The American Journal of Engineering and Technology
200
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TYPE
Original Research
PAGE NO.
200-221
10.37547/tajet/Volume07Issue06-22
OPEN ACCESS
SUBMITED
19 April 2025
ACCEPTED
22 May 2025
PUBLISHED
28 June 2025
VOLUME
Vol.07 Issue 06 2025
CITATION
Vinod Kumar Enugala. (2025). Real-Time Monitoring of Self-Healing
Biocement Using Embedded Bioluminescent Microbes. The American
Journal of Engineering and Technology, 7(06), 200
–
221.
https://doi.org/10.37547/tajet/Volume07Issue06-22
COPYRIGHT
© 2025 Original content from this work may be used under the terms
of the creative commons attributes 4.0 License.
Real-Time Monitoring of
Self-Healing Biocement
Using Embedded
Bioluminescent Microbes
Vinod Kumar Enugala
Department of Civil Engineering, University of New Haven, CT, USA
Abstract:
Our study introduces a real-time, non-
destructive strategy for monitoring self-healing in
biocement by integrating genetically engineered
bioluminescent microorganisms. Microcracking in
concrete
infrastructure
imposes
annual repair
expenditures exceeding US$18 billion in the United
States, underscoring the need for effective in-situ
diagnostics. Although microbially induced calcium
carbonate precipitation (MICP) offers an attractive self-
healing mechanism, existing evaluation techniques are
invasive, intermittent, and incapable of capturing
healing kinetics. We engineered three bacterial strains
—
Sporosarcina
pasteurii,
Bacillus
subtilis,
and
Pseudomonas aeruginosa
—
to constitutively express
luciferase, enabling emission of quantifiable light signals
proportional to metabolic activity during mineralisation.
Laboratory experiments across diverse environmental
conditions and encapsulation schemes revealed a robust
correlation (R² = 0.92) between bioluminescence
intensity and calcium carbonate precipitation rate, with
microcracks as small as 10 µm reliably detected. Field-
scale validation under simulated climatic cycles
confirmed sustained signal integrity over 24 monitoring
events during twelve months, while achieving crack-
closure efficiencies between 75 % and 89 %. The
proposed biosensing platform furnishes unprecedented
insight into temporal healing dynamics, facilitating
optimisation of microbial formulations, predictive
maintenance scheduling, and deeper elucidation of
microbe
–
mineral interactions in cementitious matrices.
Its implementation could significantly extend service life
and reduce lifecycle costs of critical infrastructure
assets. Beyond concrete, the technology can be adapted
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to other structural materials where real-time,
autonomous health monitoring is imperative.
Keywords:
Biocement,
self-healing
concrete,
bioluminescent
microbes,
real-time
monitoring,
microbially induced calcium carbonate precipitation,
luciferase, non- destructive testing, sustainable
infrastructure
I.
Introduction:
The aging and decay of infrastructure
is regarded to be one of the biggest problems for
civil engineering in the twenty-first century.
Concrete as the most common material for
construction in the world, is a very brittle material
which is prone to cracking, causing durability issues,
early failure concerns, as well as potential safety
issues. According to the American Society of Civil
Engineers 42% of bridges in the United States are at
least 50 years old, with 7.5% rated structurally
deficient, demonstrating the importance of novel
strategies for infrastructure remaining and repair
(McCallister C E. ,2025). Conventional repairing of
concrete is a laborious, expensive process and is
mostly temporary, which has led to self- healing of the
concrete to be explored.
Recent biocement techniques have been developed as
promising technology for the mitigation of concrete
decay via microbially induced calcium carbonate
precipitation (MICP). Preventing cracking and getting cracks
filled
again”
by E. Fick et al., one possibility to fill cracks in
concrete is to combine specific bacteria with the concrete
material: as soon as conditions favor the bacterial
metabolism, the naturally occurring mineralization process
is activated and so are any gaps. Such bacteria belonging
to the genera Bacillus, Sporosarcina, or Pseudomonas
are known to develop urease enzymes, which facilitate
reactions enhancing the formation of calcium carbonate and
thereby sealing off cracks and preventing additional
penetration of harmful substances (Zhang et al., 2023).
Notwithstanding significant advances in biocement, a crucial
limitation remains: the lack of real-time self-repair
observation. Current methods of assessment are
predominantly based on visual examination, water
permeability test or destructive sampling, which lack real
time continuous information on healing. Such a gap seriously
hampers optimization and performance verification and the
fundamental knowledge of the biological healing reactions
inside the concrete matrices.
The task of non-destructive monitoring in opaque,
mineralized environments has long limited our capacity
to trace biological processes in construction materials.
Although conventional sensors may be able to measure
temperature, moisture, pH, and the like, they are not able to
directly measure microbial response or healing progress.
Imaging modalities such as X-ray computed tomography
also offer high spatial resolution but are infeasible for field
monitoring due to the imaging instruments and radiation
hazards (Wang et al., 2024).
Bioluminescence, when natural living organisms emit light
through molecular processes in the div, could be the
answer to this surveillance dilemma. Luciferase enzyme-
expressing self-healing bacteria as a biocementation
sensor Prototyping This concept further, if self- healing
bacteria, engineered to carry out calcium carbonate
precipitation, can be modified to express luciferase
enzymes, the potential could exist for biocement systems
in which healing produces non-destructively measurable
detectable light signals that could be transmitted
through optical fibers or specialised sensors in the
concrete.
This study meets the high demand for real-time,
noninvasive monitoring of self-healing in biocement by
establishing and verifying a platform based on
engineered bioluminescent microorganisms. Synthetic
biology with civil engineering materials science is an
emergent interdisciplinary paradigm that has the potential
to revolutionize how we monitor, sense, and optimize self-
healing infrastructure materials.
The purposes of this study are to:
•
Develop bacterially self-healing strains with robust,
metabolically linked bioluminescent capability for
sustained long-term performance in a concrete setting.
•
Create a packaging system that shield bacteria
infrastructure and permit metabolic activation and light
penetration when the substrate is breached.
•
Develop and deploy an optical-embedded sensing
network to sense and quantify bioluminescent signals
inside a concrete structure.
•
Verify the relationship between bioluminescence
signals and CaCO3 precipitation rates by laboratory
and field testing.
•
Assess the long-term stability, sensitivity, and reliability
of the monitoring system for a range of environmental
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conditions.
The approach has profound relevance to infrastructure
monitoring in terms of possible prediction of
maintenance, verification of performances and possibly
also to the scientific knowledge around self-healing in
construction materials. By enabling in-situ monitoring of
healing, this technology can make the applications of
biocement significantly more reliable and cost-effective,
whilst also contributing to the area of smart, responsive
infrastructure materials.
II.
Literature Review
2.1
Self-Healing Mechanisms in Concrete
Research in relation to self-healing concrete technologies
has developed a lot over the last decade, encouraged by
the pursuit of enhancing the sustainability and resilience
of infrastructure. These technologies can be generally
organized in there groups: autogenous, autonomic -based
on polymer-embedded-healing-agents, and MICP
(Microbially Induced Calcium Carbonate Precipitation),
i.e., biologically-induced healing.
