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Supplementary Materials for - Science...Method for Scratch Hardness, ASTM G171-03(2009) with a...
Transcript of Supplementary Materials for - Science...Method for Scratch Hardness, ASTM G171-03(2009) with a...
science.sciencemag.org/content/364/6442/760/suppl/DC1
Supplementary Materials for
A radiative cooling structural material
Tian Li*, Yao Zhai*, Shuaiming He*, Wentao Gan, Zhiyuan Wei,
Mohammad Heidarinejad, Daniel Dalgo, Ruiyu Mi, Xinpeng Zhao, Jianwei Song,
Jiaqi Dai, Chaoji Chen, Ablimit Aili, Azhar Vellore, Ashlie Martini, Ronggui Yang,
Jelena Srebric, Xiaobo Yin†, Liangbing Hu†
*These authors contributed equally to this work.
†Corresponding author. Email: [email protected] (L.H.); [email protected] (X.Y.)
Published 24 May 2019, Science 364, 760 (2019)
DOI: 10.1126/science.aau9101
This PDF file includes:
Materials and Methods
Supplementary Text
Figs. S1 to S30
Tables S1 and S2
References
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Materials and Methods
Fabrication of the cooling wood
The natural wood block was first cut along the growth direction, which is
compatible with industry cutting methods for making large dimension wood panels. The
wood piece was then delignified with boiling H2O2 (30% solution, EMD Millipore
Corporation) followed by subsequent washing in DI water. The solvent was then replaced
by ethanol (190 proof, Pharmco-Aaper) before hot pressing.
Material characterization
The morphology of the wood samples was characterized by a scanning electron
microscope (SEM, Hitachi SU-70). The FTIR spectrum was obtained by a
ThermoNicolet NEXUS 670 FTIR spectrophotometer. The lignin content was measured
using a standard method (Technical Association of Pulp and Paper Industry Standard
Method T 222-om-83). The tensile strength of the wood was measured with a Tinius
Olsen H5KT testing machine. The test was performed with the upper fixture moving
downward at a constant velocity of 1 mm/min. The scratch hardness characterization
experiments for wood samples were performed in accordance with the Standard Test
Method for Scratch Hardness, ASTM G171-03(2009) with a linear reciprocating
tribometer (Rtec Instruments Multi-function Tribometer). The measurement was carried
out by applying a normal load and moving the specimens at a constant speed to generate
a scratch on the surface. The scratch width was measured using a white light
interferometer and the scratch hardness number (in Gpa) was calculated by kP/w2, where
P is the applied normal force, w is the scratch width and k is the geometrical constant, k =
24.98 when P is in grams-force and w is in µm. Each scratch hardness was calculated by
the arithmetic mean value of three scratches at different locations. The Charpy impact test
of the wood samples was performed on a Tinius Olsen pendulum impact tester. The
dimensions of the samples were 60 mm × 5.5 mm × 2.7 mm. We measured the bending
properties of the wood samples using an Instron 3367 tester. The dimensions for the
bending samples were approximately 60 mm × 5.5 mm × 2.8 mm. Three-point bending
tests were conducted for these samples, with a 35 mm span between the two bottom
rollers and the top roller pressing down on the center at a speed of 1 mm min−1
. We
conducted compression tests on the samples using an Instron 3367 tester. The dimensions
for the compressive samples were approximately 9.5 mm long, 9 mm wide, and 4.5 mm
thick, and the samples were compressed along the thickness direction at a speed of 1 mm
min−1
.
Optical characterization of the cooling wood
The spectroscopic performance of the cooling wood was measured via an
integrating-sphere-based characterization method. The polarization-dependent optical
reflection spectra in the solar spectrum were tested in response to the incident
polarization angle, whether parallel or perpendicular to the alignment direction of the
cellulose nanofibers. A visible and near-IR linear polarizer was applied to polarize the
incident light in the visible and near-IR region, respectively. The polarizer is placed in
front of the sample compartment of the integrating sphere. θ is the angle between the
directions of the electric field of the incident light and the aligned direction of the
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cellulose nanofibers. The reflectivity spectrum was measured by collecting the spatial
scattered light that is reflected from the sample surface and bounces within the inside
wall of the integrating sphere. The emissivity spectrum was obtained by measuring
reflectivity (R), which was calculated as 1-R where transmittance is negligible.
Thermal conductivity measurement
The thermal conductivities of wood samples were measured by laser flash method.
