Reduce unnecessary testing
Identify lower-priority candidates before they consume substantial laboratory time and resources.
Expert-led computational screening for molecular R&D
Make bettermolecular decisions.Before the expensive
work begins.
Moltera helps specialty-chemicals and materials R&D teams compare defined molecular candidates and decide which ones deserve laboratory investigation first.
✓ Designed to reduce avoidable experiments
✓ Designed to accelerate candidate prioritisation
✓ Evidence behind every recommendation
PHYSICS-BASEDMolecular evidence.
Expert-led. AI-assisted.Experimental validation remains essential.
Conceptual molecular illustrationExplore the approach
Physics-based molecular evidence is combined with AI-assisted scientific review so complex computational chemistry becomes usable decision support — without requiring your team to be computational chemistry specialists.
THE DECISION LAYER
Focus experimental effort where it is most likely to create value.
Shorten candidate-selection cycles
Move from a broad set of possible molecules to a structured experimental shortlist more quickly.
Improve decision confidence
Understand the evidence, assumptions, uncertainty and trade-offs behind each recommendation.
THE PROBLEM
Too many plausible candidates.
Too many plausible candidates.
Too little time to investigate them all.
Specialty-chemical and materials R&D programmes often begin with several plausible molecular options.
Each candidate may appear promising, but assessing every option experimentally can consume significant laboratory time, technical capacity and development budget.
Moltera helps narrow the search before the most resource-intensive work begins.
Moltera does not replace experimentation.
Better candidates into the lab.
Fewer avoidable dead ends.
It improves the decision about what to investigate first.
HOW IT WORKS
From candidate set to experimental priorities.
Moltera generates project-relevant molecular evidence, then combines expert oversight with AI-assisted scientific review before delivering a prioritised assessment.
01DEFINE THE DECISIONBegin with the actual R&D objective.
Begin with the actual R&D objective.
Agree the molecular role, relevant characteristics, constraints and what would make a candidate worth advancing.
02PROVIDE THE CANDIDATESWork from the structures already under consideration.
Work from the structures already under consideration.
Your team supplies a defined set of discrete molecular candidates, or a clearly bounded molecular family, together with the application context that matters to the decision.
03COMPUTATIONAL EVALUATIONApply scientific depth where the project requires it.
Apply scientific depth where the project requires it.
Depending on the problem, Moltera evaluates the molecular behaviour most relevant to the decision — such as stability, environment sensitivity, electronic behaviour, reactivity, energetics or photochemical behaviour.
04AI-ASSISTED SCIENTIFIC REVIEWTurn technical evidence into a usable decision.
Turn technical evidence into a usable decision.
AI helps organise and interrogate the evidence while expert review keeps suitability, confidence, trade-offs, uncertainty and evidence gaps visibly separated.
05EXPERIMENTAL SHORTLISTReceive a practical testing strategy.
Receive a practical testing strategy.
See which candidates deserve investigation first, which alternatives remain credible, why they sit where they do and where more evidence is needed.
THE MOLTERA APPROACH01 — 05
01 / Define the decision
The objective, constraints and criteria establish what makes a candidate worth advancing.
An expert-led managed serviceIllustrative process
HOW MOLTERA STRUCTURES A DECISION
A clear route from molecular possibilities to laboratory priorities.
This visual represents the current expert-led assessment process. It does not imply a client software platform.
INPUT
Candidate set
Defined molecular structures already under consideration.
→
ANALYSIS
01Project-specific criteria
02Molecular states
03Environment sensitivity
04Evidence confidence
Scientific evidence
→
OUTPUT
Prioritised assessment
Higher priorityTest first
Credible alternativesKeep visible
Review requiredEvidence gap
Lower priorityDeprioritise
WHAT YOU RECEIVE
A decision-ready evidence package.
The output is designed around one practical question: which candidates deserve experimental attention first, why, and with what level of confidence?
Prioritised candidate assessment
Ranked or grouped priorities appropriate to the available evidence and decision criteria.
Evidence behind each recommendation
The molecular evidence that materially affected the prioritisation remains visible.
Trade-offs and uncertainty
Competing criteria, limitations and scientific confidence are kept separate from apparent suitability.
Evidence gaps
Cases requiring more information are flagged rather than forced into false certainty.
Experimental priorities
A practical recommendation for which candidates deserve laboratory attention next.
Supporting methods, provenance and quality controls are retained so the assessment remains traceable without requiring the client team to operate the underlying computational workflow.
APPLICATIONS
Support for high-value molecular selection decisions.
Moltera evaluates defined discrete molecular candidates used within wider material and formulation systems.
Candidate prioritisation
Compare a defined set and identify which candidates deserve laboratory investigation first.
Molecular building-block selection
Evaluate monomers, reactive diluents, molecular precursors and other defined discrete building blocks.
