We provide the computational layer between chemical intuition and the laboratory bench — helping R&D teams identify the most promising materials before synthesis begins.
For R&D teams in coatings, polymers & specialty chemicals
We help R&D teams evaluate thousands of molecular candidates — computationally — before a single experiment begins. The result is a focused shortlist backed by physics, not guesswork.
Traditional trial-and-error is slow, expensive, and explores only a fraction of the possible design space. We change that equation.
Rank candidates by theoretical performance to focus resources on high-probability leads — before synthesis begins.
Identify stability issues or molecular incompatibility early, avoiding costly wasted synthesis time.
Gain mechanistic insight into why certain molecules perform — guiding the next generation of design.
A structured four-stage workflow to move from idea to experimental validation.
Industry clients need more than a result — they need to trust the process behind it.
The goal is not to replace the chemist,
but to give them a map.
— Moltera Methodology
Tell us about your R&D challenge and we'll discuss whether computational screening can help.
Start a ConversationWe provide the computational layer between your chemical intuition and the laboratory bench.
Modern materials R&D must evaluate thousands of potential molecules, additives, and formulations. Traditional trial-and-error experimentation is slow, expensive, and often explores only a tiny fraction of the possible design space.
We apply physics-based computational screening to evaluate candidate molecules before laboratory testing — allowing R&D teams to focus their experimental resources on the most promising leads.
A systematic approach to narrowing the search space.
We begin by defining the search space. You provide candidate structures (SMILES / 2D representations), a defined chemical family, or a list of supplier options. We align on the key performance indicators (KPIs) relevant to your application.
We configure physics-based simulations — primarily DFT and related electronic-structure methods — tailored to the property of interest. This step is computationally intensive and is executed on high-performance clusters appropriate to the scope of the study.
Raw data is meaningless without context. We analyse the computed descriptors against your KPIs, identifying trade-offs and ranking candidates by relative likelihood of meeting experimental objectives.
The final deliverable is a technical report detailing the top candidates, the rationale for their selection, and risk factors. This allows your lab team to focus synthesis efforts on the most promising leads.
"The goal is not to replace the chemist, but to give them a map."
We structure our work around your R&D questions, not rigid packages.
For early-stage feasibility.
A tightly scoped initial project designed to define the viable design space and inform the next phase of work. Establishes the modelling framework and feasibility boundaries.
For experimental prioritisation.
Our core engagement. We screen a defined library of candidates against agreed KPIs to produce a prioritised shortlist for experimental validation. Includes full data interpretation and mechanistic rationale.
For continuous support.
For teams requiring recurring computational input across multiple questions. Work is structured as a series of defined projects, informed by evolving experimental data.
A specialist computational chemistry consultancy serving industrial R&D.
Moltera was established to bridge the gap between academic computational chemistry and industrial materials development. While physics-based modelling is a powerful tool, it is often underutilised in industry due to time, cost and integration constraints.
We are a founder-led consultancy with deep expertise in molecular simulation and computational screening. We are not a software vendor; we work on focused, project-based engagements aligned to specific R&D questions.
Our methodology is grounded in first-principles physics. We believe that robust decision support requires understanding why a molecule performs, not just that it might.
We work primarily with R&D teams in sectors where molecular design is critical: coatings, additives, adhesives, and specialty formulations.
To provide objective, data-driven guidance that respects the complexity of materials science and the practical constraints of the laboratory.
We invite technical leads and R&D managers to discuss their screening challenges.
NDA available on request prior to any substantive discussion.