Laser flash measurement is a widely used transient method to determine the thermal
diffusivities of bulk materials, which employs noncontact and nondestructive temperature
sensing (37). During the measurements, the instantaneous light is used as heat source to
heat up the sample’s front side, and an infrared detector is adopted to record the
temperature response of the rear side. A very thin graphite coating is applied on both
faces of the samples to act as absorber on the front side and as emitter on the rear side.
With the assumption that the heat transfer is one-dimensional, the thermal diffusivity α
can be calculated by, 2
2
1/2
1.38d
t
(1)
where is the thickness of the sample and is the time that takes for the sample
to heat to one half of the maximum temperature on the rear surface. The thermal
conductivity is then calculated by,
pk c (2)
where ρ is the density and cp is the heat capacity. In our measurements, the
commercial Netzsch laser flash apparatus (LFA 457) was used for the thermal diffusivity
measurement and Netzsch differential scanning calorimetry (DSC 204 F1 Phoenix) for
heat capacity measurement, respectively.
Supplementary Text
Theoretical model of the radiative cooling performance of cooling wood
In Fig. S1 (a) we schematically show the direct thermal measurement system, as
tailored to the cooling wood specimens. When the cooling wood faces a clear sky in an
open environment, its surface radiates heat to the sky while absorbing solar irradiance
and downward thermal radiation emitted by atmosphere. At the same time, heat can be
transferred from the ambient surroundings to the wood via conduction and convection
because of the temperature difference between the cooling wood and ambient
environment. This is referred to as non-radiative heat loss. The net cooling power is
expressed as,
net rad atm soalr conv leakP P P P P P (3)
here,
Prad: the power density of thermal radiation emitted by the cooling wood;
Patm: the power density of the downward thermal radiation from the
atmosphere;
Psolar: the heating power density resulting from the absorption of solar irradiance;
Pconv: the convective and conductive power density from the top surface of the
wood;
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Pleak: the thermal leakage from the thermally isolated measurement box.
Prad and Patm are determined by both the spectral data of the cooling wood and the
emissivity spectrum of the atmosphere. The power density of the absorbed solar
irradiance can be assessed by,
solar wood solar0
P cos ( )I ( )d
λ, λ λ (4)
where Isolar() is the solar spectral irradiance and film(,) is the wavelength and
angle-dependent solar absorbance of the cooling wood. Angle φ is normal to the module
and the solar irradiance. The no n-radiative heat exchange, Pconv, is contributed to by heat
conduction and convection from the top surface of the wood. We applied a piece of 10-
m-thick high-density polyethylene (HDPE) film on top of the thermal isolation box to
reduce the conductive and convective heat exchange between the wood and the
environment. Pleak is the thermal leakage from the thermal box made of polystyrene foam
(4-in thick), which is much smaller than Pconv. The radiative cooling power, Prad, is the
only outgoing heat flux that allows cooling of the wood. When the wood temperature is
below ambient, all other power densities of Patm, Psolar, Pconv, and Pleak are inward and
working against the cooling. A Kapton heater is also introduced into the box as an
additional degree of freedom in evaluating the total radiative cooling power (see detailed
experimental procedures described in (9).
The heat exchange coefficient hconv is typically between 5 – 20 W/m2K, which is
sensitive to weather conditions, such as wind speed. Pconv and Pleak can also be
characterized experimentally. As shown in Fig. S1B, a heat flux is fed into the thermal
box using the heater to maintain a constant temperature difference between the wood and
ambient surroundings. The hconv is thus calculated to be ~5.3 W/m2K and the leakage rate
is ~3.2 W/m2K. Here, all radiative heat transfer was blocked and the experiments were
performed indoors.
Using the spectral data of the cooling wood, Prad can be evaluated by integrating the
blackbody radiance and angle-dependent emissivity over the hemisphere. We then
evaluated the net cooling power, netp , for s aT T varying from 230 K to 320 K and for
night-time (without solar irradiance) and daytime conditions (with solar irradiance of 886
W/m2). As shown in Fig. S2A, the daytime and nighttime cooling powers are respectively
37 W/m2 and 101 W/m
2 at Ts = Ta = 300 K. The non-radiative heat exchange effect on
sub-ambient cooling temperature is discussed in Fig. S2B. We consider various non-
radiative heat exchange coefficients from 1.0 W/(m2K) to 15.0 W/(m
2K). As the surface
is cooled below the ambient temperature, heat is induced from the ambient surroundings
to the wood surface through convection and conduction. At the same time, the thermal
radiation decreases as its surface temperature decreases. Finally, the wood reaches a
steady state, where the net cooling power Pnet is equal to zero as the non-radiative heat
cancels out the total radiation. The surface temperature at thermal equilibrium, Teq, is the
lowest temperature that can be cooled to by the cooling wood. The sub-ambient cooling
temperature at thermal equilibrium is the crossing points of the curves on the Ts – Ta axis.