The method of healing of autogenous healing is based
on the self-sealing behavior of concrete by the
continued hydration of unhydrated cement particles
and carbonation. Although this process is natural, it is
confined to very narrow openings (usually < 0.1 mm) and
is a water-dependent process (Harle C S.M , 2025).
Research by de Belie et al. (2023) showed that the
efficiency of autogenous healing decreases substantially
with concrete age, as the unhydrated cement proportion
decreases, which makes it impractical for long- term
infrastructure use.
Microencapsulated or vascular networks of the polymer
healing agents are commonly used in self-healing systems.
Dong et al. (2024) summarized the recent progress in this
subject
and pointed out that despite the fact that these systems
are able to seal larger cracks compared to autogenous
healing, they suffer from long-term stability problems,
limited supply of the healing agent and possible
incompatibility between the healing agents and the
concrete div. Moreover, these networks generally
provide for no more than one healing cycle, since the
healing components are consumed upon triggering.
Bioremediation through MICP is one of the most
encouraging nontoxic methods of bioremediation, with
the ability for repeated healing cycles, fit within the
concrete, and being environmentally friendly. This
commonly consists of including bacteria in the concrete
matrix that can lead to the precipitation of calcium
carbonate. When cracks are developed and water entry
into the cracks occurs, these bacteria become activated
metabolically and author a biochemical steps that end with
calcium carbonate precipitation and canalize effectively the
crack (Seifan C Berenjian, 2023).
Research by Zhang et al. (2023) achieved healing
efficiencies of 60
–
80% for 0.5 mm-wide cracks upon
employing Sporosarcina pasteurii in the matrix, with
Khaliq and Ehsan (2022) obtaining similar results using
Bacillus subtilis. More recently, Silva et al. (2024), who
demonstrated that bacterial blends are effective in
propelling recovery under different environmental
conditions, suggesting that biological approaches can be
significantly more versatile.
Despite these successes, a considerable bottleneck to all
SHC research is the lack of real- time monitoring, which
has impeded the scientific concepts and practical use of
these technologies.
2.2
MICP
(Microbiologically
Induced
Calcium
Carbonate Precipitation)
MICP is a biochemical phenomenon in which bacteria
metabolism is responsible for the precipitation of
calcium carbonate. In the biocement application, this
action is usually mediated by ureolytic bacteria which
hydrolyze urea, leading to carbonate ions generation and
increase the local pH supporting the precipitation of calcium
carbonate in the presence of the calcium ion (Seifan C
Berenjian, 2023).
The most commonly investigated mechanism is via the
urease enzyme pathway, in which urease-producing
bacteria such as Sporosarcina pasteurii hydrolyze urea
(CO(NH₂)₂)
into
ammonia (NH₃) and carbonic acid
(H₂CO₃). The ammonia then raises the pH of the
microenvironment, carbonic acid dissociates to
bicarbonate
(HCO₃⁻)
and later carbonate
ions (CO₃²⁻).
Under reactive conditions (Ca²⁺), these carbonate ions
precipitate as relatively insoluble calcium carbonate
(CaCO₃)
(Wei et al., 2023).
Other MICP pathways involve denitrification, as bacteria
reduce nitrate and carbonate precipitates form, and
metabolic conversion of organic calcium salts such as
calcium lactate or calcium acetate. Wang et al. (2022)
showed these alternative pathways can be preferable in
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some applications, such as in urea-limited environments
or where ammonia production is unfavourable.
The performances of MICP in curing of concrete are
influenced by many factors such as bacterial types,
sources
of
calcium,
availability
of
nutrients,
environmental conditions. Studies of the deliquescent
behaviour of powders, by Rodriguez-Navarro and others
(2023) demonstrated that the crystal habit and adhesion
strength of precipitated calcium carbonate exert a major
influence on healing behavior, and that, under certain
conditions, vaterite and aragonite polymorphs adhere
better to crack surfaces than calcite.
Although there has been much research on the MICP
mechanism, it is difficult to directly observe and quantify
MICP inside of concrete by virtue of the opaque aspect of the
concrete and the order of magnitude with which the
biological processes occur. Existing techniques for
assessing MICP activity are mostly based on indirect
measurements or after-the-fact analysis, and therefore
real-time monitoring tools are desired.
2.3
State of Art in the Concrete Self-Healing Concurrent
Monitoring
The methodologies used to measure the self-healing
efficiency in concrete can be classified into visual
examination, permeability testing, mechanical recovery
testing, and different imaging methods. Both techniques
have their limitations which make them unsuitable for
long-term on-line monitoring of the healing of the
wounds.
Optical microscopy and scanning electron microscopy
(SEM) are utilized for visual inspection of the healing
process, offering a complete visual exam of crack closure
while this requires immediate access to the crack's
surface at the time of inspection and does not give
information about healing kinetics at different time points
unless new samples are prepared. Sánchez et al. (2023)
resorted
to
environmental
SEM
to
capture
biomineralization activities at concrete surfaces, though
the approach did not penetrate beyond a surface feature
nor did it offer time-resolved information on the healing
process.
Permeability tests characterize the resistance of the
concrete to fluid flow as an index of crack healing, such as
water permeability, capillary water absorption, and gas
permeability. Such methods give function information about
the healing efficiency, but are not suited for continuous
process monitoring without disturbing the healing process
at all. Li et al. (2023) found out that water permeability
reduction correlate very well with the healing cell
evolution, however, the test itself changes the local
environment of the crack to which it is applied, and
therefore it is known to interfere with the development of
the healing process under study.
Mechanical recovery test tests the recovery of structure
properties by including strength regain, stiffness recovery
or fracture toughness measurement. Although these
methods provide useful information on functionality, they
are invasive and not feasible for real-time measurements.
In addition, as reported by Zhang et al. (2024), the
mechanical behaviour might not simply relate to crack filling
as mechanical properties are determined by both the
amount and quality of the healing products.
Advanced imaging methods like the x-ray computed
tomography (CT), neutron radiography, and ultrasonic
testing provide a non-destructive look inside the crack for
healing. Wang et al. (2024) imaged CaCO3 precipitation
within loose and concrete samples by time-lapse X- ray CT
with resolutions allowing for investigation of bacterial
activity. But in general these techniques require special
equipment and cannot see continuous data and can not be
used for field monitoring.
Common to all these approaches is the site specific
monitoring of the biological activity underlying the
healing process, in real time. This gap has restricted
optimization of mitigation strategies and prevented a
fundamental understanding of the influence of
environmental factors on healing kinetics in situ, bringing
to focus the requirement for a novel approach that is
capable of immediate quantitation of bacterial metabolism
directly within a concrete matrix.
