Researchers from Singapore-MIT Alliance for Research and Technology (SMART) have developed
the world’s smallest LED (light emitting diode) that enables the conversion of existing
mobile phone cameras into high-resolution microscopes. Smaller than the wavelength of
light, the new LED was used to build the world’s smallest holographic microscope, paving the
way for existing cameras in everyday devices such as mobile phones to be converted into
microscopes via only modifications to the silicon chip and software. This technology
also represents a significant step forward in the miniaturisation of diagnostics for
indoor farmers and sustainable agriculture.
This breakthrough was supplemented by the researchers’ development of a revolutionary
neural networking algorithm that is able to reconstruct objects measured by the holographic
microscope, thus enabling enhanced examination of microscopic objects such as cells and bacteria
without the need for bulky conventional microscopes or additional optics. The research also paves
the way for a major advancement in photonics - the building of a powerful on-chip emitter
that is smaller than a micrometre, which has long been a challenge in the field.
The light in most photonic chips originates from off-chip sources, which leads to low
overall energy efficiency and fundamentally limits the scalability of these chips. To
address this issue, researchers have developed on-chip emitters using various materials such
as rare-earth-doped glass. While emitters based on these materials have shown promising
device performance, integrating their fabrication processes into standard complementary metal-oxide-semiconductor
(CMOS) platforms remains challenging. While silicon (Si) has shown potential as a candidate
material for nanoscale and individually controllable emitters, Si emitters suffer from low quantum
efficiency because of the indirect bandgap, and this fundamental disadvantage combined
with the limitations set by the available materials and fabrication tools has hindered
the realisation of a small native Si emitter in CMOS.
In a recently published Nature Communications paper titled, “A sub-wavelength Si LED integrated
in a CMOS platform”, SMART researchers described their development of the smallest reported
Si emitter with a light intensity comparable to that of state-of-the-art Si emitters with
much larger emission areas. In a related breakthrough, SMART researchers also unveiled their construction
of a novel, untrained deep neural network architecture capable of reconstructing images
from a holographic microscope in a paper titled, “Simultaneous spectral recovery and CMOS
micro-LED holography with an untrained deep neural network” recently published in the
journal Optica.
The novel LED developed by SMART researchers is a CMOS-integrated sub-wavelength scale
LED at room temperature exhibiting high spatial intensity (102 ± 48 mW/cm2) and possessing
the smallest emission area (0.09 ± 0.04 μm2) among all known Si emitters in scientific
literature. In order to demonstrate a potential practical application, the researchers then
integrated this LED into an in-line, centimetre-scale, all-silicon holographic microscope requiring
no lens or pinhole, integral to a field known as lensless holography.
A commonly faced obstacle in lensless holography is computational reconstruction of the imaged
object. Traditional reconstruction methods require detailed knowledge of the experimental
setup for accurate reconstruction and are sensitive to difficult-to-control variables
such as optical aberrations, the presence of noise, and the twin image problem.
The research team also developed a deep neural network architecture to improve the quality
of image reconstruction. This novel, untrained deep neural network incorporates total variation
regularisation for increased contrast and takes into account the wide spectral bandwidth
of the source. Unlike traditional methods of computational reconstruction that require
training data, this neural network eliminates the need for training by embedding a physics
model within the algorithm. In addition to holographic image reconstruction, the neutral
network also offers blind source spectrum recovery from a single diffracted intensity
pattern, which marks a groundbreaking departure from all previous supervised learning techniques.
The untrained neural network demonstrated in this study allows researchers to use novel
light sources without prior knowledge of the source spectrum or beam profile, such as the
novel and smallest known Si LED , fabricated via a fully commercial, unmodified bulk CMOS
microelectronics.
The researchers envision that this synergetic combination of CMOS micro-LEDs and the neural
network can be used in other computational imaging applications, such as a compact microscope
for live-cell tracking or spectroscopic imaging of biological tissues such as living plants.
This work also demonstrates the feasibility of next-generation on-chip imaging systems.
Already, in-line holography microscopes have been employed for a variety of applications,
including particle tracking, environmental monitoring, biological sample imaging, and
metrology. Further applications include arraying these LEDs in CMOS to generate programmable
coherent illumination for more complex systems in the future.
The researcher says that their breakthrough represents a proof of concept that could be
hugely impactful for numerous applications requiring the use of micro-LEDs. For instance,
this LED could be combined into an array for higher levels of illumination needed for larger-scale
applications. In addition, due to the low cost and scalability of microelectronics CMOS
processes, this can be done without increasing the system’s complexity, cost, or form factor.
This enables them to convert, with relative ease, a mobile phone camera into a holographic
microscope of this type. Furthermore, control electronics and even the imager could be integrated
into the same chip by exploiting the available electronics in the process, thus creating
an ‘all-in-one’ micro-LED that could be transformative for the field.
On top of its immense potential in lensless holography, the new LED has a wide range of
other possible applications. Because its wavelength is within the minimum absorption window of
biological tissues, together with its high intensity and nanoscale emission area, this
LED could be ideal for bio-imaging and bio-sensing applications, including near-field microscopy
and implantable CMOS devices. Also, it is possible to integrate this LED with on-chip
photodetectors, and it could then find further applications in on-chip communication, NIR
proximity sensing, and on-wafer testing of photonics.