Sb₂S₃ is a chalcogenide material with a heat-controlled transition from amorphous to crystalline phase. Combined with significant changes in optical properties during the transition, it is an extremely interesting and applicable material for applied IR optics. In this talk, we present nanofabricated resonant Sb₂S₃ pillars, showing how methodically designed metasurfaces with these structures can exhibit a wide range of optical properties across the phase change. Furthermore, we show a tunable ability to control these metasurfaces with intentional design.

We present an approach for the physical optics modeling of metasurface-refractive hybrid lenses, emphasizing the task of monitoring polarization variations as the beam propagates through the lens. To address this, we introduce a ray/wave hybrid propagation scheme capable of tracking polarization information as a beam propagates. Through a series of case studies, we demonstrate the applicability of our propagation scheme to both polarization-dependent and polarization-independent hybrid lenses.

This study demonstrates the fabrication of tunable masking layer consisting of gold islands on fused silica substrates. The goal is to produce anti-reflective structured surfaces (ARSS) that correlate to the repeatable and scalable masking step. The transmission enhancement waveband of fused silica is controlled by variations in gold masking islands created through repetitive dewetting process. Gold layer is formed by physical vapor deposition and thermal annealing. Varying deposition thickness and annealing temperature, size and periodicity of gold islands is controlled. With each iterative step of deposition and annealing, relative periodicity established by the initial island formation, or “seed”, is maintained while increasing fill factor in subsequent iterations. Optical transmission spectra were analyzed of the masking layer and formation of metasurface by plasma etching. Results showed that larger deposition thicknesses required higher annealing temperatures to generate circular islands. The seed layer sets the mask periodicity, then the mask fill factor can be increased to allow for deeper etching of ARSS features, for broadband performance. For example, initial deposition thickness of 10nm and repeated iterative steps of deposition and annealing, the fill factor increased (28%, 39%, 47%, 49%), while the island periodicity was maintained at average 91 ± 6nm for all iterative steps. Etching these masked samples resulted in broadband transmission enhancement, over 94% of theoretical maximum. A comprehensive database of masking layer fabrication, resultant surface feature dimensions, and ARSS transmission enhancement capabilities was generated. This scalable masking approach can broaden high laser damage threshold applications utilizing tunable performance ARSS.

Standard scalar wave propagation techniques, such as Fourier optics, struggle with the multi-scale challenges inherent in the inverse design of optical metasurfaces. Conventional approaches often assume that the source and observation planes are axially aligned and share the same spatial size and discretization. This becomes problematic in the case of metasurface design where often the source and observation planes are on the order of the wavelength. Designing metasurfaces nanometer by nanometer for large-scale applications is computationally prohibitive. Current metasurface inverse design methods generally approximate amplitude and phase under the local phase approximation. However, this is insufficient when considering the intricate interactions among nearest neighbors in a metasurface. A more comprehensive understanding requires the consideration of the complex near electric field, which holds richer information about the metasurface’s physics. Yet, computing the resultant complex field at a far distance from the metasurface is both essential for inverse design and challenging. This work presents an evaluation of three computational approaches, i.e., padded field propagation, shifted field propagation, and propagation by the chirp-z-transform, for the explicit purpose of metasurface inverse design. These techniques are implemented in the Pytorch Lightning deep learning framework facilitating optimization using the backpropagation algorithm.

Understanding wave propagation is fundamental across numerous scientific domains, underpinning crucial tasks in acoustics, seismology, radar technology, materials science, and optics. Machine learning methods offer a promising avenue to deepen our understanding of wave propagation dynamics, providing insights into the behavior of nearfield wave patterns. Moreover, well-trained machine learning models have the capacity to generalize beyond specific training data, allowing for predictions in scenarios not explicitly encountered during training. This paper presents a machine learning approach using time-series neural networks to predict the complex near-field wave patterns emerging from metasurface devices. The recurrent neural network (RNN) and the long short term memory (LSTM) models are presented along with a custom dataset that includes 3x3 configurations of meta-atoms. The experiment focuses on assessing the models’ capabilities with varying amounts of input data and explores the challenges posed by predicting propagating waves. Results indicate that the LSTM outperforms the RNN, markedly in learning training data, highlighting its efficacy in capturing complex dependencies. Analysis of error metrics reveals insights into the impact of dataset size on model performance, with larger datasets posing computational challenges but potentially enhancing generalization. Overall, this study lays the foundation for advancing the use of time-series machine learning models for applications involving wave propagation, with implications for various applications in photonics and beyond.