2.4
Bioluminescence and Its Bioanalytical Applications
Bioluminescence is the emission of light by living
organisms as the result of the metabolic breakdown of
organic
compounds,
wherein
energy-contained
intermediates produced from the reaction (luciferin,
luciferase, oxygen, and ATP) ultimately break down into
products of lower energy.) This natural system is
widespread in model organisms such as some bacteria,
fungi, insects or marine organisms and has arisen for
different functional roles (either communication,
predation or defense) (Kotlobay et al., 2023).
In scientific researches, bioluminescence has evolved to
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be an effective and attractive approach to investigate
biological activities or process in live organism, for its
sensitivity, real-time imaging ability and non-invasion.
The luciferase-luciferin system of the North American
firefly (Photinus pyralis) is one of the best-characterized
reporter systems and has been widely employed in a
variety of biological systems. On the other hand,
bacterial luciferase systems, particularly those of Vibrio
fischeri or Photorhabdus luminescens, are more
favourable choices for long-term monitoring applications
due to remaining decoupled from an additional excitation
source, as V. fischeri or P. luminescens are capable of
producing the enzyme and substrate endogenously
(Kotlobay et al., 2023).
In the field of environmental in environmental
assessment, bioluminescent bacteria have been
implemented as biosensors in order to monitor pollution in
the environment9, with the amount of light produced being
proportional to metabolic activity which is compromised in
the presence of toxic compounds. Gutiérrez et al. (2022)
used a genetically engineered Pseudomonas putida
carrying the luciferase genes for the real-time
monitoring of soil contamination, showing the light
production as a response of bacteria metabolism to the
environment.
Bioluminescence has been more recently used in solid
materials. Lin et al. (2024) used bioluminescent algae in
translucent concrete for decorative and emergency
lightening purposes, and Nguyen et al. (2023) employed
bioluminescent bacteria to monitor moisture penetration
in building materials. However, these applications were
more related to light generation, and not applying
bioluminescence as a biological repair process monitor.
The use of bioluminescence for self-healing detection in
concrete is a new case that shows promising applications
on the crossroads of synthetic biology and structural
engineering. The method/tools also relate to tackling
various obstacles such as engineering of construction
capable bacteria species for the genetic manipulation, to
make luciferase expression stable under harsh concrete
conditions and system of detection, and reading the light
signals from opaque constructions materials.
2.5
Incorporation of Optical Fiber in Concrete Monitoring
Optical fiber systems have significantly transformed
health monitoring systems, where distributed data can be
collected within concrete structures. These flexible and
thin glass fibers transmit light signals with minimal power
loss and are relatively robust against electromagnetic
interferences indicating them as a material of choice for
long-term sensing applications in infrastructure.
Typical uses of optical fibers in concrete monitoring are
for strain and temperature measurements. Fiber Bragg
Grating (FBG) sensors, which reflect certain light wavelength
to the extent of changes in grating period when strained,
provide an attractive option for structural health
monitoring [1]. (Tiejun Liu et al. ,2025) successfully verified
the long-term stability of the FBG sensor in the reinforced
concrete, measured the good strain data for 5 years under
continuous condition, and the variation under the actual
alkaline condition of the structure was not obvious.
Without any moving parts, BOTDA and ROFDR are
distributed fiber optic sensing approaches that provide
quasi-real-time sensing information over the full length
of the optical fiber. They have been successfully used in
massive infrastructure projects for high resolution strain
and temperature profile monitoring. (Wong et al. ,2023)
used BOTDA for monitoring strain distributions on a
concrete dam with spatial resolutions of 0.5 meters over
sensing lengths longer than 10 kilometers.
Apart from typical monitoring parameters such as strain
and temperature, new usage of optical fiber in the context
of concrete has arisen over the last years. (Barrias et al.
,2023) designed a chloride ion penetration monitoring
system based on a couple of chloride sensor coated fibers
and (Liu et al. ,2024) detected moisture using the refractive
index change in cladding modified fibers.
The utilization of optical fibers for the collection of light
from within the luminescent inclusions is especially
attractive. (Zhang et al. ,2024) used the optical fibers to
measure the fluorescence from dye-doped cement
under stress, resulting in a pressure-sensitive concrete
with a sensor functionality. This method shows that it is
possible to pick up light signals from within concrete
matrices, but it has not been used for the
bioluminescence monitoring for self-healing structures.
The combination of bioluminescence measurements
with optical fiber technology has advantages and
disadvantages. Although light propagating from within
concrete can be efficiently transmitted through optical
fibers, the collector efficiency will rely on fiber orientation
with respect to light sources, which for bacterial healing
agents can be randomly distributed on the crack surface.
Here, the separation of bacterial luminescence from the
background, though technically feasible, and the
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enhancement of sensitivity for feeble biological light
production, remain as challenges to be met if it the
approach is to be successfully exploited.
III.
MATERIALS AND METHODS
3.1
Bacterial Strains and Genetic Modification
3.1.1
Bacterial Strain Selection
Three bacteria that had a long history of versatile
applications of biocementation were chosen to study on
account of their wide range of environmental
resistances and mechanisms of calcification:
1.
Sporosarcina pasteurii (ATCC 11859): An extremely
ureolytic bacterium that best grows at pH 9.0, used
ob ject marker for efficient calcium carbonate
formation by urea hydrolysis pathway.
2.
Bacillus subtilis (ATCC 6051): A soil bacterium that is
widely studied in the laboratory, has low levels of
urease activity, but excellent survival in adverse
conditions via the formation of endospores.
3.
Pseudomonas aeruginosa (ATCC 27853): A non-
restricted range of bacteria with potential of calcium
carbonate precipitation through denitrification and
organic acid metabolism.
Strains were inoculated into their correspondent growth
medium: ATCC 1376 medium for
S. pasteurii; Luria-Bertani (LB) medium for B. subtilis; and
King's B medium for P. aeruginosa. Cultures were
growing/work/maintaining their overnight at the optimal
temperature for growth (30 °C for S. pasteurii and P.
aeruginosa and 37 °C for B. subtilis) before modification.
3.1.2
Luciferase Gene Selection and Vector Construction
Two distinct luciferase systems were evaluated for each
bacterial strain:
1.
The bacterial
luxCDABE
operon from
Photorhabdus
luminescens
, which encodes both the luciferase
enzyme complex (LuxA and LuxB) and the enzymes
required for synthesizing the luciferin substrate (LuxC,
LuxD, and LuxE).
2.
The firefly luciferase gene (
luc
) from
Photinus pyralis
,
which produces stronger light output but requires
external addition of the luciferin substrate.
For each system, synthetic gene constructs were designed
with codon optimization for the respective bacterial host.
The constructs included:
●
A constitutive promoter (P43 for
B. subtilis
, PlacUV5
for
S. pasteurii
and
P. aeruginosa
)
●
A strong ribosome binding site sequence
●
The luciferase gene(s) with an N-terminal His-tag for
verification
●
A rho-independent terminator sequence
For the
luxCDABE
system, the entire operon was
maintained in its natural organization to ensure proper
expression of all components. For the firefly luciferase, the
single
luc
gene was placed under direct control of the
selected promoter.