At natural convection condition with hconv = 5.0 W/(m2K) and an ambient temperature of
300 K (27 oC), the cooling wood can in principle create > 6 K and > 12 K below-ambient
cooling temperatures during day- and nighttime operation, respectively. In the following
section, we show quantitative measurements of the newly manufactured, large cooling
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wood, and we demonstrate > 4 K and > 9 K below-ambient cooling temperature during
day- and nighttime operation. The lower below-ambient cooling temperature is due to the
lower average ambient temperature of < 15 oC .
Experimental characterization of large cooling wood
Fig. S3B shows a photo of the direct thermal measurement setup. Two boxes were
constructed. In each box, two pieces of cooling wood with a total size of 200 mm 200
mm were used. One box had the Kapton heater turned ON and a feedback control
program was used to maintain the wood temperature the same as the ambient
temperature. The other box had the Kapton heater turned OFF and the steady state below-
ambient temperature of the wood was tracked over time. The two thermal boxes were
elevated 1.2 meter over the sunlight-shaded ground in order to avoid heat conducted from
ground to the boxes and also avoid overestimation of ambient temperature measured by
the thermal-couples underneath the boxes. The experimental site was located at Cave
Creek, Arizona (33° 49’ 32” N, 112° 1’ 44” W, 585 m altitude). A weather station was
placed beside the thermal box to record the weather conditions at the testing position.
Fig. 2E shows the 24-hr continuous measurement of the 200 mm 200 mm sized
cooling wood. The two thermal boxes allow us to perform two experiments in parallel:
(1) Experiment in Box-1, direct measurement of the radiative cooling power of the
cooling wood by maintaining the wood temperature the same as the ambient to minimize
all convective and conductive heat losses (Fig. 2E upper panel). The heater was ON and a
feedback control program maintained the wood temperature the same as the ambient, Ts =
Ta. At this condition, the heating power is the same as the total radiative cooling power
because all other heat fluxes are zero due to the zero-temperature difference. The
Experiment in Box-2 was the steady-state wood temperature measurement of the cooling
wood (Fig. 2E middle and lower panel). As shown in the upper panel of Fig. 2E, the
average cooling power was 63 W/m2 and 16 W/m
2 during the night and daytime (between
11AM – 2PM), respectively, which matches well with the theoretical predictions. The
average cooling power was 52 W/m2 over the entire 24-h period. As shown in the middle
and lower panels of Fig. 2E, the wood temperature is clearly below ambient over the
entire 24-h period. The average below-ambient temperature was > 9 oC during the night
and > 4 oC during midday (between 11AM – 2PM). The results are close to the
theoretical prediction: at a natural convection condition with hconv = 5.0 W/(m2K) and an
ambient temperature of 30 oC, the cooling wood can in principle create > 6 K and > 12 K
below-ambient cooling temperatures during day- and nighttime operation, respectively.
The small difference is mainly due to the non-ideal convection loss. In Fig. S4, we
tracked the solar irradiance and the wind speed during the experiment. Although the
overall wind speed was mild, the wind speed escalated over the day, which results in a
higher average convective loss.
We compared the ambient temperature measured by our thermal measurement with
that recorded by the weather station over the entire 24-hour test period. As shown in Fig.
S5A the ambient temperature matches well with the local temperature recorded by the
weather station. The difference between the two measured temperatures is much less than
1 ºC over the 24 hour test period. In Fig. S5B, we show the histogram of the temperature
difference for the 24 hour period.
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With the assistance of the feedback-controlled heating system, the cooling wood
temperature was maintained at the ambient temperature to minimize the conductive and
convective heat loss induced from the surrounding environment. The temperature of the
cooling wood matches well with the ambient temperature, as shown in Fig. S6A. The
peak of the temperature difference was less than 0.1 oC, which occurred during noon-time
(Fig. S6B). The histogram of temperature difference over 24 hours is less than 0.1 oC as
well (Fig. S6C). Since the conductive and convection coefficient is mainly dependent on
the weather conditions and the thermal box has demonstrated a 5.3 W/(m2 K) heat loss
coefficient, the heat loss induced from the ambient is negligible during the 24 hours
under the windless condition. Thus, the power provided by the feedback-controlled heat
accurately measures the real-time radiative cooling power.
