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TECHNOLOGY/BUSINESS OPPORTUNITY High Throughput Materials Screening

USARFP notice for TECHNOLOGY/BUSINESS OPPORTUNITY High Throughput Materials Screening. The reference ID of the tender is 122251868 and it is closing on 07 Aug 2025.

Tender Details

  • Country: USA
  • Summary: TECHNOLOGY/BUSINESS OPPORTUNITY High Throughput Materials Screening
  • UST Ref No: 122251868
  • Deadline: 07 Aug 2025
  • Financier: Self Financed
  • Purchaser Ownership: Government
  • Tender Value: Refer Document
  • Notice Type: Tender
  • Document Ref. No.: IL-13738
  • Purchaser's Detail:
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  • Description:
  • Description
    Opportunity:
    Lawrence Livermore National Laboratory (LLNL), operated by the Lawrence Livermore National Security (LLNS), LLC under contract no. DE-AC52-07NA27344 (Contract 44) with the U.S. Department of Energy (DOE), is offering the opportunity to enter into a collaboration to further develop and commercialize its Automated High-Throughput Materials Optimization Active-Mixing DIW Platform.

    Background:
    Polymer materials formulation and optimization has been generally limited to mixing by hand, as polymers have a wide range of viscosities. A high throughput approach is therefore needed to enable faster screening of polymers optimized for targeted applications. There currently exists systems that mix multi-materials with disparate viscosities. If these systems are integrated with an in-situ characterization capability combined with machine learning experimental planning systems, an all-in-one polymer optimization and screening platform could be developed that can facilitate high-throughput materials development.

    Description:
    The platform has three major components:
    (1) active-mixing direct-ink-write
    (2) in situ characterization substrates or probes
    (3) active learning experimental planning system.

    Active-mixing direct ink write (DIW) additive manufacturing enable mixing of materials with highly disparate viscosities, from liquids to pastes. By coupling this mixing system with in-situ characterization methods with machine learning experimental planning systems, LLNL researchers developed an automated platform for materials discovery and optimization.
    Machine learning models take the data from the DIW AM prints and use it to dictate the next batch of films to be printed, homing in on the formulation that achieves the best desired property required for the target application. While active mixing DIW has already been developed [Harvard-s U.S. Patent No 10,071,350], the novelty of this LLNL inventio...
  • Documents:

 Tender Notice

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TECHNOLOGY/BUSINESS OPPORTUNITY High Throughput Materials Screening - USA Tender

The ENERGY, DEPARTMENT OF, a Government sector organization in USA, has announced a new tender for TECHNOLOGY/BUSINESS OPPORTUNITY High Throughput Materials Screening. This tender is published on USARFP under UST Ref No: 122251868 and is categorized as a Tender. Interested and eligible suppliers are invited to participate by reviewing the tender documents and submitting their bids before the deadline on 2025-08-07.

The estimated tender value is Refer Document, and full details, including technical specifications and submission requirements, are provided in the official tender documents. Ensure all submissions meet the criteria outlined to be considered for evaluation.

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