Both constructs were synthesized and cloned into
appropriate shuttle vectors: pMK4 for
B. subtilis
, pRO1600
for
P. aeruginosa
, and a custom-designed pSP01 vector for
S. pasteurii
based on the pUC backbone with
modifications for alkaliphilic bacteria.
3.1.3
Transformation and Selection
Bacterial transformations were performed using
established protocols for each species:
●
B. subtilis
was transformed using the natural
competence method with modified CM medium
●
P. aeruginosa
was transformed via electroporation
(2.5kV,
200Ω,
25μF)
●
S.
pasteurii
,
being
more
recalcitrant
to
transformation, required a specialized protocol
involving protoplast formation and polyethylene
glycol-mediated DNA uptake
Transformants were selected on appropriate antibiotic-
containing media based on the resistance markers in
each vector (chloramphenicol for pMK4, tetracycline for
pRO1600, and ampicillin for pSP01). Initial screening for
bioluminescence was conducted using a sensitive CCD
camera in a dark room setting.
For each strain-luciferase combination, three successful
transformants with stable luminescence were selected for
further characterization. The presence and integrity of the
luciferase genes were confirmed by PCR amplification and
sequencing.
3.2
Luminescence Characterization
The bioluminescence properties of each modified strain
were characterized to determine:
1.
Emission spectrum and peak wavelength using a
spectrofluorometer with emission scans from 400-
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700nm
2.
Light output intensity using a luminometer, reported in
relative light units (RLU)
3.
Correlation between light output and cell density
(OD600) during growth phases
4.
Luminescence stability over multiple generations
(minimum 50 generations)
5.
Response to varying environmental conditions (pH 6-11,
temperature 5-50°C, oxygen levels 1-21%)
For strains carrying the bacterial
luxCDABE
operon,
measurements were taken directly from cultures. For
firefly luciferase-expressing strains, measurements were
performed after addition of D-luciferin substrate
(150μg/ml
final concentration).
Based on these characterizations, the optimal strain-
luciferase combination for each bacterial species was
selected for further development, considering factors
such as luminescence intensity, stability, and correlation
with metabolic activity.
3.3
Bacterial Encapsulation and Concrete Incorporation
3.3.1
Encapsulation Method Development
Three encapsulation methods were evaluated for their
ability to protect bacteria during concrete mixing while
allowing activation when cracks occur:
1.
Hydrogel Microcapsules
: Bacteria were encapsulated
in calcium-alginate hydrogel beads using an extrusion
technique. Bacterial suspension was mixed with 2%
sodium alginate solution and extruded through a
30G needle into a bath of 2% calcium chloride with
constant stirring. The formed beads (diameter 0.8-
1.2mm) were cured in the calcium solution for 30
minutes, washed with sterile saline, and gradually
dehydrated to approximately 10% moisture content.
2.
Expanded Clay Aggregates
: Lightweight expanded clay
particles
(2-4mm
diameter)
were
vacuum-
impregnated with bacterial suspension in a nutrient
solution containing calcium lactate (3%) and yeast
extract (1%). After impregnation, the particles were
surface-dried and coated with a water-soluble polyvinyl
alcohol layer to prevent premature bacterial release.
3.
Silica Gel Encapsulation
: Bacteria were mixed with
a pre-gelled silica solution prepared by acidifying
sodium silicate to pH 7.0. The mixture was allowed to
solidify, ground to 0.5-2mm particles, and dried under
controlled conditions (30°C, 50% RH) until reaching
approximately 5% moisture content.
Each encapsulation method was evaluated for:
●
Bacterial survival during processing (viable counts
before and after encapsulation)
●
Protection efficiency during exposure to cement
mixing (bacterial survival after 30 minutes in cement
paste, pH ~12.5)
●
Release kinetics when exposed to simulated crack
conditions (immersion in water after mechanical
disruption)
●
Light
transmission
characteristics
using
a
spectrophotometer
Based on these evaluations, the most suitable
encapsulation method for each bacterial strain was
selected for concrete incorporation.
3.3.2
Concrete Mix Design and Specimen Preparation
A standard concrete mix was designed with the following
composition per cubic meter:
●
Ordinary Portland Cement (Type I/II): 380 kg
●
Water: 171 kg (W/C ratio 0.45)
●
Fine aggregate (river sand): 720 kg
●
Coarse aggregate (crushed limestone, 19mm max size):
1080 kg
●
Water-reducing admixture (polycarboxylate-based): 2.3
kg
●
Encapsulated bacteria: 5% by volume of cement
●
Nutrients (calcium lactate and yeast extract): 3% by
weight of cement
Control mixes without bacteria were prepared with the
same basic composition, with additional fine aggregate to
compensate for the volume of bacterial carriers.
Concrete was mixed following ASTM C192 procedures in a
laboratory mixer. After mixing, specimens were cast in
various forms:
●
Prisms (75 × 75 × 285 mm) for flexural testing and crack
creation
●
Cylinders (100 × 200 mm) for compressive strength
testing
●
Slabs (300 × 300 × 50 mm) for field testing with installed
monitoring systems
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All specimens were cured in a climate-controlled chamber
(23 ± 2°C, 95% RH) for 28 days before testing or crack
induction.
3.3.3
Optical Fiber Integration
A distributed optical fiber sensing network was integrated
into selected concrete specimens during casting. The
network consisted of:
1.
Light-collecting fibers: Multimode plastic optical
fibers (1mm core diameter) with modified cladding to
enhance lateral light collection. These fibers were
arranged in a grid pattern (spacing 25mm) and
embedded at mid-depth in slab specimens.
2.
Data transmission fibers: Single-mode glass optical
fibers
(9/125μm)
connected to the collection fibers
via specialized couplers and routed to the exterior of
the specimens for connection to measurement
equipment.
3.
Reference fibers: Additional fibers embedded in
non-cracked
regions
to
provide
baseline
measurements and compensation for environmental
factors.
The fiber network was carefully positioned and secured
using custom-designed supports before concrete
placement to ensure proper alignment and prevent
displacement during casting and vibration.
3.4
Crack Induction and Healing Assessment
3.4.1
Controlled Crack Formation
After the 28-day curing period, controlled cracks were
induced in test specimens using two methods:
1.
Three-point bending
: Prism specimens were subjected
to controlled loading using a servo-hydraulic testing
machine. Loading was applied at a rate of 0.05mm/min
until a crack of the desired width was achieved. The
loading was then held constant while crack width was
measured using a digital microscope with 200×
magnification. Specimens were prepared with cracks
ranging from 0.05 to 1.0mm in width.
2.
Brazilian splitting test
: Cylinder specimens were
loaded along their diameter using the Brazilian
splitting method to induce tensile cracks. Loading
was controlled to achieve specific crack widths,
measured using the same digital microscopy
approach.