The measurement error in the radiative cooling power is less than 10 W/m2 based on
the histogram width of the radiative cooling power variation (Fig. S7B). Since the
feedback-controlled heating system maintains the cooling wood at the ambient
temperature, the cooling wood temperature varies by less than 0.1 oC (Fig. S7A). The
momentary oscillation of the feedback heating system causes measurement inaccuracy,
which leads to overestimation of the cooling power. Therefore, we used the real-time
averaged value to evaluate the radiative cooling power.
We also measured the temperature of the cooling wood and natural wood
simultaneously during day-time. The cooling wood and natural wood were placed in two
thermal boxes, separately, when their surfaces were exposed to the sunlight and the
Kapton heaters were off, shown in Fig. S8A. Their temperatures recorded over 30-minute
period from 14:40 to 15:10 are shown in Fig. S8B. The cooling wood exhibited 12 oC
degree lower than natural wood and 2 oC below ambient temperature.
Solar absorbance of lignin and cellulose
To understand the contribution of the remaining lignin in the cooling wood, the
absorption coefficient of lignin was studied. We deposited a pure lignin powder on
transparent tape as shown in the inset of Fig. 13A. The lignin film exhibits a mass density
of 0.77 g/cm3. The absorption coefficient was calculated based on the measured
reflectance and transmittance (Fig. S13A).
We also measured the optical transmittance and reflectance of a transparent
cellulose film with a thickness of 110 µm to calculate the optical absorption coefficient in
the spectrum range (Fig. S13B). Note that the transparent cellulose film is denser with
less scattering centers and a mass density of 1.31 g/cm3. In contrast to the lignin,
cellulose absorption mainly occurs at wavelengths higher than 1 µm.
In cooling wood, the lignin content is only ~0.8%. The lignin mass density in
cooling wood is calculated to be 0.0288 g/cm3. The contribution to the absorption
coefficient by the remaining lignin is calculated based on its mass density and plotted in
Fig. S14 (blue dashed line). The mass density of the cellulose in cooling wood is
calculated to be ~ 1.2 g/cm3. The contribution to the absorption coefficient by the
cellulose component is shown in Fig. S14 (green dashed line). Fig. S14 also shows the
absorptivity measured for cooling wood and natural wood. The cooling wood exhibits a
negligible absorption peak at 367 nm, which indicates the effective removal of lignin
from natural wood. The absorption peaks > 1 µm still exist in cooling wood due to the
absorption contribution from cellulose.
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Effective light scattering by the mesoporous structure of cooling wood with hierarchical
cellulose fibers.
Disordered cellulose reduces the transmission of solar radiation that leads to a lower
solar heating. The underlying physics indicate that the disorder greatly reduces the
scattering mean free path of the cooling wood as well as transmission through the
material. To qualitatively evaluate the effect of scattering centers in the cooling wood, we
measured the reflectivity of the cooling wood (with more scattering centers) in
comparison to a transparent cellulose film (with fewer scattering centers due to a much
smaller thickness and higher packing density compared to cooling wood) (Fig. S15). The
transparent cellulose film exhibits a much lower reflectivity, less than < 10%, while the
reflectivity of the cooling wood is much higher, at 97% between 400 nm to 700 nm.
Cooling wood features a highly mesoporous structure made of densely packed
cellulose nanofibers. Cellulose has a theoretical mass density of 1.50 g/cm3
(38), while
the cooling wood has a density of 1.2 g/cm3, which yields an estimated porosity of
~19.5%. We evaluated the dimensions of the pores via a combination of characterization
methods (39) and determined a multiscale aligned structure with hierarchical pore sizes
as elaborated below.
Polarization dependent reflection
To investigate the effect of nanofiber alignment on the absorbed solar power, the
incoming light was polarized along and across the alignment direction. The polarization-
dependent reflection spectra were characterized on a UV-VIS-NIR spectrophotometer
(PC3101, Shimadzu Inc.) with an integrating sphere. A NIST-certified diffusive mirror
standard (SRS-99-010, Labsphere Inc.) was used as a reference mirror throughout the
measurements. The reflection was higher when the incoming polarization direction was
along the fiber alignment direction, indicating stronger light scattering when the electrical
field aligns with the nanofiber direction (Fig. S18B).
