blue method60, for which the method detection limit was ~ 0.005 mg P L−1. Between 2009 and 2016, soil samples (0–25 cm depth) were collected each autumn from all plots for determination of soil test P (STP) by the Bray-1 method61, using as an extractant a dilute hydrochloric acid and ammonium fluoride solution, as is recommended for neutral to slightly acidic soils. The measured STP concentration in mg P kg−1 was converted to kg P ha−1 based on soil sampling depth and soil bulk density (mean, 1.5 g cm−3). Sampling of water samples from lakes, streams and wells for P determination In addition to chemistry of soil and subsurface soil water in the BCSE, waters from lakes, streams, and residential water supply wells were also sampled during 2009–2016 for TDP analysis using Supor 450 membrane filters and the same analytical method as for soil water. These water bodies are within 15 km of the study site, within a landscape mosaic of row crops, grasslands, deciduous forest, and wetlands, with some residential development (Supplementary Fig. S2, Supplementary Table S2). Details of land use and cover change in the vicinity of KBS are given in Hamilton et al.48, and patterns in nutrient concentrations in local surface waters are further discussed in Hamilton62. Leaching estimates, modeled drainage, and data analysis Leaching was estimated at daily time steps and summarized as total leaching on a crop-year basis, defined from the date of planting or leaf emergence in a given year to the day prior to planting or emergence in the following year. TDP concentrations (mg L−1) of subsurface soil water were linearly interpolated between sampling dates during non-freezing periods (April–November) and over non-sampling periods (December–March) based on the preceding November and subsequent April samples. Daily rates of TDP leaching (kg ha−1) were calculated by multiplying concentration (mg L−1) by drainage rates (m3 ha−1 day−1) modeled by the Systems Approach for Land Use Sustainability (SALUS) model, a crop growth model that is well calibrated for KBS soil and environmental conditions. SALUS simulates yield and environmental outcomes in response to weather, soil, management (planting dates, plant population, irrigation, N fertilizer application, and tillage), and genetics63. The SALUS water balance sub-model simulates surface runoff, saturated and unsaturated water flow, drainage, root water uptake, and evapotranspiration during growing and non-growing seasons63. The SALUS model has been used in studies of evapotranspiration48,51,64 and nutrient leaching20,65,66,67 from KBS soils, and its predictions of growing-season evapotranspiration are consistent with independent measurements based on growing-season soil water drawdown53 and evapotranspiration measured by eddy covariance68. Phosphorus leaching was assumed insignificant on days when SALUS predicted no drainage. Volume-weighted mean TDP concentrations in leachate for each crop-year and for the entire 7-year study period were calculated as the total dissolved P leaching flux (kg ha−1) divided by the total drainage (m3 ha−1). One-way ANOVA with time (crop-year) as the fixed factor was conducted to compare total annual drainage rates, P leaching rates, volume-weighted mean TDP concentrations, and maximum aboveground biomass among the cropping systems over all seven crop-years as well as with TDP concentrations from local lakes, streams, and groundwater wells. When a significant (α &#61; 0.05) difference was detected among the groups, we used the Tukey honest significant difference (HSD) post-hoc test to make pairwise comparisons among the groups. In the case of maximum aboveground biomass, we used the Tukey–Kramer method to make pairwise comparisons among the groups because the absence of poplar data after the 2013 harvest resulted in unequal sample sizes. We also used the Tukey–Kramer method to compare the frequency distributions of TDP concentrations in all of the soil leachate samples with concentrations in lakes, streams, and groundwater wells, since each sample category had very different numbers of measurements.
   

   Other

   Individual spreadsheets in “data table_leaching_dissolved organic carbon and nitrogen.xls” 1.    annual precip_drainage 2.    biomass_corn, perennial grasses 3.    biomass_poplar 4.    annual N leaching _vol-wtd conc 5.    Summary_N leached 6.    annual DOC leachin_vol-wtd conc 7.    growing season length 8.    correlation_nh4 VS no3 9.    correlations_don VS no3_doc VS don Each spreadsheet is described below along with an explanation of variates. Note that ‘nan’ indicate data are missing or not available. First row indicates header; second row indicates units 1. Spreadsheet: annual precip_drainage Description: Precipitation measured from nearby Kellogg Biological Station (KBS) Long Term Ecological Research (LTER) Weather station, over 2009-2016 study period. Data shown in Figure 1; original data source for precipitation (https://lter.kbs.msu.edu/datatables/7). Drainage estimated from SALUS crop model. Note that drainage is percolation out of the root zone (0-125 cm). Annual precipitation and drainage values shown here are calculated for growing and non-growing crop periods. Variate    Description year    year of the observation crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” precip_G    precipitation during growing period (milliMeter) precip_NG    precipitation during non-growing period (milliMeter) drainage_G    drainage during growing period (milliMeter) drainage_NG    drainage during non-growing period (milliMeter)      2. Spreadsheet: biomass_corn, perennial grasses Description: Maximum aboveground biomass measurements from corn, switchgrass, miscanthus, native grass and restored prairie plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Data shown in Figure 2.   