What’s new in OptiLayer Pro — 2026

This page summarizes the new features and improvements introduced in OptiLayer Pro 2026 compared with version 15.88. The changes span the whole suite: major additions to the OptiLayer design and monitoring tools, a redesigned graphical interface, an improved OptiChar characterization option, and the new OptiMonitor Pro real-time control software.

OptiLayer module

Filter Design

The Filter Design option is intended for designing narrow band pass filters with quarter-wave and multiple quarter-wave optical thickness. The optimization code has been entirely rewritten around a completely new optimization method. As a result, it now works hundreds of times faster than before and can find excellent filter designs with hundreds of layers — results that were unachievable in earlier versions of OptiLayer.

Rugate Synthesis

The Rugate Synthesis mode synthesizes optical coatings with a continuously graded refractive-index profile — so-called rugate filters — which suppress narrow spectral bands while leaving the rest of the spectrum unaffected. The synthesis window has been redesigned around four clearly separated tabs: spectral characteristics (T, R), synthesis progress, the refractive-index profile, and the synthesis parameters.

The following profile parametrizations are supported:

• table-based parametrization;
• apodized sine functions, including multi-apodized variants;
• envelope-and-carrier representation;
• localized packet;
• Fourier band-limited profile;
• wavelet-sparse parametrization (Haar basis);
• several additional parametrizations.

As a prerequisite, a composite material must be defined in the database and included in the starting design before synthesis is initiated.

Design Cleaner and Thin Layer Removal

Important additional options of the Synthesis menu use improved internal algorithms that make them more effective and faster than before. The Design Cleaner tool automatically removes layers that have negligible impact on the merit function and reoptimizes the remaining structure, now converging faster and yielding more compact designs. The Thin Layer Removal option identifies and eliminates physically thin layers more reliably while keeping the spectral performance within the user-specified tolerance.

Extended target specifications

The target specification capabilities have been significantly extended. The Thickness/Stress Target, which had limited functionality in previous releases, is now fully operational. It allows users to formulate linear combinations of the total physical thicknesses of individual coating materials as optimization targets — a key tool for managing mechanical stress in real deposition processes. Based on the Stoney formula, these targets can directly encode stress-balance conditions (for example, by requiring matched material content on front and back coatings) without requiring detailed knowledge of material mechanical properties; the associated merit function contribution is integrated seamlessly into the optimization engine.

The Color Target has also been substantially improved. Color-related optimization now runs noticeably faster, and the Color Analysis window provides a graphical preview of the entered coordinates. Up to 99 color targets can be specified simultaneously across a wide range of color spaces, with support for range targets defined as convex polygons and for anchor-referenced color specifications.

New Monitoring menu

OptiLayer Pro has a new main-menu item, Monitoring. It includes an improved version of the Pre-Production Estimation of Errors option available in previous releases, but practically all other options in this menu are completely new. They let you perform pre-production experiments that assess the applicability of broadband and monochromatic optical monitoring to the production of coatings of different types.

In recent years, tremendous progress has been made in understanding the peculiarities of various monitoring methods — in particular the role of the error self-compensation effect, which can be present in both broadband and monochromatic optical monitoring. OptiLayer Pro can run batch experiments that simulate optical production with various monitoring approaches, allowing you to estimate the expected production quality for any coating design.

For monochromatic optical monitoring, a proper specification of the monitoring spreadsheet is key to successful production: determining the number of witness chips, assigning groups of layers to be monitored on each chip, and choosing an optimal monitoring wavelength for each layer. OptiLayer Pro provides a set of completely new options that solve these problems.

Monitoring Spreadsheet

The OptiLayer Pro Monitor (Monitoring → Monitoring Spreadsheet) is a completely redesigned tool for creating, editing, and analyzing the monochromatic monitoring spreadsheet. Key features include:

• an extended monitoring table with a configurable set of columns (column visibility is preserved between sessions);
• a graphical display of the monitoring signal with support for multi-chip mode, providing separate tabs for each witness chip plus a combined overview;
• a Deposition Chips panel for specifying the number of chips, their substrates and thicknesses, with an Auto-Assign function that distributes layers across chips automatically;
• an integrated Error Analysis panel for immediate quantitative estimation of production errors within the monitoring window;
• accounting for the spectral line width of the light source when calculating the monitoring signal;
• export to the Bühler Leybold and Optorun formats.

Monitoring Simulation

Broadband Monitoring Simulation (Monitoring → Broadband Monitoring Simulation) is a six-step wizard for setting up the deposition process, measurement system, and broadband monitoring device parameters, running the computational experiment, and analyzing the resulting spectral performance.