The integration of neural networks and differentiable scalar wave optics has facilitated a modern approach to the design of optical systems, where simulation and optimization are carried out concurrently. These techniques encode the equations of wavefront propagation and modulation directly as layers of a neural network where the forward pass carries out simulation and the backward pass carries out optimization using the backpropagation algorithm. While this allows standard optical optimization as well as classifier-driven optimization of diffractive optics, it suffers from the ubiquitous simulation-to-reality gap. Identifying, characterizing, and ultimately reducing this simulation-to-reality gap is an ever-present objective – as the adage goes, “all models are wrong, some are useful.” To this end, this work extends recent advancements in physics-aware training where an optimizable physical device is used alongside in-silico simulation. By comparing the simulation output with the measured result from the physical device, an additional error term is introduced to the optimization objective. This work analyzes the multi-criteria loss function by varying weighting terms and analyzing performance. It is found that minimizing this new error term reduces the simulation-to-reality gap but at the cost of device performance. The optimizable device in this work is implemented using a reprogrammable spatial light modulator.

Optical cross section (OCS) is an important metric for optical systems in which unintended back reflections that propagate towards object space are of concern. This paper discusses the derivation and implementation of a first-order optical cross section (OCS) calculation. The Lagrange invariant is invoked to derive an expression for OCS based solely on a paraxial ray trace and is applicable for any optical surface within the system. It is shown that an explicit reverse ray trace is not required to complete the calculation. This approach enables rapid calculation of OCS for all surfaces within a lens system and is suitable for use during lens design optimization. The validity of the OCS expression relative to far-field diffraction calculations is examined in terms of the Fresnel number of the near field (exiting) beam. For this purpose, it is shown that the Lagrange invariant can be employed to perform an “effective” reverse ray trace so that the Fresnel number of the exiting beam can be calculated. The validity of the paraxial calculations in the presence of lens aberrations is also explored using real ray tracing.

The Chrisp Compact Visible-SWIR Spectrometer (CCVIS) was developed by MIT Lincoln Laboratory as a high performance, low Size-Weight-Power (SWAP) slit-based hyperspectral sensor that provides comparable performance to current fielded units but more than an order smaller in packaging volume. The design takes advantage of a flat, immersed grating and a color-corrected catadioptric layout to provide >25mm slit length operating from 380-2500nm. We show results from our efforts to design and build an environmentally robust variant which undergoing Technology Readiness Level 6 testing for future spaceflight.

This brief will overview Optimax’ progress since 2019 on developing the necessary DE manufacturing capabilities and working towards offsetting lead time risk. Optimax will review the learnings taken from the fabrication of multiple operationally relevant OAPs and how these learnings benefit transition to programs of record.

In this paper, edge filters including short pass (SP) filters and long pass (LP) filters are reviewed in terms of definition and features. The necessity of SP and particularly LP filters and their functions in an optical system are addressed in depth. Principles of defining the OD level in the blocking band are elaborated for different spectra ranges, particularly for long wavelength LP filters. For SP filters, the filter design, performance, and potential applications are discussed. An example is given on a DUV filter via reactive plasma ion assisted deposition of HfO2/SiO2 that suppresses solar background at wavelengths above 300 nm and transmits 260-290 nm radiation. For LP filters, the design principles of the blocking band for the LP filter using the substrate, absorption material in coating, and interference type reflective coating are discussed. Semiconductor materials and doping levels for different bandgap energies and cut-on wavelengths are proposed for blocking band solutions. Examples of design practices cover a broad spectra range including short wavelength infrared (SWIR), mid-wavelength infrared (MWIR), and long wavelength infrared (LWIR). Coating challenges, for example element segregations in the deposition of a compound semiconductor, are discussed. Finally, quality control and related issues are also addressed.