Variate    Description year    year of the observation date    day of the observation (mm/dd/yyyy) crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” replicate    each crop has four replicated plots, R1, R2, R3 and R4 station    stations (S1, S2 and S3) of samplings within the plot. For more details, refer to link (https://data.sustainability.glbrc.org/protocols/156) species    plant species that are rooted within the quadrat during the time of maximum biomass harvest. See protocol for more information, refer to link (http://lter.kbs.msu.edu/datatables/36) For maize biomass, grain and whole biomass reported in the paper (weed biomass or surface litter are excluded). Surface litter biomass not included in any crops; weed biomass not included in switchgrass and miscanthus, but included in grass mixture and prairie. fraction    Fraction of biomass biomass_plot    biomass per plot on dry-weight basis (Grams_Per_SquareMeter) biomass_ha    biomass (megaGrams_Per_Hectare) by multiplying column biomass per plot with 0.01 3. Spreadsheet: biomass_poplar Description: Maximum aboveground biomass measurements from poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Data shown in Figure 2. Note that poplar biomass was estimated from crop growth curves until the poplar was harvested in the winter of 2013-14. Variate    Description year    year of the observation method    methods of poplar biomass sampling date    day of the observation (mm/dd/yyyy) replicate    each crop has four replicated plots, R1, R2, R3 and R4 diameter_at_ground    poplar diameter (milliMeter) at the ground diameter_at_15cm    poplar diameter (milliMeter) at 15 cm height biomass_tree    biomass per plot (Grams_Per_Tree) biomass_ha    biomass (megaGrams_Per_Hectare) by multiplying biomass per tree with 0.01 4. Spreadsheet: annual N leaching_vol-wtd conc Description: Annual leaching rate (kiloGrams_N_Per_Hectare) and volume-weighted mean N concentrations (milliGrams_N_Per_Liter) of nitrate (no3) and dissolved organic nitrogen (don) in the leachate samples collected from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for nitrogen leached and volume-wtd mean N concentration shown in Figure 3a and Figure 3b, respectively. Note that ammonium (nh4) concentration were much lower and often undetectable (&lt;0.07 milliGrams_N_Per_Liter). Also note that in 2009 and 2010 crop-years, data from some replicates are missing.    Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” crop-year    year of the observation replicate    each crop has four replicated plots, R1, R2, R3 and R4 no3 leached    annual leaching rates of nitrate (kiloGrams_N_Per_Hectare) don leached    annual leaching rates of don (kiloGrams_N_Per_Hectare) vol-wtd no3 conc.    Volume-weighted mean no3 concentration (milliGrams_N_Per_Liter) vol-wtd don conc.    Volume-weighted mean don concentration (milliGrams_N_Per_Liter) 5. Spreadsheet: summary_N leached Description: Summary of total amount and forms of N leached (kiloGrams_N_Per_Hectare) and the percent of applied N lost to leaching over the seven years for corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for nitrogen amount leached shown in Figure 4a and percent of applied N lost shown in Figure 4b. Note the fraction of unleached N includes in harvest, accumulation in root biomass, soil organic matter or gaseous N emissions were not measured in the study. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” no3 leached    annual leaching rates of nitrate (kiloGrams_N_Per_Hectare) don leached    annual leaching rates of don (kiloGrams_N_Per_Hectare) N unleached    N unleached (kiloGrams_N_Per_Hectare) in other sources are not studied % of N applied N lost to leaching    % of N applied N lost to leaching 6. Spreadsheet: annual DOC leachin_vol-wtd conc Description: Annual leaching rate (kiloGrams_Per_Hectare) and volume-weighted mean N concentrations (milliGrams_Per_Liter) of dissolved organic carbon (DOC) in the leachate samples collected from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for DOC leached and volume-wtd mean DOC concentration shown in Figure 5a and Figure 5b, respectively. Note that in 2009 and 2010 crop-years, water samples were not available for DOC measurements.     Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” crop-year    year of the observation replicate    each crop has four replicated plots, R1, R2, R3 and R4 doc leached    annual leaching rates of nitrate (kiloGrams_Per_Hectare) vol-wtd doc conc.    volume-weighted mean doc concentration (milliGrams_Per_Liter) 7. Spreadsheet: growing season length Description: Growing season length (days) of corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in the Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Date shown in Figure S2. Note that growing season is from the date of planting or emergence to the date of harvest (or leaf senescence in case of poplar).   Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” year    year of the observation growing season length    growing season length (days) 8. Spreadsheet: correlation_nh4 VS no3 Description: Correlation of ammonium (nh4&#43;) and nitrate (no3-) concentrations (milliGrams_N_Per_Liter) in the leachate samples from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2013-2015. Data shown in Figure S3. Note that nh4&#43; concentration in the leachates was very low compared to no3- and don concentration and often undetectable in three crop-years (2013-2015) when measurements are available. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” date    date of the observation (mm/dd/yyyy) replicate    each crop has four replicated plots, R1, R2, R3 and R4 nh4 conc    nh4 concentration (milliGrams_N_Per_Liter) no3 conc    no3 concentration (milliGrams_N_Per_Liter)   9. Spreadsheet: correlations_don VS no3_doc VS don Description: Correlations of don and nitrate concentrations (milliGrams_N_Per_Liter); and doc (milliGrams_Per_Liter) and don concentrations (milliGrams_N_Per_Liter) in the leachate samples of corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2013-2015. Data of correlation of don and nitrate concentrations shown in Figure S4 a and doc and don concentrations shown in Figure S4 b. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” year    year of the observation don    don concentration (milliGrams_N_Per_Liter) no3     no3 concentration (milliGrams_N_Per_Liter) doc    doc concentration (milliGrams_Per_Liter)
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