Water resistant coating
While the cooling wood demonstrates excellent passive radiative cooling behavior,
stable performance is required under different levels of humidity. Hydrophobicity is also
needed for exterior building applications to ensure the material does not degrade over
time. To make hydrophobic cooling wood, after chemical delignification the sample was
immersed in 2% 1H,1H,2H,2H-Perfluorooctyltriethoxysilane (98%, Sigma
Aldrich)/ethanol solution for 24 hours before pressing and drying. The fluoro-silane
groups are chemically bonded to the wood channels (28) for stable surface modification
and to restrict the effect of moisture and water. Unlike conventional coating methods, the
solution penetrates the mesoporous wood structure and converts the hydrophilic -OH
groups of cellulose into hydrophobic functional groups (perflourinated hydrocarbon
chains). A water contact angle of ~150o was obtained. Notably, the treatment can easily
penetrate into the mesoporous structure, rendering the cooling wood super hydrophobic
even from the inside (Fig. S21). We evaluated the performance of the cooling wood after
the hydrophobic treatment and the spectral response shows negligible changes in the
visible range and almost no change in the infrared, indicating a negligible change in
radiative cooling performance (Fig. S21C).
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Additional modeling of energy consumption patterns
This study demonstrates the potential cooling, fan, heating, and total energy savings
from the installation of cooling wood on mid-rise apartment building exterior surfaces,
including (1) the exterior wall siding and (2) the exterior roof membrane. The
demonstration uses midrise apartment buildings from the DOE Reference Buildings
database to establish an energy use baseline (33). The modified cases use cooling wood
material in place of the siding and roofing material, with the material properties obtained
in laboratory experiments as specified in Table S1.
Building energy models account for a total heat balance on both internal and
external building enclosure surfaces, heat transfer through the building enclosure, and
heat sources/sinks, such as internal loads generated by equipment, occupants, and
lighting. This modeling is governed by heat transfer equations for both the outside and
inside surfaces of the building, as shown in Table S2, which are solved simultaneously.
In order to determine an annual rate of energy consumption, we solved the governing
equations iteratively with an hourly time step over the duration of a year. The internal
boundary conditions used an indoor air temperature set point of 24 oC, and the external
boundary conditions used hourly weather data for a Typical Meteorological Year (32).
These models use ray tracing for all components of radiative heat transfer, including
direct and indirect fluxes, and fluxes reflected from both the ground and surrounding
building surfaces. Furthermore, the energy modeling through the building enclosure uses
different wall assemblies and their material properties to calculate transient one-
dimensional heat fluxes for the entire building enclosure (i.e., walls and roof).
Due to the high reflectivity of this new material, the installation of cooling wood is
proposed for buildings that receive higher external thermal loads (e.g., weather-related
loads) rather than internal thermal loads (e.g., internal lights or receptacles). These
buildings are commonly known as external-load dominated buildings. For example, about
42% and 14% of the buildings on school campuses are external-load dominated during
the heating and cooling seasons, respectively (34). Among the common building types,
residential buildings and warehouses also fall into the category of external-load
dominated buildings. However, typically warehouses are not fully conditioned during the
heating and cooling seasons, indicating that cooling or heating energy consumption are
not significant. Therefore, this study considers only residential buildings, and specifically
medium-sized midrise apartments located in 16 geographic locations (Fig. S25).