After crack formation, specimens were unloaded and crack
dimensions (width, length, and where possible, depth)
were documented using high-resolution photography
and microscopic measurements at five points along each
crack. Reference markers were attached to facilitate
consistent measurements throughout the healing period.
3.4.2
Healing Conditions
Specimens with induced cracks were subjected to three
different healing regimes designed to evaluate
performance across varying environmental conditions:
1.
Standard healing conditions
: Specimens were
immersed in water for 4 hours daily and maintained at
room temperature (21 ± 2°C) with ambient humidity
(50-60% RH) between wetting cycles. This regime
simulated optimal conditions for bacterial activity.
2.
Cyclic
temperature
conditions
:
Specimens
underwent temperature cycling between 5°C and
40°C with a 24-hour cycle period, while maintaining
the same wetting schedule as the standard
conditions. This regime tested the system's
performance under temperature fluctuations.
3.
Field-simulated conditions
: Specimens were placed in
an environmental chamber programmed to simulate
natural weather patterns from three climate zones
(temperate, tropical, and arid), including realistic
temperature, humidity, and precipitation cycles
based on meteorological data.
Each healing regime was maintained for 56 days, with
periodic measurements and monitoring throughout this
period.
3.4.3
Healing Effectiveness Evaluation
Healing effectiveness was evaluated using multiple
complementary methods:
1.
Visual assessment
: Crack width measurements were
performed at the same five reference points at
regular intervals (0, 3, 7, 14, 28, and 56 days) using
digital microscopy. Healing efficiency was calculated
as the percentage reduction in average crack width.
2.
Water permeability
: Modified RILEM tube tests
were conducted at the same intervals to measure
water penetration through cracks. Permeability
reduction was
calculated relative to initial
measurements immediately after crack formation.
3.
Mechanical property recovery
: Healing specimens
were selected and mechanically tested to evaluate
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strength restoration. Prisms were evaluated for
flexural strength and cylinders for splitting tensile
strength.
“Recovery
ratios”
were calculated as the
ratio of the strength of healed specimen to that of
intact control specimens.
4.
Microstructural analysis
: After healing period, healed
fracture surfaces were cut off, and the analyses on
the composition and morphology of the healing
products were carried out by scanning electron
microscope (SEM) and X-ray diffraction (XRD).
3.5
Bioluminescence Monitoring System
3.5.1
Optical Detection System
A dedicated optical detection system was created for
the detection and evaluation of bioluminescent signals
from the depths of concrete specimens:
•
Light detector: The system was equipped with a
scientific-grade cooled CCD camera (Andor iXon
Ultra 888) in a lightproof box. For in-situ
measurements, a portable PMT-based detector with
fiber optic readout was developed, as a more
ruggedized version.
•
Signal filtering: Signal-to-noise ratios were increased by
excluding background light, using optical bandpass
filters which covered the visible light emitted by
each bacterial luciferase system.
•
Data collection: The detection system was operated
under the control of our custom software, which offers
features for systematic recording of collected data,
timing, and according to changes in signal intensity,
event-triggered recording.
The detector system was calibrated with standard
light sources being placed at different depths in non-
luminescent concrete specimens for penetration of
the light through concrete matrices of varying
thicknesses.
3.5.2
Correlation Analysis
To build the correlation between bioluminescence signals
and the healing response, dual experiments for the
determination of;
1.
Bioluminescence intensity (photons/second) and
bacterial counts (CFU/ml) in artificial cultures under
controlled laboratory conditions
2.
Bioluminescence intensity with calcium carbonate
precipitation rates measured by calcium ion depletion
in solution
3.
Bioluminescence spatial distribution with crack
closure patterns observed through microscopy
4.
Integrated bioluminescence signals over time with
total healing efficiency at experiment conclusion
These correlations were established for each bacterial
strain and encapsulation method under various
environmental conditions, creating a comprehensive
calibration framework for interpreting bioluminescence
data from concrete specimens.
3.5.3
Field Monitoring Setup
For long-term field monitoring, a self-contained system was
developed consisting of:
1.
A weatherproof housing containing the optical detection
equipment
2.
A solar-powered battery system for autonomous
operation
3.
A microcontroller-based data acquisition system
with wireless data transmission capabilities
4.
Environmental sensors (temperature, humidity,
rainfall) for contextual data collection
This system was deployed at three locations with different
climate conditions (temperate, tropical, and arid) to
evaluate the monitoring system's performance under
real-world conditions. At each location, instrumented
concrete slabs with induced cracks were installed and
monitored for a 12-month period.
3.5.4
Data Analysis and Statistical Methods
All experiments were conducted with a minimum of three
replicates to ensure statistical validity. Data analysis
methods included:
1.
Descriptive statistics
: Mean, standard deviation, and
coefficient of variation were calculated for all
measured parameters.
2.
Regression analysis
: Linear and non-linear
regression models were developed to quantify
relationships between bioluminescence signals and
healing parameters. Model quality was assessed
using R² values and residual analysis.
3.
Analysis of variance (ANOVA)
: Factorial ANOVA was
employed to evaluate the effects of bacterial strain,
encapsulation
method,
crack
width,
and
environmental conditions on healing performance
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and bioluminescence characteristics.
4.
Time series analysis
: For continuous monitoring
data, time series analysis techniques including
moving averages and exponential smoothing were
applied to identify trends and patterns in healing
dynamics.
5.
Image analysis
: Specialized image processing
algorithms
were
developed
to
analyze
bioluminescence spatial distribution and correlate
light patterns with crack geometries.
Statistical significance was established at p < 0.05 for all
analyses. All statistical calculations were performed using
R (version 4.2.0) with appropriate packages for specific
analyses.
IV.
Results and Discussion
4.1
Bacterial Strain Development and Characterization
4.1.1
Bioluminescence Expression and Stability
The genetic modification of bacterial strains with luciferase
systems resulted in successful
bioluminescence
expression, though with varying characteristics across
species and luciferase types. Table 1 summarizes the key
bioluminescence properties of the modified strains.
Table 1: Bioluminescence Properties of Modified Bacterial
Bacterial
Strain
Luciferase
System
Peak
Wavelength
(nm)
Maximum
Intensity
(RLU/10⁸ cells)
Stability
(t₁/₂, days)
S. pasteurii
luxCDABE
490
4.2 × 10⁵
42
S. pasteurii
Firefly
luc
562
8.6 × 10⁶
35
B. subtilis
luxCDABE
490
2.8 × 10⁵
87
B. subtilis
Firefly
luc
562
5.9 × 10⁶
64
P.
aeruginosa
luxCDABE
490
5.3 × 10⁵
31
P.
aeruginosa
Firefly
luc
562
9.4 × 10⁶
27
The firefly luciferase (
luc
) consistently produced higher
light intensity across all bacterial species, with emission
approximately 15-20 times greater than the bacterial
luxCDABE
system. However, the bacterial luciferase system
demonstrated superior stability over time, particularly in
B.
subtilis
where the half-life exceeded 80 days without
selective pressure. This stability difference likely results
from the integrated nature of the bacterial luciferase
system, where all components are encoded within a single
operon, compared to the firefly system's dependence on
exogenous substrate addition.
