A composition is described comprising semicrystalline polylactic acid polymer; polyvinyl acetate polymer having a glass transition temperature (Tg) of at least 25° C.; plasticizer; and optionally amorphous polylactic acid polymer. In another embodiment the composition further comprises nucleating agent. Also described are films comprising the composition as well as articles, such as a tape or sheet, comprising the film described herein and a layer of pressure sensitive adhesive disposed on the film.

This invention relates to a multilayer biodegradable film which is particularly suitable for the manufacture of packaging and is also characterised by appreciable optical transparency properties in addition to high level mechanical properties.

An amorphous or semi-crystalline polymer/aPHA composition (masterbatch) has a high load of aPHA (30 to 50 wt % based on the total amount of the composition). A method for production of the composition includes two or more split feedings of the aPHA in a blending or mixing or compounding operation. The method includes feeding about 1-15 weight percent (wt %) of the total aPHA in a primary feed hopper of a blending or mixing or compounding apparatus and about 30-49 weight percent downstream in the process.

Provided is a method of producing a film by cryogenically grinding polypropiolactone to form a powder, and extruding the powder to form the film. Provided herein are also polypropiolactone films having certain biocontent and compostability, as well as certain mechanical and physical properties. Such films may also be suitable for use as packaging materials.

Trimmer line compositions and methods for forming trimmer line compositions are provided. The trimmer line compositions include a biodegradable toughening agent and polycaprolactone and advantageously increase the degradability of the trimmer line with minimal-to-no impact on the performance of the composition as trimmer line.

An algae-based thermoplastic composition is provided that includes a protein-rich algae biomass selected from either microalgae, macroalgae or combinations thereof. The protein content is greater than or equal to 15% by weight of the algae biomass and the algae biomass is dried to a moisture content of less than or equal to 15% by weight and having a particle d99 of up to 200 microns. The dried algae biomass is at least 5% by weight of the thermoplastic composition. The composition includes a biodegradable resin configured to exhibit rheological properties suitable for blending with algae including a melting temperature less than 250° C. and a melt flow rate in excess of 0.01 g/10 min.

The invention concerns a polymer composite comprising:

a. biodegradable polymer in an amount of 5-94.5% by weight of the overall weight;

b. flour of pulse in an amount of at least 5% by weight of the overall weight;

c. plasticizer in an amount from 5-50% w/w of component b);

d. optional filler, and

e. optional additive,

wherein

c) is a solid plasticizer with a melting temperature in the range of 70 to 210°. The invention also concerns a process for its preparation, an intermediate, and a solid article comprising the polymer composite.

Computer-implemented methods may include identifying a polymer for decomposition. The method may further include accessing, for an ionic liquid, one or more properties corresponding to the polymer. One or more properties may characterize a reaction between the polymer and the ionic liquid. The method may also include accessing a value of the property using a quantum-mechanical or thermodynamical method. The method may include determining a bond string and position (BSP) representation of a molecule of the ionic liquid. The method may further include determining an embedded representation of the ionic liquid based on the BSP representation. In addition, the method may include generating a relationship between BSP representations of molecules and the one or more properties. The method may also include identifying an ionic liquid as a prospect for depolymerizing the specific polymer based on the relationship. The method may include outputting an identification of the ionic liquid.

Methods may include accessing a first data set that includes a plurality of first data elements. Each of the plurality of first data elements may characterize a depolymerization reaction. Each first data element may include an embedded representation of a structure of a reactant and a reaction-characteristic value that characterizes a reaction between the reactant and a polymer. The embedded representation may be identified as a set of coordinate values within an embedding space. The method may include constructing a predictive function to predict reaction-characteristic values from embedded representations. The method may also include evaluating a utility function that transforms a given point within the embedding space into a utility metric. The method may include identifying particular points as corresponding to high utility metrics. The method may also include outputting a result that identifies a reactant corresponding to the particular point or a reactant structure corresponding to the particular point.

Computer-implemented methods may include accessing a predictive function. The predictive function may be configured to receive a partial or complete bond string and position (BSP) representation of a molecule of a reactant ionic liquid, where the representation identifies relative positions of atoms in the molecule. The predictive function may be configured to predict a reaction-characteristic value that characterizes a reaction between the ionic liquid and a particular polymer. The predictive function may be generated using training data corresponding to a set of molecules that were selected using Bayesian optimization, one or more previous versions of the predictive function, and experimentally derived reaction-characteristic values characterizing reactions between the molecules and the particular polymer. The method may also include identifying a particular ionic liquid as a prospect for depolymerizing the particular polymer based on the predictive function. The method may further include outputting an identification of the ionic liquid.