Fig. S26 provides a detailed analysis of baseline and modified energy consumption
patterns. Besides cooling energy savings, we also carried out the analysis in terms of
energy used to power fans and the additional energy cost for heating. Fig. S26 C-D
illustrates that the fan energy does not contribute significantly to the total energy
consumption. Consequently, any potential savings will not have a significant influence on
the total energy consumption. Fig. S26 E-F provides the heating energy consumption
patterns and highlights the significance of any potential savings. The heating
consumption increased for all cities with the installation of the cooling wood during the
winter months. Fig. S26 G-H summarizes the total energy consumption. Among the
reviewed cities, Honolulu with 8.4% (135.1 GJ), Phoenix with 5.6% (108.0 GJ), Austin
with 4.6% (83.9 GJ), Atlanta with 1.9% (41.0 GJ), and Las Vegas with 1.8 % (36.5 GJ)
featured net total energy savings. Therefore, the installation of this cooling wood for old
midrise apartment buildings is suitable for cities with warm/hot climates. New midrise
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apartment energy consumption patterns for the selected sixteen cities follow a similar
pattern as the old midrise apartment buildings (Fig. S26 E–H). In general, it is expected
that new buildings will have relatively lower energy savings using the cooling wood
since the new building codes require installation of better insulation materials than the
old building code requirements (33). The results of Fig. S26 show that Phoenix with
20.2% of cooling energy savings (70.2 GJ) is the most suitable city for the installation of
this new material to reduce the energy consumption of cooling. While the energy
consumption for building heating increases with the installation of the new material, the
energy consumption remains unchanged for Honolulu. Consequently, the offset with the
increase in heating energy consumption typically limits the savings up to 6%. Honolulu
with 5.8% (75.4 GJ), Phoenix with 4.1% (55.9 GJ), and Austin are among the cities that
illustrate promising total energy savings in addition to the cooling and fan energy
savings. Therefore, the best buildings for the installation of this new material are old
midrise apartments located in Austin, Honolulu, or Phoenix. These cities are located in
warm climates where cooling energy consumption accounts for a larger percentage of the
total energy consumption. Consequently, the heating energy consumption does not offset
the potential cooling energy savings. Overall, the main criteria for the installation of this
material in terms of the energy savings are (i) climates with long and warm summers, (ii)
climates with short and warm winters, (iii) external-load dominated buildings, and (iv)
structures with poor insulation, such as older buildings.
The cooling energy savings shown in Fig. S27 represent the difference in cooling
energy when comparing the baseline model results for pre-1980 and post-2004 buildings
for the sixteen studied cities and four different urban densities. The modeling results
demonstrate that the shading effect of neighboring buildings mitigates the effect of the
emitted radiation. As the urban area density increases, resulting in reduced distances
between the building covered with cooling wood and neighboring buildings, the cooling
energy savings increase due to the lower exposure to solar radiation, including the
reflected solar radiation from the surrounding buildings. On the one hand, the effect of
neighboring structures on the building cooling energy consumption shows no major
impact in cities with cold climates. On the other hand, buildings in hot and dry climates
could potentially benefit from cooling wood due to the potential cooling energy savings
with a greater benefit to buildings located in dense urban areas.
Our modeled building had a rectangular shape with 4 floors. The surface area of the
roof was 783 m2, and the total external wall surface area was 1542 m
2. The windows
covered 14% of the total wall surface area. The thermal radiative cooling wood has 0.83
thermal absorbance and 0.07 solar absorbance, while standard wood used in roofing and
siding assembly has 0.90 thermal absorbance and 0.78 solar absorbance. Therefore, the
difference in thermal radiation properties between standard wood and cooling wood
drives the cooling energy savings found in Fig. S27 and Fig. S28. Specifically, Fig. S28
shows the total cooling energy savings for buildings using cooling wood as the external
layer of the roof assembly only, while Fig. S27 shows the total cooling energy savings for
buildings using cooling wood to cover both siding and roof surfaces. A comparison
between cooling energy savings shown in Fig. S27 and Fig. S28 indicates on average
25% and 12% less cooling energy savings for pre-1980 and post-2004 midrise apartment
buildings, respectively, because they use cooling wood on roof surfaces only. This
10
reduction in cooling energy savings is due to the reduction in building surface coverage
with cooling wood, indicating the effective cooling of this material.
The present study used urban density ( ) to analyze the energy consumption of a
building model in isolation )=0(λ as well as in different urban neighborhoods
( =0.022, 0.05 0.22)λ , with different potential arrangements of neighboring structures.
We explored the effect of neighboring structures on the energy performance in pre-1980
and post-2004 midrise apartment buildings that have cooling wood as material covering
their external surfaces. Fig. S29 shows the spacing in a horizontal cross section between
the building covered with cooling wood in the middle and four surrounding buildings for
urban plan area densities of 0, 0.022, 0.05, and 0.22. Each urban area density is
associated with a specific distance between the surface of the building covered with
cooling wood and the surface of neighboring buildings, except ( )=0λ which represents
an isolated building without any neighboring structures. Furthermore, the urban densities
of 0.022, 0.05, and 0.22 represent urban morphologies with distances between buildings
equal to 3, 9.15, and 15.26 meters, respectively. These distances are the suggested
distances reported in the Lot and Building standards. Therefore, these four different urban
area densities represent realistic urban conditions to study the effect of radiation reflected
from neighboring buildings as well as the shading effect they provide to the building
covered with cooling wood.