Emission spectra analysis revealed that the bacterial
luciferase system produced blue- green light with peak
emission at 490nm, while the firefly system yielded yellow-
green light peaking at 562nm. The longer wavelength of the
firefly system represents an advantage for concrete
applications, as longer wavelengths experience less
scattering and absorption when traveling through dense,
heterogeneous materials.
4.1.2
Correlation Between Bioluminescence and
Metabolic Activity
A critical requirement for the monitoring system was
establishing
a
reliable
correlation
between
bioluminescence signals and the metabolic activities
responsible for calcium carbonate precipitation. Figure 1
illustrates the relationship between bioluminescence
intensity and ureolytic activity (measured as urease enzyme
activity) for
S. pasteurii
with the firefly luciferase system
under various environmental conditions
.
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Figure 1: Correlation between bioluminescence intensity and urease activity for
S. pasteurii
expressing firefly
luciferase under varying pH and temperature conditions
The results demonstrated a strong linear correlation (R² =
0.92) between bioluminescence intensity and urease
activity across standard conditions (pH 7-9, 25-30°C).
However, this correlation weakened at extreme pH values (<
6 or > 10) and temperatures (< 10°C or > 40°C). Notably, the
relationship remained predictable when environmental
conditions were known, allowing for compensation factors
to be applied to bioluminescence measurements in varying
environments.
Similar analyses for all strain-luciferase combinations
revealed that
B. subtilis
with the firefly luciferase system
maintained the most consistent correlation between light
output and metabolic activity across the widest range of
environmental conditions. This strain was therefore selected
as the primary candidate for further development, with
S.
pasteurii
(firefly luciferase) as a secondary option for
applications requiring higher alkalinity tolerance.
4.1.3
Environmental Tolerance
The environmental tolerance of the modified bacterial
strains was assessed to determine their suitability for
diverse concrete applications. Figure 2 shows the
relative bioluminescence intensity of the selected
strains across temperature ranges typical of
construction environments.
Figure 2: Relative bioluminescence intensity as a function of temperature for modified bacterial strains
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B. subtilis
expressing firefly luciferase maintained detectable
bioluminescence (>10% of maximum) across the widest temperature
range (4-45°C), with optimal performance between 25-37°C. By
contrast,
S. pasteurii
showed higher tolerance to alkaline conditions,
maintaining significant bioluminescence activity (>50% of maximum) at
pH values up to 11, making it particularly suitable for early-age concrete
environments.
The genetic stability of the luciferase expression was also assessed
over multiple generations. After 50 generations of growth without
selective pressure,
B. subtilis
retained 89% of its original bioluminescence
intensity, while
S. pasteurii
and
P. aeruginosa
retained 74% and 62%,
respectively. This superior genetic stability of
B. subtilis
is likely
attributable to successful chromosomal integration of the luciferase
genes, as confirmed by whole genome sequencing.
Based on these combined results,
B. subtilis
with firefly luciferase was
selected as the primary bacterial system for concrete incorporation,
with environmental response correlation factors developed to
interpret bioluminescence signals across varying conditions.
4.2
Encapsulation and Concrete Integration
4.2.1
Encapsulation Efficiency
The three encapsulation methods were evaluated for their protective
efficiency during concrete mixing and their ability to preserve bacterial
viability over time. Table 2 presents the survival rates of encapsulated
bacteria after exposure to cement paste (pH ~12.5) for 30 minutes,
simulating the harsh conditions of concrete mixing.
Table 2: Bacterial Survival Rates After Exposure to Cement Paste
Encapsulation
Method
B.
subtilis
Survival (%)
S.
pasteurii
Survival (%)
P.
aeruginosa
Survival (%)
Hydrogel
Microcapsules
68.3 ± 5.2
52.7 ± 6.8
41.5 ± 7.3
Expanded
Clay
Aggregates
83.7 ± 4.1
65.4 ± 5.3
59.2 ± 6.1
Silica
Gel
Encapsulation
92.4 ± 3.8
81.2 ± 4.9
72.6 ± 5.5
Silica gel encapsulation provided the highest protection
across all bacterial species, with survival rates exceeding
90% for
B. subtilis
. The superior protection of silica gel
can be attributed to its stable mineral structure and buffering
capacity, which shields bacteria from the highly alkaline
environment of fresh cement paste. Additionally, the silica
gel particles maintained structural integrity during
mixing, unlike the hydrogel microcapsules which showed
some deformation and rupture.
Long-term viability testing revealed that bacteria
encapsulated in silica gel maintained viable cell counts
above
10⁶
CFU/g for over 6 months when stored at room
temperature in dry conditions. This extended shelf life is
critical for practical construction applications where
materials may be stored for significant periods before use.
4.2.3
Light Transmission Characteristics
The optical properties of the encapsulation materials were
evaluated to ensure effective
transmission of
bioluminescence signals. Figure 3 shows the light
transmission spectra for each encapsulation material at
thicknesses representative of typical crack widths (0.1-
1.0mm).
Figure 3: Light transmission spectra for encapsulation materials at 0.5mm thickness
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Hydrogel microcapsules demonstrated the highest light
transmission (>85% across the visible spectrum when
fully hydrated), followed by silica gel (65-75%
transmission, with better transmission at longer
wavelengths). Expanded clay aggregates showed the
lowest transmission (<50%), with significant scattering
effects due to their heterogeneous structure.
These findings indicated that while silica gel provided
optimal bacterial protection, its light transmission
characteristics were not ideal. However, the superior
protection efficiency was prioritized over transmission
properties, as signal detection methods could be adjusted to
compensate for lower light transmission.
4.2.4
Concrete Performance with Bacterial Additions
The inclusion of encapsulated bacteria in concrete
mixtures could potentially affect the material's
fundamental properties. Comprehensive testing was
conducted to assess the impact of bacterial additions on
concrete mechanical and durability characteristics. Table
3 summarizes key performance parameters for concrete
with different bacterial encapsulation systems
compared to control specimen
Table 3: Effect of Bacterial Additions on Concrete Properties
Property
Control
Concrete
With
Hydrogel
Microcapsules
With Expanded
Clay
With Silica
Gel
Compressive
Strength (28d, MPa)
42.7 ± 1.8
38.3 ± 2.1
36.5 ± 2.4
41.2
±
1.9
Flexural
Strength
(28d, MPa)
4.8 ± 0.3
4.3 ± 0.4
4.1 ± 0.4
4.7 ± 0.3
Elastic Modulus (GPa)
32.5 ± 1.1
29.8 ± 1.3
27.6 ± 1.5
31.8
±
1.2
Setting Time (h)
5.5 ± 0.2
6.2 ± 0.3
5.8 ± 0.3
5.7 ± 0.2
Slump (mm)
85 ± 5
95 ± 6
90 ± 7
80 ± 6
The results indicated that silica gel encapsulation had
the least impact on concrete mechanical properties, with
strength values within 5% of control specimens. In
contrast, hydrogel microcapsules and expanded clay
caused more significant reductions in strength (10-15%),
likely due to their higher water absorption and lower
mechanical strength compared to conventional
aggregates.
