Reduce unnecessary testing
Identify lower-priority candidates before they consume substantial laboratory time and resources.
Expert-led computational screening for molecular R&D
Make better molecular decisions before the expensive work begins.
Moltera helps specialty-chemicals and materials R&D teams compare molecular candidates and identify which ones deserve laboratory investigation first.
By evaluating candidates before extensive synthesis, formulation and testing, Moltera helps teams reduce avoidable experiments, focus technical resources and make more informed development decisions.
✓ Fewer avoidable experiments
✓ Faster candidate prioritisation
✓ Clear evidence behind every shortlist
Illustrative decision journeyFrom candidate set to laboratory priorities
Current service workflow
Candidate set
24
Project criteria
Computational evidence
StatesEnvironmentElectronicConfidence
Structured
Scientific review
Prioritised shortlist
Higher priority
Credible alternatives
Review required
Lower priority
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.
Materials and formulation projects often begin with several possible 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 applies a controlled computational chemistry workflow, then scientifically reviews the evidence before delivering a prioritised assessment.
DEFINE THE DECISION
Begin with the actual R&D objective.
Agree the molecular role, relevant characteristics, constraints and what would make a candidate worth advancing.
PROVIDE THE CANDIDATES
Work from the structures already under consideration.
Your team supplies a defined set of discrete small-to-medium molecular candidates and relevant application context.
COMPUTATIONAL EVALUATION
Apply scientific depth where the project requires it.
Depending on the problem, analysis may consider conformations, molecular states, environmental sensitivity, electronic behaviour, ionisation, local reactivity and quality controls.
DECISION ANALYSIS
Compare candidates against project requirements.
Predicted suitability, evidence confidence, defined exclusions, important trade-offs, uncertainty and cases requiring further scientific review remain visibly separated.
EXPERIMENTAL SHORTLIST
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.
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
APPLICATIONS
Support for high-value molecular selection decisions.
Moltera evaluates 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, resin precursors, reactive components and other 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.
New-material development
Compare molecules intended for new formulations, functional materials or development programmes.
Sustainable molecular alternatives
Assess bio-derived or lower-impact candidates 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.
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
Client-facing conclusions are scientifically reviewed and interpreted before delivery.
Designed around experimentation
Moltera strengthens existing laboratory workflows by helping teams decide where experimental effort should be focused first.
ScientificEvidenceDecision support
SCIENTIFIC FOUNDATION
Rigorous underneath.
Rigorous underneath.
Clear in the final decision.
Moltera uses a controlled computational chemistry workflow to examine molecular behaviour that may not be obvious from structure alone.
- Multiple molecular conformations
- Geometry and minimum verification
- Alternative protonation and tautomeric states
- Environment-conditioned molecular behaviour
- Electronic and electrostatic properties
- Ionisation and electron affinity
- Local atomic reactivity
- Calculation provenance
- Scientific confidence
- 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. Client work is delivered through a defined project, scientific review and a client-facing technical assessment.
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 shortlist and technical report
FIRST PROJECT
Start with one important molecular decision.
Tell us about the candidate-selection, formulation or materials-development challenge your team is working on.
Discuss a Project →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
VALIDATION
Built to earn trust through measurable outcomes.
Moltera is designed to improve real experimental decisions.
Successful candidates surfaced
Whether successful candidates appear in the highest-priority groups.
Promising candidates retained
Whether promising candidates are accidentally missed.
Recommendation stability
How stable recommendations are across molecular states and environments.
Experimental burden reduced
Whether Moltera reduces the number of candidates requiring deeper experimental investigation.
Agreement with laboratory outcomes
How computational recommendations compare with laboratory outcomes.
The strongest projects are those where the eventual experimental result can be compared directly with the computational recommendation.
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 an expert-led computational screening and decision-support workflow.
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.
Tell us about the molecular-selection or materials-development challenge your team is facing.