Additives and functional molecules
Compare additives, inhibitors, photoinitiators and other functional candidates.
Reformulation and replacement
Prioritise alternatives driven by regulation, supply, cost, sustainability or performance requirements.
Molecular selection for new-material development
Compare defined molecular candidates within a broader formulation or materials-development programme.
Sustainability-driven molecular alternatives
Compare bio-derived or sustainability-driven candidates against project-relevant molecular criteria before substantial synthesis and testing.
Molecular screening for formulated materials
Support molecular ingredient selection for coatings, resin systems, polymer-related applications, adhesives, inks, composites, corrosion protection and photochemical systems.
Current focus
The analysis focuses on discrete molecular candidates used within these systems, helping teams decide which options warrant deeper formulation and experimental investigation. Moltera does not model whole formulations, polymer networks, morphology, rheology or finished-product performance. Experimental validation remains essential.
WHY MOLTERA
Built on physics.
Built on physics.
Designed for decisions.
Many computational tools are designed to produce calculations. Moltera is designed to help R&D teams decide what to do next.
Application-specific
The analysis reflects the actual objective, constraints and molecular mechanisms relevant to the project.
Explainable
Every recommendation is linked to calculated evidence, defined criteria and visible assumptions.
Uncertainty-aware
Predicted suitability remains separate from scientific confidence.
Auditable
Structures, methods, settings, outputs and quality checks remain recorded throughout the workflow.
Expert-led, AI-assisted
AI supports evidence integration and scientific review; client-facing conclusions remain under expert oversight before delivery.
Built for R&D teams
Your scientists receive decision-ready evidence rather than raw computational outputs, so they do not need to be computational chemistry specialists.
Evidence → interpretationFIG. 02
Molecular statesElectronic behaviourEnvironment sensitivityLocal reactivity
COMPUTATIONAL CHEMISTRYMolecular evidence
AI-ASSISTED SCIENTIFIC REVIEWIntegration & interpretationExpert oversight
Decision support for laboratory priorities
PHYSICS + AI
Physics generates the evidence.
Physics generates the evidence.
AI helps turn it into a decision.
Moltera combines controlled computational chemistry with an AI-assisted scientific review layer. The calculations create the molecular evidence; AI helps organise, interrogate and communicate that evidence in a form industrial R&D teams can use.
- Molecular structure and stability
- Context-relevant molecular states
- Environment sensitivity
- Electronic and redox behaviour
- Local molecular reactivity
- Reaction and bond energetics where relevant
- Photochemical behaviour where relevant
- Scientific confidence and evidence gaps
- Calculation provenance and traceability
- Project-specific decision criteria
The primary output remains practical
Which candidates deserve experimental attention first — and why?
EXPERIMENTAL FIT
Designed to strengthen experimental decisions.
Moltera evaluates molecular candidates before extensive laboratory work begins, helping teams develop a stronger shortlist and clearer experimental strategy.
Final material performance also depends on factors such as formulation composition, concentration, processing, curing, interfaces and manufacturing conditions.
Better-prioritised candidates
Clearer scientific hypotheses
Greater visibility of uncertainty
Fewer avoidable experimental dead ends
CURRENT DELIVERY MODEL
Expert-led computational screening.
Moltera currently operates as a managed scientific service. Each engagement is scoped around a defined molecular decision and delivered as a decision-ready evidence package.
01Definition of the technical decision
02Review of candidate structures
03Agreement of relevant success criteria
04Computational evaluation and quality control
05Interpretation of uncertainty and trade-offs
06Prioritised assessment, experimental priorities and technical provenance
FIRST PROJECT
Start with one important molecular decision.
Start with a concise Problem Brief describing the molecular-selection decision your team is facing. High-level context is enough for an initial review.
Start a Problem Brief →01Understand the technical objective
02Assess whether Moltera is suitable
03Review the candidate set
04Agree the relevant molecular evidence
05Define success criteria
06Propose a focused first project
ABOUT MOLTERA
Turning computational chemistry into practical R&D action.
Moltera was created to close the gap between advanced molecular modelling and the decisions industrial scientists make every day.
Generating molecular properties is not enough. R&D teams need to understand which candidates deserve attention, why they appear promising, what trade-offs exist, where uncertainty remains and what should be investigated next.
Moltera brings those elements together through physics-based molecular evidence, AI-assisted scientific review and expert-led decision support.
The long-term vision is to make this capability available through a secure and scalable platform for industrial molecular R&D.
FOUNDER & CEO
Daniel Clark
Daniel developed Moltera through work spanning materials science, computational chemistry and scientific software.
START WITH ONE IMPORTANT MOLECULAR DECISION
Make the next experimental cycle more focused.
Describe the molecular-selection decision your team is facing and Moltera will review the problem directly.