Microstructural analysis using SEM revealed good
integration of silica gel particles within the cement matrix,
with minimal interfacial voids or weak zones. This effective
integration contributed to the maintenance of
mechanical properties despite the inclusion of the
bacterial carriers.
Based on these combined results of protection efficiency,
light transmission, and concrete property effects, silica gel
encapsulation was selected as the optimal method for
incorporating bioluminescent bacteria into concrete for
self-healing applications.
4.4
Crack Healing Performance and Monitoring
4.4.1 Healing Efficiency Across Crack Widths
The effectiveness of the self-healing system was
evaluated across various crack widths under standard
healing conditions. Figure 4 illustrates the healing
progression over time for cracks of different initial widths.
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Figure 4: Healing progression (percentage of crack width reduction) over time for varying initial crack widths
For narrow cracks (0.1-0.3mm), substantial healing was
observed within the first 14 days, with complete closure
(>95% width reduction) achieved by day 28 in most
specimens. Medium cracks (0.3-0.6mm) showed slower
progression, reaching 75-85% closure by day
56. Larger cracks (0.6-1.0mm) exhibited the slowest healing
rates, achieving 60-70% closure by the end of the 56-day
observation period.
Microscopic examination of healed cracks revealed that the
precipitated calcium carbonate formed primarily as calcite
crystals with excellent bonding to crack surfaces. This
strong adhesion was reflected in the mechanical property
recovery, with specimens containing fully healed narrow
cracks regaining up to 93% of their original flexural
strength.
Water permeability tests corroborated these findings, with
permeability reduction closely tracking visual crack
closure. Notably, permeability decreased more rapidly
than visual crack width in the early stages of healing,
suggesting that bacterial precipitation initially bridges
critical flow paths within cracks before achieving complete
surface closure.
4.4.2
Bioluminescence Signal Patterns During Healing
The bioluminescence monitoring system successfully
detected signals from within concrete specimens, with
distinct patterns emerging during the healing process.
Figure 5 shows representative bioluminescence intensity
profiles over time for cracks of different widths.
Figure 5: Bioluminescence intensity profiles during healing of cracks with different initial widths
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Bioluminescence signals were detectable within 2-4 hours
after crack formation and water exposure, indicating rapid
activation of the bacterial healing agents. Signal
intensity
typically peaked between days 3-7,
corresponding to the period of most active bacterial
metabolism and calcium carbonate precipitation. The
signal then gradually declined as bacterial activity
decreased, either due to nutrient depletion or crack closure
limiting water and oxygen availability.
Notably, the integrated bioluminescence signal over time
(area under the curve) showed strong correlation with the
final healing percentage (R² = 0.89), suggesting that total
light output could serve as a predictive indicator of healing
effectiveness.
Spatial mapping of bioluminescence signals, achieved
through the distributed fiber optic network, enabled
visualization of healing activity along crack paths. Figure 6
presents a time-series of spatial bioluminescence
distributions mapped onto a concrete specimen with an
induced crack.
Figure 6: Spatial distribution of bioluminescence intensity along a crack at different time points during healing
The spatial data revealed that healing typically initiated at
multiple points along the crack rather than progressing
uniformly from the edges, with activity hotspots
corresponding to locations of bacterial carrier clusters.
Over time, these hotspots expanded and merged as
healing progressed throughout the crack volume.
4.4.3
Environmental Effects on Healing and Monitoring
The performance of the self-healing system was
evaluated under three different environmental regimes
to assess its robustness across varying conditions. Figure
7 compares healing efficiency and bioluminescence
signal characteristics across these environmental
scenarios.
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Figure 7: Comparison of healing efficiency and peak bioluminescence intensity under different environmental conditions
Standard conditions yielded the highest healing efficiency
(85%
average
crack
closure)
and
strongest
bioluminescence signals. Cyclic temperature conditions
resulted in moderately reduced performance (72%
healing efficiency), with bioluminescence patterns
showing distinct daily fluctuations corresponding to
temperature cycles.
The field-simulated conditions produced the most
variable results, with significantly different outcomes
across the three simulated climate zones. Temperate
climate simulation yielded results similar to standard
conditions (80% healing), while tropical conditions
showed accelerated healing in the early stages but lower
overall efficiency (68%) due to rapid nutrient consumption
at elevated temperatures. Arid climate simulation
resulted in the lowest healing efficiency (52%), with
intermittent bioluminescence signals corresponding to
wetting events.
Importantly, the correlation between bioluminescence
patterns and healing progression remained consistent
across all environmental conditions when compensated
for temperature effects, confirming the monitoring
system's reliability in diverse scenarios.
4.4.4
Correlation Between Bioluminescence and
Healing Parameters
A comprehensive analysis was conducted to quantify
relationships between bioluminescence signals and
various healing parameters. Table 4 presents the
correlation coefficients between key bioluminescence
metrics and healing outcomes.
Table 4: Correlation Coefficients Between Bioluminescence Metrics and Healing Parameters
Bioluminescence
Metric
Crack
Width
Reduction
Permeability
Reduction
CaCO₃
Precipitation
Strength
Recovery
Peak Intensity
0.76
0.82
0.91
0.73
Time to Peak
-0.58
-0.64
-0.72
-0.51
Signal Duration
0.83
0.79
0.84
0.80
Integrated
Signal
(AUC)
0.89
0.93
0.94
0.85
The integrated signal (area under the curve) showed the
strongest correlations with all healing parameters,
particularly with calcium carbonate precipitation (R² =
0.94) and permeability reduction (R² = 0.93). These
strong correlations validate the use of bioluminescence
as a quantitative indicator of healing effectiveness.
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Multivariate regression analysis yielded a predictive model
for healing outcomes based on bioluminescence
parameters:
H =
0.82(AUC)⁰·⁵⁴
×
0.31(P)⁰·²¹
×
0.26(D)⁰·¹⁸
Where:
●
H = Healing efficiency (percentage of crack width
reduction)
●
AUC = Normalized integrated bioluminescence signal
●
P = Peak bioluminescence intensity (normalized)
●
D = Signal duration (days)
This model achieved a prediction accuracy of 87% for
healing efficiency when tested on validation specimens,
demonstrating
the
practical
utility
of
the
bioluminescence monitoring approach for quantitative
healing assessment.
4.5
Field Validation and Long-Term Performance
4.5.1
Monitoring System Durability
The long-term functionality of the monitoring system was
evaluated through continuous operation under field-
simulated conditions. Figure 8 shows the signal detection
reliability over a 12-month period with repeated healing
cycles.