Fig. S30 shows the average cooling energy savings for the sixteen studied cities. Our
cooling wood shows potential cooling savings for pre-1980 buildings that range from 16
MJ/m2-year for an isolated building ( )=0λ to 23 MJ/m
2-year for the densest urban
neighborhoods ( )=0.22λ . Similarly, for post-2004 buildings, the cooling energy savings
range from 9 MJ/m2-year for an isolated building ( )=0λ to 14 MJ/m
2-year for the densest
urban neighborhoods ( )=0.22λ . The surrounding buildings decrease the cooling energy
demand of the building covered with cooling wood due to the shading that the
surrounding structures provide. Therefore, the potential cooling energy savings by using
cooling wood changes on average from 35% for an isolated building to 51% for the
highest urban density in pre-1980 buildings. Similarly, for post-2004 buildings, the
average cooling energy savings for a building covered with cooling wood changes from
21% for an isolated building to 39% for the highest urban density, as shown in Fig. S30B.
Lastly, the potential cooling savings associated with cooling wood could be reversed
during the winter months by the increase in heating energy. Additionally, the shading
effect of neighboring buildings will increase the heating energy consumption in the
building of interest. An overall annual energy analysis of the building model using
cooling wood for both roofing and siding shows that the cooling energy savings are
almost mitigated by the heating energy increase. The offset of the increased heating
energy costs and a more detailed analysis of the overall energy savings can be found in
Fig. S26.
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Fig. S1
A. Schematic drawing of the thermal characterization setup. The cooling wood is placed
in a thermal isolation box. The top surface of the wood is facing toward the sky with a
10-m-thick HDPE film sandwiched between the wood and outside ambient. The air gap
between the wood and HDPE is about 10 mm. B. Convective and conductive heat loss of
the thermal characterization box. The heating power is fed by the Kapton heater to
maintain a fixed temperature difference between the wood and the ambient. Here all
radiative heat transfer was blocked and the experiments were performed indoors.
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Fig. S2
The day-time radiative cooling power of the cooling wood versus sub-ambient cooling
temperature for non-radiative heat exchange coefficients of 1.0, 5.0, 10.0, and 15.0
W/(m2 K). The calculations are based on the actual spectral data of the cooling wood.
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Fig. S3
A. A 200 mm 100 mm sized piece of cooling wood. B. Two thermal boxes were used
to conduct the direct thermal measurement. One box had the Kapton heater turned ON
and a feedback control program was used to maintain the wood temperature the same as
the ambient temperature. The other box had the Kapton heater turned OFF and the steady
state below-ambient temperature of the wood was tracked over time.
14
Fig. S4
The solar irradiance (top panel) and wind speed (bottom panel) over the 24-h
experimental period.
15
Fig. S5
Comparison of the ambient temperature measured by our thermal measurement system
and weather station. A. 24-hour record of the ambient temperature. B. Distribution of the
temperature difference between the two measured temperatures over 24 hours.
16
Fig. S6
Temperature difference of the cooling wood and ambient in the radiative cooling power
measurement. A. The temperature of the ambient and cooling wood that is heated by a
feedback-controlled heating system over 24 hours. B. The temperature difference
between the cooling wood and ambient. C. A histogram of the temperature difference
shows a narrow distribution of 0.1 oC for the 24-hour period.
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Fig. S7
24-hour continuous measurement of the radiative cooling power of the cooling wood. A.
Real-time radiative cooling power with sampling rate of 0.2 Hz (black) and their average
value over 1 minute (red). B. The histogram of the difference between the real-time and
averaged cooling power. The width of the histogram is 10 W/m2, indicating the accuracy
of our thermal measurement system.
18
Fig. S8
Real time measurement of the sub-ambient cooling performance of the cooling wood in
comparison with that of natural wood. The cooling wood is 12 oC cooler than the natural
wood.
19
Fig. S9
SEM image of the cooling wood. The arrow indicates the tree growth direction.
20
Fig. S10
SEM image of the cooling wood when viewed from the top.
21
Fig. S11
SEM image of the partially aligned cellulose nanofibers of the delignified wood along the
tree growth direction.
22
Fig. S12
The composition of cellulose and lignin in the natural and cooling wood samples.
23
Fig. S13
A. Absorption coefficient of the lignin film deposited on a transparent film. B.
Absorption coefficient of the cellulose film.
24
Fig. S14
Absorption coefficient (right) vs. wavelength for lignin and cellulose. Absorptivity (left)
vs. wavelength for cooling wood and natural wood, respectively.
