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: binghu@umd.edu (L.H.); xiaobo.yin@colorado.edu (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

2

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

3

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;

4

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

5

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.

6

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.

7

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).

8

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

9

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.

11

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.

12

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.

13

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.

17

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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