Figure 8: Monitoring system signal detection reliability over 12 months of operation
The optical fiber network maintained signal transmission
efficiency above 80% throughout the 12-month testing
period, with gradual degradation attributed primarily to
fiber connection points rather than the embedded fibers
themselves. The most significant challenge to long-term
monitoring was biofouling of the fiber tips at crack locations,
which reduced signal collection efficiency over time. This
was partially mitigated by periodic washing cycles that
removed precipitate buildup from fiber surfaces.
The electronic components of the monitoring system,
including the CCD detector and data acquisition hardware,
maintained full functionality throughout the testing
period when properly protected from environmental
exposure. The portable PMT-based system proved more
robust for field applications, with consistent
performance despite temperature fluctuations and
occasional exposure to high humidity.
4.5.2
Multiple Healing Cycles
The capacity for multiple healing events was assessed
through repeated cracking and healing cycles on the
same specimens. Figure 9 illustrates healing efficiency
over consecutive healing cycles for specimens with silica
gel-encapsulated
B. subtilis
.
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Figure 9: Healing efficiency over consecutive crack-heal cycles
The system demonstrated remarkable capacity for
repeated healing, with only modest reduction in efficiency
over four consecutive cycles. First-cycle healing averaged
85% crack closure, decreasing to 76%, 68%, and 61% in
subsequent cycles. This gradual reduction was attributed
to three factors: consumption of nutrients embedded in
the concrete matrix, decreasing bacterial viability over
time, and accumulation of healing products near crack
surfaces that limited bacterial access to fresh cracks.
Bioluminescence monitoring provided valuable insights into
these repeated healing events, with signal strength
progressively decreasing in each cycle. The reduction in
bioluminescence preceded and predicted the decline in
healing efficiency, confirming the monitoring system's
utility for assessing remaining self-healing capacity.
4.5.3
Bioluminescence Signal Thresholds and Predictive
Maintenance
The established correlations between bioluminescence
signals and healing outcomes enabled the development
of threshold values for predictive maintenance
applications. Table 5 presents the derived threshold values
for different levels of healing activity.
Table 5: Bioluminescence Signal Thresholds for Healing Activity Assessment
Healing
Activity
Level
Bioluminescence
Threshold
(RLU/cm²)
Predicted Crack Closure Rate
(μm/day)
Minimal
10² - 10³
< 5
Low
10³ - 10⁴
5 - 15
Moderate
10⁴ - 10⁵
15 - 30
High
10⁵ - 10⁶
30 - 50
Very High
> 10⁶
> 50
These thresholds were incorporated into the monitoring
system's data analysis algorithms to enable automated
assessment of healing activity and prediction of
maintenance needs. When bioluminescence signals fell
below the "Low" threshold during a healing event, the
system could trigger alerts indicating potentially
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insufficient healing that might require external
intervention.
Field validation confirmed that these threshold-based
predictions achieved an accuracy of 83% in identifying
instances where external repair would be necessary,
demonstrating the practical utility of the monitoring system
for infrastructure management.
4.5.4
Economic and Life Cycle Assessment
A comprehensive economic analysis was conducted to
assess the cost-effectiveness of the bioluminescent self-
healing concrete system compared to conventional
concrete with traditional maintenance. Table 6
summarizes the key economic parameters for a typical
bridge deck application over a 50-year service lif
Table 6: Economic Comparison of Conventional vs. Self-Healing Concrete (per m³)
Parameter
Conventional
Concrete
Self-Healing
Concrete
Initial Material Cost
$180
$320
Installation Cost
$120
$150
Monitoring
System
Cost
$0
$45
Maintenance
Frequency
Every 7-10 years
Every 20-25 years
Repair Costs (50 years)
$480
$120
Total Life Cycle Cost
$780
$635
Service Life
50 years
75+ years
Despite the higher initial cost (+78%), the self-healing
concrete system demonstrated a 19% reduction in total life
cycle cost due to substantially reduced maintenance
requirements and extended service life. The real-time
monitoring capability provided additional value through
early detection of potential issues and optimization of
maintenance scheduling.
Life cycle assessment (LCA) further revealed environmental
benefits, with the self-healing system reducing the carbon
footprint by approximately 37% over the full life cycle
compared to conventional concrete with regular
maintenance. This reduction was primarily attributed to
avoided repair activities and the extended service life that
delayed replacement.
V.
CONCLUSION
This research successfully developed and validated a
novel approach for real-time monitoring of self-healing
processes in biocement through the integration of
bioluminescent bacteria and distributed optical sensing. The
key findings and contributions of this work include:
1.
The successful genetic modification of construction-
relevant bacterial species (
B. subtilis
,
S. pasteurii
, and
P. aeruginosa
) to express stable, metabolically-
linked bioluminescence through two distinct
luciferase systems.
B. subtilis
with firefly luciferase
emerged as the optimal combination, providing
strong light signals with excellent correlation to
healing activity across diverse environmental
conditions.
2.
Development of a silica gel encapsulation method that
provides superior protection for bacterial agents
during concrete mixing (>90% survival) while
maintaining
appropriate
light
transmission
characteristics and minimizing impact on concrete
mechanical properties (<5% strength reduction).
3.
Integration of a distributed optical fiber sensing
network capable of detecting bioluminescence
signals from within concrete matrices, enabling real-
time, non- destructive monitoring of bacterial
metabolism and associated healing processes with
microscopic spatial resolution.
4.
Demonstration of strong correlations between
bioluminescence signals and healing parameters, with
integrated signal (area under the curve) showing
particularly strong relationships with calcium
carbonate precipitation (R² = 0.94) and permeability
reduction (R² = 0.93).
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5.
Validation of the monitoring system's long-term
functionality through 12 months of continuous
operation, with the ability to track multiple healing
cycles and predict maintenance needs based on
signal threshold analysis.
6.
Life cycle assessment showing that despite higher
initial costs, the self-healing concrete system with
integrated monitoring capabilities reduces total life cycle
costs by 19% and carbon footprint by 37% compared
to
conventional
concrete
with
traditional
maintenance.
These findings represent a significant advance in both self-
healing concrete technology and structural health
monitoring approaches. By enabling real-time, in situ
observation of biological healing processes, this system
provides unprecedented insights into the dynamics of
biocement behavior under actual service conditions.
The continuous data stream from embedded monitoring
allows for optimization of healing parameters,
verification of performance, and implementation of
predictive maintenance strategies that maximize
infrastructure resilience while minimizing intervention
costs.
The technology developed in this research has
immediate applications in critical infrastructure where
repair access is limited or costly, such as underground
structures, marine environments, and transportation
infrastructure in remote locations. Beyond concrete, the
approach could be extended to other cementitious
materials and possibly to diverse self-healing systems
across the construction industry.
Future research directions should focus on further
enhancing the longevity of the bioluminescent bacteria
for multi-decade monitoring, expanding the detection
sensitivity for earlier crack identification, and developing
integrated data analysis systems that combine
bioluminescence data with other structural health
parameters
for
comprehensive
infrastructure
management platforms.
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