25
Fig. S15
Reflectivity of the cooling wood (black curve) and a transparent cellulose film (red
curve).
26
Fig. S16
The mesoporous structure of cooling wood, featuring hierarchical cellulose fibers.
27
Fig. S17
The reflection haze of the cooling wood over visible wavelengths.
28
Fig. S18
The polarization-dependent reflection spectra of the cooling wood. A. 0o and 90
o
polarized incident light with respect to the aligned nanofiber bundles of the cooling wood,
and B. the corresponding reflectance spectra.
29
Fig. S19
FTIR absorbance of the cooling wood due to molecular vibration and stretching.
30
Fig. S20
Thermal conductivities of natural wood and cooling wood in the transverse direction
(between the top and bottom surfaces during temperature measurement).
31
Fig. S21
The emissivity of the cooling wood before and after the hydrophobic treatment.
32
Fig. S22
Strength and toughness comparison between natural wood and cooling wood.
33
Fig. S23
Schematic illustration of the scratch hardness test (test conditions: load: 1 kg; sliding
speed: 0.2 mm/s; scratch length: 7 mm; 3 scratches for each direction; ASTM Standard
Followed–G171-03).
34
Fig. S24
Comparison of mechanical properties of natural wood and cooling wood. (A) Schematic
of the bending test. (B) Corresponding flexural stress as a function of roller displacement
(bending deflection). (C) Flexural strength of natural wood and cooling wood. (D)
Schematic of the compression test. (E) Compressive stress-strain curves for natural wood
and cooling wood. (F) Comparison of compressive strength of natural wood and cooling
wood. Insets illustrate the representative cross-sectional features of the two types of
wood. (G) Schematic of the Charpy impact test. (H) Charpy impact toughness of natural
wood and cooling wood.
35
Fig. S25
Modeling of energy savings by installing cooling wood panels on roofing and external
siding of midrise apartment buildings. A. Photo image of a cooling wood board. B.
Schematic of a midrise building. C. The 16 U.S. cities assessed for cooling energy
savings during summer for midrise buildings.
36
Fig. S26
Baseline and modified energy consumption patterns of old midrise apartments: (A)
cooling, (C) fan, (E) heating, and (G) total. Baseline and modified energy consumption
patterns of new midrise apartments: (B) cooling, (D) fan, (F) heating, and (H) total.
37
Fig. S27
Total cooling energy savings using cooling wood for roofing and siding for buildings
made (a) pre-1980 and (b) post-2004 as a function of different urban area densities and
locations across the United States.
38
Fig. S28
Total cooling energy savings using cooling wood as roofing alone for buildings made (A)
pre-1980 and (B) post-2004 as a function of different urban area densities and locations
across the United States.
39
Fig. S29
Studied urban area density configurations for λ = 0 (isolated building), λ = 0.22 (3
meters), λ = 0.05 (9.15 meters), and λ = 0.022 (15.26 meters).
40
Fig. S30
A. Average cooling energy savings and B. average percent cooling energy savings as a
function of different urban area densities for buildings made pre-1980 and post-2004
using cooling wood as roofing and siding material.
41
Table S1.
Thermo-fluid properties of the cooling wood used in the energy modeling Property Value
Thickness [mm] 3
Specific Heat Capacity [kJ/kgK] 1800
Thermal Absorptance [-] 0.83
Solar Absorptance [-] 0.08
Visible Absorptance [-] 0.05
42
Table S2.
Outside and Inside Energy Balance Equations Outside Surface Heat Balance Inside Surface Heat Balance
sol LWR conv koq" q" q" q" α
where:
solq" α Absorbed direct and
diffuse solar (short wavelength)
radiation heat flux.
LWRq" Net long wavelength
(thermal) radiation flux exchange
with the air and surroundings
(including sky).
convq" Convective flux exchange
with outside air.
koq" Conduction heat flux (q/A)
into the wall.
LWX SW LWS ki sol convq" q" q" q" q" q"
where:
LWXq" Net longwave radiant exchange flux
between zone surfaces.
SWq" Net short-wave radiation flux to surface
from lights.
LWSq" Longwave radiation flux from equipment
in zone.
kiq" Conduction flux through the wall.
solq" Transmitted solar radiation flux absorbed
at surface.
convq" Convective heat flux to zone air.*
*Note: the convq" term uses a system of equations for transient convective heat transfer to the air volume
in each building zone defined by bulk air properties and heat sources from internal loads, wall surfaces, and
the air conditioning system.
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