Sulfur is an earth abundant element that can be combined with organic crosslinking molecules to synthesize polymers through a process called inverse vulcanization. The resulting polymer materials can be fabricated to possess advantageous optical properties, including high refractive index and optical transparency in the infrared (IR) region of the electromagnetic spectrum. Despite their potential use in various optical platforms, implementing these sulfur-rich polymers into practical applications is a non-trivial endeavor. The work presented details efforts in developing these materials into optical polymer preforms and optical polymer fibers for use as waveguides in the IR.

GRIN materials can help compensate chromatic aberrations and enhance athermalization in an optical system, leading to more lightweight and compact lens assemblies, often with a lower number of elements. For several years, Umicore and ISCR in Rennes have developed GRIN materials for systems, using several approaches to modify the index in a chalcogenide glass. We will mention two of the most promising paths in this review: partial and spatially controlled crystallization by fast heating of the perimeter of a glass rod and ionic exchange which modifies locally the glass composition, leading to local changes in refractive index.

SupremEX^® 640XA Al-SiC MMC and AyontEX^™ 13 Al-Si alloy are advanced aluminum-based materials developed by Materion Corporation that are under consideration for mirrors and related precision structures for high performing land, sea, air, and space applications. SupremE X^® 640XA is a Metal Matrix Composite (MMC) with a 6061B aluminum alloy matrix reinforced with 40vol.% ultrafine Silicon Carbide particles and is harder, lighter, and stiffer than Titanium 6Al4V with excellent fracture toughness and fatigue resistance. AyontEX^™ 13 is a hypereutectic Aluminium-Silicon alloy and is both lighter and stiffer than aluminum alloy 6061-T6. Both materials also have CTEs that are well matched to that of electroless nickel plating (13ppm/°C) commonly used for mirror applications. Our investigations demonstrate that these materials can sustain requisite properties of finished mirrors operating at visible wavelengths and over broad ranges of operational temperature. A 150mm aperture finished light-weighted concave spherical test mirror was designed and manufactured according to developed manufacturing guidelines for both materials and is representative of design forms for airborne and space applications. Optical finishing operations inclded diamond point turning (DPT) and loose abrasive polishing. By use of laser interferometry, mirror figure stability was verified after multiple thermal cycles. Similar interferometric measurements were then repeated when subjecting the test mirrors to hot and cold temperature excursions under vacuum. These experiments were also performed both before and after the application of electroless nickel plating. Also considered were concepts for precision structures that are best fitted to the unique manufacturing-related characteristics of these materials.

This paper illuminates the scientific footsteps of the Short-Wave Infrared (SWIR) detectors, tracing the journey of the growth and development in this critical technology area from its early days in 1969 to its swift ascent in 2023. Employing bibliometric information and VOSviewer examination, we unveil major tendencies, thematic clusters, and the dynamic swelling of the scientific publications, spotlighting the burgeoning interest and technological evolution of SWIR detectors. Our research pieces together the key stages of SWIR technology emergence, originating from the initial revelations, advances in material science and also expansion of application spheres from military surveillance to environmental monitoring and medical imaging. Thus, we shed a light on the tremendous sway of SWIR detectors on the optical engineering and also photonics, attributable to their distinct capabilities to resolve current challenges. The findings throw a lot of light on the maturation within the SWIR detector research, underlining its heightening significance in both scientific and also industrial applications. This paper is a very comprehensive overview of the SWIR detector landscape that elaborates the successes of the past and also the trajectory of the future for the researchers, practitioners, and policymakers journeying in this transformative field.