Monochromatic Monitoring Simulation (Monitoring → Monochromatic Monitoring Simulation) provides a five-step wizard for setting up the deposition process and measurement system parameters, running the experiment, and analyzing the results. Four automatic wavelength-selection strategies are available:

1. Most Sensitive Wavelength — selects, independently for each layer, the wavelength at which the derivative of transmittance with respect to thickness |dT/dd| is largest, maximizing sensitivity to thickness deviations.
2. Least Cumulative Errors — accounts for the interaction of errors across layers and sequentially chooses wavelengths that minimize the accumulated thickness error-correction matrix, reducing the cumulative growth of errors.
3. Wavelength Screening — builds a monitoring table with the minimum number of wavelength changes using a greedy forward pass through the layers, subject to signal quality constraints (Entry Variation ≥ 4%; Initial and Final Swing 20–80%).
4. Swing Optimization — uses dynamic programming to optimally partition all layers into a user-specified number of wavelength groups K and selects the best wavelength for each group.

For multi-chip configurations, a fifth strategy — Auto-Assign — simultaneously optimizes the distribution of layers across chips and the choice of monitoring wavelengths. Layers that fail to satisfy the signal quality criteria are highlighted automatically, and any wavelength can be adjusted interactively at any time.

Batch Experiments

The Batch Experiments options (Monitoring → Broadband / Monochromatic Batch Experiments) extend both monitoring simulators by running up to 1,000 independent virtual deposition experiments in parallel using all available processor cores, yielding statistical distributions of the production results. Results are displayed in real time across six tabs:

• ΔMF histogram — distribution of the merit-function increment;
• Yield — cumulative yield curve (fraction of runs with ΔMF below a threshold);
• Thickness errors — mean absolute thickness error by layer;
• Dominant layer — the layer with the largest error, shown as frequency across runs;
• Failed runs — number of failures by layer;
• Results — full table of all runs with ΔMF and per-layer thicknesses.

Status information — active threads, completed and failed experiments, mean ΔMF, its standard deviation, and mean ||Δd|| — is updated continuously. When the tool is invoked again, you can choose to continue accumulating results or start a new series.

Error Self-Compensation

The Error Self-Compensation option (Monitoring → Error self-compensation → Broadband monitoring) provides a quantitative assessment of the self-compensation effect in broadband optical monitoring. When broadband monitoring is used, errors in previously deposited layers influence the spectral reference for subsequent layers, causing the thickness errors of adjacent layers to partially cancel each other — so the spectral quality of the finished coating can be considerably better than individual layer errors alone would predict.

The strength of the effect is evaluated by statistically comparing the impact on the merit function of correlated errors (generated by a fast internal monitoring simulator) and uncorrelated Gaussian errors of the same average RMS magnitude. For each experiment a self-compensation coefficient c = ΔMF(corr) / ⟨ΔMF(norm)⟩ is calculated: c < 1 indicates that self-compensation is present, c > 1 indicates its absence. Its expected value across all experiments — the error self-compensation factor ç — quantifies the overall strength of the effect. Results are presented across five tabs:

• Error Levels — RMS thickness errors by layer for the correlated error set;
• Self-compensation — histogram of the per-run coefficient c, with its expected value shown below the chart;
• Distribution Function — cumulative distribution functions for correlated and uncorrelated errors; the horizontal shift between the curves reflects the strength of the effect;
• RMS Deviations — ±RMS bands of spectral deviation from the theoretical design for both error types;
• Worst Case — maximum spectral deviations within a user-selected fraction of the best experiments (controlled by a slider).

Redesigned graphical interface

The graphical interface has been completely redesigned. All spectral charts and analysis plots are rendered by a modern graphics engine that is noticeably faster and more comfortable to work with: zoom, pan, and reset are smooth and responsive, and the overall appearance is cleaner. A new Dock Mode (Window menu) allows switching from the traditional floating-window layout to a unified single-window workspace in which all panels are embedded within the main application window — eliminating the problem of windows being hidden behind one another. In addition, a Dark Theme switches all windows, charts, and panels to a dark background with appropriately contrasted colors, significantly reducing eye strain during extended work sessions.

OptiChar module

The unique OptiChar n(λ), k(λ) option for investigating complex wavelength dependencies of the refractive index and extinction coefficient has been substantially redesigned to provide reliable characterization of non-dielectric thin films and a wide range of substrates with noticeable absorption losses. New OptiChar project examples demonstrate applications to the characterization of thin metal films, ITO films, non-standard absorbing substrates, and more.

OptiMonitor module

OptiMonitor Pro is OptiLayer’s real-time control software for the deposition of multilayer optical coatings, fully integrated with the OptiLayer Pro ecosystem so that complete projects — designs, materials, and targets — can be loaded directly without special data formats. It supports both broadband and monochromatic optical monitoring simultaneously, with a live visual display of the measured spectral signal alongside the expected characteristics for the current and remaining layers.

Detailed real-time process information — current layer number, deposited and remaining thickness, deposition rate, and estimated time to completion — is displayed throughout the run, and layer termination can be automatic or manual, with a visual alert as each layer approaches its target thickness. Every deposition run, including incomplete ones, is automatically logged to a database for post-production error analysis and subsequent characterization in OptiRE. OptiMonitor Pro also includes a deposition simulator for testing monitoring configurations before production, and supports direct communication with broadband control-system hardware for calibration and signal identification.